Decision Support System for Determining the Best Lecturer at Wiraraja University Using the AHP (Analytical Hierarchy Process) Method

Decision Support System for Determining the Best Lecturer at Wiraraja University Using the AHP (Analytical Hierarchy Process) Method | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Decision Support System for Determining the Best Lecturer at Wiraraja University Using the AHP (Analytical Hierarchy Process) Method Wariezatul Hasanah1, Iddrus2 This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7390791/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The selection of the best lecturer at Wiraraja University has been conducted manually, potentially causing inefficiency, subjectivity, and difficulties in managing complex data. This research aims to develop a web-based Decision Support System (DSS) using the Analytical Hierarchy Process (AHP) method to enhance objectivity, transparency, and assessment accuracy. The system employs four evaluation criteria: ( 1 ) Education & Teaching, ( 2 ) Research, ( 3 ) Community Service, and ( 4 ) Supporting Activities. The AHP method calculates criteria and alternative priority weights through pairwise comparisons, followed by a consistency ratio (CR) calculation to ensure judgment consistency. System implementation using PHP, HTML, and MySQL demonstrates improved selection efficiency, reduced recording errors, and data-based ranking of the best lecturers. User testing evaluation confirms optimal system functionality with a consistency rate (CR < 0.1). This system is expected to support strategic university decision- making more fairly and measurably. Theoretical Computer Science Computer Architecture and Engineering Design Thinking E-Achievement Application Development Figures Figure 1 Figure 2 Figure 3 Figure 4 I. INTRODUCTION Lecturers play an important role in higher education through academic activities. The quality of lecturers can be measured through the implementation of the Tri Dharma of Higher Education, which includes teaching, research, and community service. Wiraraja University, as one of the higher education institutions, needs to have an objective and transparent system in determining the best lecturers in order to provide recognition and improve the quality of education. Wiraraja University has approximately 150 lecturers, each of whom engages in different teaching, research, and community service activities. The assessment of the best lecturers is based on several criteria, such as performance in teaching and learning activities, research productivity, and contributions to community service. Currently, the selection of the best lecturers at Wiraraja University is still carried out conventionally, such as based on subjective assessments or manual recapitulation of student scores. This process faces several challenges, such as the lack of measurable standards, potential bias in assessment, and difficulties in managing complex data. Therefore, a Decision Support System (DSS) is needed to assist in the decision-making process in a more objective, accurate, and efficient manner. The Analytical Hierarchy Process (AHP) method is one of the multi-criteria decision-making methods that can be used to evaluate lecturers based on various predetermined aspects. AHP works by comparing criteria in pairs (pairwise comparison) to determine the priority weights of each factor. By applying this method, the system can assist the university in selecting the best lecturers more fairly and in a data-driven manner. II. RESEARCH METHOD A. Research Design The stages of the research conducted are illustrated in the figure below: In the figure above, the research begins with problem identification through interviews and observations at Wiraraja University to identify the challenges in the process of determining the best lecturers, which is still conducted manually. This is followed by a literature review to understand relevant theories and decision-making methods, as well as data collection such as lecturer data, assessment criteria, and related regulations. Next, system analysis and design are carried out by creating use cases, flowcharts, DFDs, and prototypes to illustrate the system to be developed. After that, the system is tested using the AHP (Analytic Hierarchy Process) method to calculate weights and rankings based on objectively defined criteria. The designed system then undergoes a trial phase to ensure its functionality and accuracy, followed by evaluation based on test results and user feedback to identify and improve shortcomings. Finally, the tested and evaluated system proceeds to the implementation stage so that it can be used operationally to support decision-making in determining the best lecturers. B. Reseach Instrument The research instruments used in this study consist of two types, namely hardware and software. The hardware used is a Lenovo ThinkPad T430 laptop with an Intel Dual Core i5 processor up to 3.3 GHz and 4 GB of RAM, which functions to support the design, testing, and implementation of the system. Meanwhile, the software used includes Microsoft Word for report writing, Canva for designing the application prototype interface, XAMPP as a local server for testing the web-based system, and Visual Studio Code as the main code editor to efficiently support the system development process. C. Data Collections Procedures In this study, the data collection procedure was carried out directly from the relevant parties at Wiraraja University, particularly within the General Administration Bureau (BAU), to understand the procedures and systems used in selecting the best lecturers. Through this process, the researcher also obtained data on the lecturers participating in the selection as well as the assessment criteria used as the basis for evaluating the best lecturers. D. Reseach Flow Diagram System design encompasses all information about the process of designing a system. The purpose of system design is to create a model or initial framework of the system to be developed. In this system design, the concept and workflow of the system to be built will be explained. In this study, the researcher will present the use case, flowchart, and Data Flow Diagram (DFD) of the Decision Support System for Determining the Best Lecturer at Wiraraja University using the Analytical Hierarchy Process (AHP) method. III. RESULTS AND DISCUSSION A. System Development Results The Decision Support System (DSS) for determining the best lecturer at Wiraraja University has been successfully developed and is ready for implementation. This DSS provides an objective and efficient platform that significantly enhances the transparency, accuracy, and speed of the evaluation process, replacing the previous manual methods and subjective assessments with measurable criteria for lecturer performance. The Dashboard page of the DSS for Determining the Best Lecturer at Wiraraja University functions as an information and navigation center, presenting an overview of the AHP-based system that supports objective and transparent evaluation through features such as Alternative Data, Assessment Criteria, Evaluation, and Result Reports. It also explains the assessment flow, from data input to the determination of the best lecturer based on the highest score. This page is an essential part of the AHP process, allowing users to systematically compare the importance level of each lecturer assessment criterion so that the system can produce objective and consistent decisions. This page displays the report of the best lecturer evaluation results based on the AHP method, where users can select the evaluation year (e.g., 2025) to view the total final score of each lecturer according to the values of the four criteria and AHP weights, with the results presented in a table format. B. System Test Results The testing of the DSS for Determining the Best Lecturer at Wiraraja University was carried out to ensure that the system operates according to its objectives, namely producing lecturer rankings that are objective, transparent, and measurable. This system applies the AHP method to systematically compare criteria and alternatives. The assessment is based on four main criteria: Education and Teaching, Research, Community Service, and Supporting Activities. The process includes constructing the comparison matrix, normalization, priority weight calculation, and consistency testing (CR). If the CR result is below 0.1, the calculation is considered valid. The final score is obtained from the multiplication of lecturers’ performance values with the criteria weights, which are then summed to determine the total score. The system then automatically generates lecturer rankings, serving as the basis for determining the best lecturer by the university in a structured and periodic manner. 1. Determination of Criteria The determination of criteria in this system refers to the regulations already established at Wiraraja University. Each criterion used has been assigned a specific weight. The criteria are as follows: Table 1. Criteria Table Kode Kriteria Bobot K1 Bidang Pendidikan & Pengajaran 35% K2 Bidang Penelitian 40% K3 Bidang Pengabdian Kepada Masyarakat 15% K4 Kegiatan Penunjang 10 % 2. The stages of the Analytical Hierarchy Process (AHP) A Decision Support System (DSS) is a tool that assists in making systematic and objective decisions by considering various alternatives and criteria. One commonly used method is the Analytic Hierarchy Process (AHP), which structures the problem in the form of a hierarchy and uses pairwise comparisons to determine the weight of each criterion and alternative. The AHP process includes defining the goal, comparing criteria and alternatives, calculating priority weights, and conducting a consistency test to ensure the reliability of the decision results. a. Comparison Matrix Between Criteria Table 2 is the pairwise comparison matrix of criteria used in the Analytical Hierarchy Process (AHP). This matrix is utilized to compare the relative importance of each criterion in the decision-making system, in this case, the selection of the best lecturer. Table 2 Comparison Matrix Between Criteria Kriteria K1 K2 K3 K4 K1 1 3 2 2 K2 0.3333 1 2 2 K3 0.5 0.5 1 1 K4 0.5 0.5 1 1 Total Bobot Kolom 2.333 5.000 6.000 6.000 b. Normalization Calculation Table 3 presents the results of the normalization process of the criteria comparison matrix in the Analytical Hierarchy Process (AHP). The purpose of this process is to ensure that each value in the column is proportional and can be used to determine the priority weight of each criterion. This normalization is carried out by dividing each element in the column by the total sum of that column, which was previously calculated in the initial comparison matrix. Table 3 Criteria Matrix Normalization & Weights Kriteria K1 K2 K3 K4 K1 0.429 0.600 0.333 0.333 K2 0.143 0.200 0.333 0.333 K3 0.214 0.100 0.167 0.167 K4 0.214 0.100 0.167 0.167 c. Calculating the Preference Value (Final Score) The Table of Priority Weights and Consistency Measure (CM) represents the final result of the AHP process after the normalization of the criteria comparison matrix. Criterion K1 has the highest weight of 0.424, indicating the greatest level of importance, followed by K2 (0.252), as well as K3 and K4, each with a weight of 0.162. The Consistency Measure (CM) value is obtained by multiplying the priority weights with the sum of the columns in the initial comparison matrix, which is then used to calculate the Consistency Index (CI) of 0.0514. Compared to the Random Index (RI) of 0.90, the Consistency Ratio (CR) is 0.0571 or 5.71%. Since the CR value is less than 10%, the matrix is considered consistent, and the resulting weights can be used in decision-making. Table 4 Preference Value (Final Score) Kriteria Bobot Prioritas Consistency Measure K1 0.424 4.315 K2 0.252 4.126 K3 0.162 4.088 K4 0.162 4.088 CI (Consistency Index): 0.0514 RI (Ratio Index): 0.90 CR (Consistency Ratio): 0.0571 d. Alternative Ranking Table 5 is the alternative ranking table that presents the final assessment results of the two candidates (alternatives) based on the four main criteria, including their total scores and respective rankings. Table 5 Alternative Ranking Alter K1 K2 K3 K4 Tot Ranking Warieza 2.4663 24.0571 24.0846 23.8981 99.7061 1 rieza 2.2663 22.0571 21.0846 20.8981 90.3061 2 IV. CONCLUSION Based on the study on the implementation of a Decision Support System (DSS) using the Analytical Hierarchy Process (AHP) method in determining the best lecturer at Universitas Wiraraja, it can be concluded that the AHP method provides an effective and objective solution in the decision-making process. AHP assists in systematically evaluating lecturers’ performance based on several main criteria determined by the university. Through the pairwise comparison method, AHP generates priority weights that reflect the relative importance of each criterion. The final results of this calculation provide a ranking of lecturers based on their total performance scores, thereby enabling a fair and measurable selection of the best lecturer. References Dewa, W. A., & Rahmawati, L. S. (2018). Analisis dan Desain Sistem Pendukung Keputusan Penentuan Dosen Pembimbing Tugas Akhir Menggunakan Metode AHP. JurnalTechnopreneur(JTech) , 6 (2),81. Herman, H., Riadi, I., Kurniawan, Y., & Rafiq, I. A. (2023). Analisis Keamanan Website Menggunakan Information System Security Asessment Framework(ISSAF). Jurnal Teknologi Informatika Dan Komputer, 9(1), 126–136. Magdalena Sundari, Asnawati Asnawati, & Indra Kanedi. (2024). Sistem Pendukung Keputusan Penilaian Dosen Terbaik Menggunakan Metode Analytical Hierarchy Process (AHP) Studi Kasus Fakultas Keguruan dan Ilmu Pendidikan Universitas Dehasen Bengkulu. Jurnal Ilmiah Teknik Mesin, Elektro Dan Komputer , 4 (1), 28–43. Mie, Y., & Wibowo, C. (2024). Sistem Pendukung Keputusan Metode Analytical Hierarchy Process untuk Penentuan Dosen dengan Kinerja Terbaik pada Fakultas Komputer di Universitas Universal . 4 (2), 44–50. Permatasari, A., & Suhendi, S. (2020). Rancang Bangun Sistem Informasi Pengelolaan Talent Film berbasis Aplikasi Web. Jurnal Informatika Terpadu , 6 (1), 29–37. Sesfao, Y. F., Nababan, D., & Seran, K. J. T. (2024). Penerapan Metode Analitycal Hierarchy Process dalam Rancang Bangun Sistem Pendukung Keputusan Penentuan Dosen Terbaik . 7 (5), 1300–1308. Tri, S., Nova, E., & Muchayan, A. (2024). SISTEM INFORMASI MANAJEMEN SURAT MENGGUNAKAN QR CODE DI LINGKUNGAN STAFF PERSONEL KODAM V / BRAWIJAYA Sembodo Tri Eko Nova Riawan , Achmad Muchayan Program Studi Sistem informasi , Fakultas Teknik dan Ilmu Komputer , Universitas Narotama Kata Kunci : Koda . 9 (1). Yasa, I. W. S., Werthi, K. T., & Satwika, I. P. (2021). Sistem Pendukung Keputusan Penentuan Dosen Terbaik Menggunakan Metode Analytical Hierarchy Process (AHP) Pada STMIK Primakara. Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika (KARMAPATI) , 10 (3), 289. https://doi.org/10.23887/karmapati.v10i3.36824 Nendya, Matahari Bhakti, Budi Susanto, Gabriel Indra Widi Tamtama, and Timotius Johan Wijaya. 2023. “Desain Level Berbasis Storyboard Pada Perancangan Game Edukasi Augmented Reality Tap The Trash.” Fountain of Informatics Journal 8 (1): 1–6. Syarif Muhammad., Nugraha Wahyu, 2020. “Pemodelan Diagram Uml Sistem Pembayarantunaipada Transaksie-Commerce”. Jurnal Pontianak Universitas Bina Sarana. IV,1-7 Tia Arianti, et al., 2022. “Perancangan Sistem Informasi Perpustakaan”. Jurnal Ilmiah Komputer Terapan dan Informasi Pontianak. 1(1),19-25 Taufik, M., & Armansyah, A. (2021). Eksistensi Pelaku Usaha Sektor Informal Offline dan Online di Tengah. Publikauma: Jurnal Administrasi Publik Universitas Medan Area, 9(1), 57-66. Kuryanti, S. J., & Indriani, N. (2018). Pembuatan Website Sebagai Sarana Promosi Pariwisata. Publikasi Jurnal & Penelitian Teknik Informatika, 40-41 . Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7390791","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":501415968,"identity":"8857d2b3-069e-451b-b193-79bcfa0d888f","order_by":0,"name":"Wariezatul Hasanah1, Iddrus2","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYJCCA2CSnYfxAZDi4SNWiwQDMw+zAUgLG7E2gbSwSYBYBLUYHD/78MCHP3Z1Bod5j1V+zbGTYWNgfvjoBj4tZ9INDs7gSZYwOMyXdlt2WzLQYWzGxjl4tJgdSGM4zCPBDNTCY3ZbchvQeUDvSOPVcv4Zw+E/BvVgLcWS2+qJ0HIDaAtDwmGwFsaP2w4T1mJ/4xnDwZ4DxyVnHuYxlmbcdpyHjZmAXyT705g//PhTzc93vMfw489t1fb87M0PH+PTggKYecAkscpBgPEHKapHwSgYBaNgxAAAjOJDyizt48YAAAAASUVORK5CYII=","orcid":"","institution":"Wiraraja University","correspondingAuthor":true,"prefix":"","firstName":"Iddrus2","middleName":"Wariezatul","lastName":"Hasanah1","suffix":""}],"badges":[],"createdAt":"2025-08-17 06:40:43","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7390791/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7390791/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89348543,"identity":"a00726e4-0bfe-4af6-b2ca-8d6182d129b5","added_by":"auto","created_at":"2025-08-19 05:38:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":18825,"visible":true,"origin":"","legend":"\u003cp\u003eResearch Stages\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7390791/v1/ae761f4c6d237bee2526e605.png"},{"id":89349914,"identity":"9f6b305a-5c70-4584-a5aa-4e4316f40a08","added_by":"auto","created_at":"2025-08-19 05:54:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81208,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 1. Student Dashboard Page\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7390791/v1/250cf95bbb5a53267f2ead6d.png"},{"id":89349225,"identity":"8cec2d1c-5f41-432b-a043-59356f45a51f","added_by":"auto","created_at":"2025-08-19 05:46:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":57024,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 2. Assesment Page\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7390791/v1/ed08842985988b716929dbe2.png"},{"id":89348541,"identity":"94109554-1030-460a-892e-59bc5813c670","added_by":"auto","created_at":"2025-08-19 05:38:00","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":123550,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 3. 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INTRODUCTION","content":"\u003cp\u003eLecturers play an important role in higher education through academic activities. The quality of lecturers can be measured through the implementation of the Tri Dharma of Higher Education, which includes teaching, research, and community service. Wiraraja University, as one of the higher education institutions, needs to have an objective and transparent system in determining the best lecturers in order to provide recognition and improve the quality of education.\u003c/p\u003e\u003cp\u003eWiraraja University has approximately 150 lecturers, each of whom engages in different teaching, research, and community service activities. The assessment of the best lecturers is based on several criteria, such as performance in teaching and learning activities, research productivity, and contributions to community service.\u003c/p\u003e\u003cp\u003eCurrently, the selection of the best lecturers at Wiraraja University is still carried out conventionally, such as based on subjective assessments or manual recapitulation of student scores. This process faces several challenges, such as the lack of measurable standards, potential bias in assessment, and difficulties in managing complex data. Therefore, a Decision Support System (DSS) is needed to assist in the decision-making process in a more objective, accurate, and efficient manner.\u003c/p\u003e\u003cp\u003eThe Analytical Hierarchy Process (AHP) method is one of the multi-criteria decision-making methods that can be used to evaluate lecturers based on various predetermined aspects. AHP works by comparing criteria in pairs (pairwise comparison) to determine the priority weights of each factor. By applying this method, the system can assist the university in selecting the best lecturers more fairly and in a data-driven manner.\u003c/p\u003e"},{"header":"II. RESEARCH METHOD","content":"\u003cp\u003eA. \u003cem\u003eResearch Design\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe stages of the research conducted are illustrated in the figure below:\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the figure above, the research begins with problem identification through interviews and observations at Wiraraja University to identify the challenges in the process of determining the best lecturers, which is still conducted manually. This is followed by a literature review to understand relevant theories and decision-making methods, as well as data collection such as lecturer data, assessment criteria, and related regulations. Next, system analysis and design are carried out by creating use cases, flowcharts, DFDs, and prototypes to illustrate the system to be developed. After that, the system is tested using the AHP (Analytic Hierarchy Process) method to calculate weights and rankings based on objectively defined criteria. The designed system then undergoes a trial phase to ensure its functionality and accuracy, followed by evaluation based on test results and user feedback to identify and improve shortcomings. Finally, the tested and evaluated system proceeds to the implementation stage so that it can be used operationally to support decision-making in determining the best lecturers.\u003c/p\u003e\u003cp\u003eB. \u003cem\u003eReseach Instrument\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe research instruments used in this study consist of two types, namely hardware and software. The hardware used is a Lenovo ThinkPad T430 laptop with an Intel Dual Core i5 processor up to 3.3 GHz and 4 GB of RAM, which functions to support the design, testing, and implementation of the system. Meanwhile, the software used includes Microsoft Word for report writing, Canva for designing the application prototype interface, XAMPP as a local server for testing the web-based system, and Visual Studio Code as the main code editor to efficiently support the system development process.\u003c/p\u003e\u003cp\u003eC. \u003cem\u003eData Collections Procedures\u003c/em\u003e\u003c/p\u003e\u003cp\u003eIn this study, the data collection procedure was carried out directly from the relevant parties at Wiraraja University, particularly within the General Administration Bureau (BAU), to understand the procedures and systems used in selecting the best lecturers. Through this process, the researcher also obtained data on the lecturers participating in the selection as well as the assessment criteria used as the basis for evaluating the best lecturers.\u003c/p\u003e\u003cp\u003eD. \u003cem\u003eReseach Flow Diagram\u003c/em\u003e\u003c/p\u003e\u003cp\u003eSystem design encompasses all information about the process of designing a system. The purpose of system design is to create a model or initial framework of the system to be developed. In this system design, the concept and workflow of the system to be built will be explained. In this study, the researcher will present the use case, flowchart, and Data Flow Diagram (DFD) of the Decision Support System for Determining the Best Lecturer at Wiraraja University using the Analytical Hierarchy Process (AHP) method.\u003c/p\u003e"},{"header":"III. RESULTS AND DISCUSSION","content":"\u003cp\u003eA. \u003cem\u003eSystem Development Results\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Decision Support System (DSS) for determining the best lecturer at Wiraraja University has been successfully developed and is ready for implementation. This DSS provides an objective and efficient platform that significantly enhances the transparency, accuracy, and speed of the evaluation process, replacing the previous manual methods and subjective assessments with measurable criteria for lecturer performance.\u003c/p\u003e\n\u003cp\u003eThe Dashboard page of the DSS for Determining the Best Lecturer at Wiraraja University functions as an information and navigation center, presenting an overview of the AHP-based system that supports objective and transparent evaluation through features such as Alternative Data, Assessment Criteria, Evaluation, and Result Reports. It also explains the assessment flow, from data input to the determination of the best lecturer based on the highest score.\u003c/p\u003e\n\u003cp\u003eThis page is an essential part of the AHP process, allowing users to systematically compare the importance level of each lecturer assessment criterion so that the system can produce objective and consistent decisions.\u003c/p\u003e\n\u003cp\u003eThis page displays the report of the best lecturer evaluation results based on the AHP method, where users can select the evaluation year (e.g., 2025) to view the total final score of each lecturer according to the values of the four criteria and AHP weights, with the results presented in a table format.\u003c/p\u003e\n\u003cp\u003eB. \u003cem\u003eSystem Test Results\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe testing of the DSS for Determining the Best Lecturer at Wiraraja University was carried out to ensure that the system operates according to its objectives, namely producing lecturer rankings that are objective, transparent, and measurable. This system applies the AHP method to systematically compare criteria and alternatives. The assessment is based on four main criteria: Education and Teaching, Research, Community Service, and Supporting Activities. The process includes constructing the comparison matrix, normalization, priority weight calculation, and consistency testing (CR). If the CR result is below 0.1, the calculation is considered valid. The final score is obtained from the multiplication of lecturers\u0026rsquo; performance values with the criteria weights, which are then summed to determine the total score. The system then automatically generates lecturer rankings, serving as the basis for determining the best lecturer by the university in a structured and periodic manner.\u003c/p\u003e\n\u003cp\u003e1. Determination of Criteria\u003c/p\u003e\n\u003cp\u003eThe determination of criteria in this system refers to the regulations already established at Wiraraja University. Each criterion used has been assigned a specific weight. The criteria are as follows:\u003c/p\u003e\n\u003cp\u003eTable 1. Criteria Table\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eKode\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eKriteria\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBobot\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBidang Pendidikan \u0026amp; Pengajaran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBidang Penelitian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBidang Pengabdian Kepada Masyarakat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKegiatan Penunjang\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e2. The stages of the Analytical Hierarchy Process (AHP)\u003c/p\u003e\n\u003cp\u003eA Decision Support System (DSS) is a tool that assists in making systematic and objective decisions by considering various alternatives and criteria. One commonly used method is the Analytic Hierarchy Process (AHP), which structures the problem in the form of a hierarchy and uses pairwise comparisons to determine the weight of each criterion and alternative. The AHP process includes defining the goal, comparing criteria and alternatives, calculating priority weights, and conducting a consistency test to ensure the reliability of the decision results.\u003c/p\u003e\n\u003cp\u003ea. Comparison Matrix Between Criteria\u003c/p\u003e\n\u003cp\u003eTable 2 is the pairwise comparison matrix of criteria used in the Analytical Hierarchy Process (AHP). This matrix is utilized to compare the relative importance of each criterion in the decision-making system, in this case, the selection of the best lecturer.\u003c/p\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison Matrix Between Criteria\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eKriteria\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK4\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eK1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eK2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eK3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eK4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Bobot Kolom\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eb. Normalization Calculation\u003c/p\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e presents the results of the normalization process of the criteria comparison matrix in the Analytical Hierarchy Process (AHP). The purpose of this process is to ensure that each value in the column is proportional and can be used to determine the priority weight of each criterion. This normalization is carried out by dividing each element in the column by the total sum of that column, which was previously calculated in the initial comparison matrix.\u003c/p\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCriteria Matrix Normalization \u0026amp; Weights\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eKriteria\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK4\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003ec. Calculating the Preference Value (Final Score)\u003c/p\u003e\n\u003cp\u003eThe Table of Priority Weights and Consistency Measure (CM) represents the final result of the AHP process after the normalization of the criteria comparison matrix. Criterion K1 has the highest weight of 0.424, indicating the greatest level of importance, followed by K2 (0.252), as well as K3 and K4, each with a weight of 0.162. The Consistency Measure (CM) value is obtained by multiplying the priority weights with the sum of the columns in the initial comparison matrix, which is then used to calculate the Consistency Index (CI) of 0.0514. Compared to the Random Index (RI) of 0.90, the Consistency Ratio (CR) is 0.0571 or 5.71%. Since the CR value is less than 10%, the matrix is considered consistent, and the resulting weights can be used in decision-making.\u003c/p\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePreference Value (Final Score)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eKriteria\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBobot Prioritas\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConsistency Measure\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.315\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.126\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.088\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.088\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eCI (Consistency Index): 0.0514\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eRI (Ratio Index): 0.90\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eCR (Consistency Ratio): 0.0571\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003ed. Alternative Ranking\u003c/p\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e is the alternative ranking table that presents the final assessment results of the two candidates (alternatives) based on the four main criteria, including their total scores and respective rankings.\u003c/p\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAlternative Ranking\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAlter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK4\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTot\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRanking\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWarieza\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.4663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.0571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.0846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23.8981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e99.7061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003erieza\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.2663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.0571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.0846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.8981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90.3061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"IV. CONCLUSION","content":"\u003cp\u003eBased on the study on the implementation of a Decision Support System (DSS) using the Analytical Hierarchy Process (AHP) method in determining the best lecturer at Universitas Wiraraja, it can be concluded that the AHP method provides an effective and objective solution in the decision-making process. AHP assists in systematically evaluating lecturers\u0026rsquo; performance based on several main criteria determined by the university. Through the pairwise comparison method, AHP generates priority weights that reflect the relative importance of each criterion. The final results of this calculation provide a ranking of lecturers based on their total performance scores, thereby enabling a fair and measurable selection of the best lecturer.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDewa, W. A., \u0026amp; Rahmawati, L. S. (2018). Analisis dan Desain Sistem Pendukung Keputusan Penentuan Dosen Pembimbing Tugas Akhir Menggunakan Metode AHP. \u003cem\u003eJurnalTechnopreneur(JTech)\u003c/em\u003e,\u003cem\u003e6\u003c/em\u003e(2),81.\u003c/li\u003e\n\u003cli\u003eHerman, H., Riadi, I., Kurniawan, Y., \u0026amp; Rafiq, I. A. (2023). Analisis Keamanan Website Menggunakan Information System Security Asessment Framework(ISSAF). Jurnal Teknologi Informatika Dan Komputer, 9(1), 126\u0026ndash;136. \u003c/li\u003e\n\u003cli\u003eMagdalena Sundari, Asnawati Asnawati, \u0026amp; Indra Kanedi. (2024). Sistem Pendukung Keputusan Penilaian Dosen Terbaik Menggunakan Metode Analytical Hierarchy Process (AHP) Studi Kasus Fakultas Keguruan dan Ilmu Pendidikan Universitas Dehasen Bengkulu. \u003cem\u003eJurnal Ilmiah Teknik Mesin, Elektro Dan Komputer\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(1), 28\u0026ndash;43.\u003c/li\u003e\n\u003cli\u003eMie, Y., \u0026amp; Wibowo, C. (2024). \u003cem\u003eSistem Pendukung Keputusan Metode Analytical Hierarchy Process untuk Penentuan Dosen dengan Kinerja Terbaik pada Fakultas Komputer di Universitas Universal\u003c/em\u003e. \u003cem\u003e4\u003c/em\u003e(2), 44\u0026ndash;50.\u003c/li\u003e\n\u003cli\u003ePermatasari, A., \u0026amp; Suhendi, S. (2020). Rancang Bangun Sistem Informasi Pengelolaan Talent Film berbasis Aplikasi Web. \u003cem\u003eJurnal Informatika Terpadu\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(1), 29\u0026ndash;37.\u003c/li\u003e\n\u003cli\u003eSesfao, Y. F., Nababan, D., \u0026amp; Seran, K. J. T. (2024). \u003cem\u003ePenerapan Metode Analitycal Hierarchy Process dalam Rancang Bangun Sistem Pendukung Keputusan Penentuan Dosen Terbaik\u003c/em\u003e. \u003cem\u003e7\u003c/em\u003e(5), 1300\u0026ndash;1308.\u003c/li\u003e\n\u003cli\u003eTri, S., Nova, E., \u0026amp; Muchayan, A. (2024). \u003cem\u003eSISTEM INFORMASI MANAJEMEN SURAT MENGGUNAKAN QR CODE DI LINGKUNGAN STAFF PERSONEL KODAM V / BRAWIJAYA Sembodo Tri Eko Nova Riawan , Achmad Muchayan Program Studi Sistem informasi , Fakultas Teknik dan Ilmu Komputer , Universitas Narotama Kata Kunci : Koda\u003c/em\u003e. \u003cem\u003e9\u003c/em\u003e(1).\u003c/li\u003e\n\u003cli\u003eYasa, I. W. S., Werthi, K. T., \u0026amp; Satwika, I. P. (2021). Sistem Pendukung Keputusan Penentuan Dosen Terbaik Menggunakan Metode Analytical Hierarchy Process (AHP) Pada STMIK Primakara. \u003cem\u003eKumpulan Artikel Mahasiswa Pendidikan Teknik Informatika (KARMAPATI)\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(3), 289. https://doi.org/10.23887/karmapati.v10i3.36824\u003c/li\u003e\n\u003cli\u003eNendya, Matahari Bhakti, Budi Susanto, Gabriel Indra Widi Tamtama, and Timotius Johan Wijaya. 2023. \u0026ldquo;Desain Level Berbasis Storyboard Pada Perancangan Game Edukasi Augmented Reality Tap The Trash.\u0026rdquo; Fountain of Informatics Journal 8 (1): 1\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eSyarif Muhammad., Nugraha Wahyu, 2020. \u0026ldquo;Pemodelan Diagram Uml Sistem Pembayarantunaipada Transaksie-Commerce\u0026rdquo;. Jurnal Pontianak Universitas Bina Sarana. IV,1-7\u003c/li\u003e\n\u003cli\u003eTia Arianti, et al., 2022. \u0026ldquo;Perancangan Sistem Informasi Perpustakaan\u0026rdquo;. Jurnal Ilmiah Komputer Terapan dan Informasi Pontianak. 1(1),19-25\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eTaufik, M., \u0026amp; Armansyah, A. (2021). Eksistensi Pelaku Usaha Sektor Informal Offline dan Online di Tengah. Publikauma: Jurnal Administrasi Publik Universitas Medan Area, 9(1), 57-66.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eKuryanti, S. J., \u0026amp; Indriani, N. (2018). Pembuatan Website Sebagai Sarana Promosi Pariwisata. Publikasi Jurnal \u0026amp; Penelitian Teknik Informatika, 40-41\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Wiraraja University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Design Thinking, E-Achievement, Application Development","lastPublishedDoi":"10.21203/rs.3.rs-7390791/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7390791/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe selection of the best lecturer at Wiraraja University has been conducted manually, potentially causing inefficiency, subjectivity, and difficulties in managing complex data. This research aims to develop a web-based Decision Support System (DSS) using the Analytical Hierarchy Process (AHP) method to enhance objectivity, transparency, and assessment accuracy. The system employs four evaluation criteria: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Education \u0026amp; Teaching, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Research, (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Community Service, and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) Supporting Activities. The AHP method calculates criteria and alternative priority weights through pairwise comparisons, followed by a consistency ratio (CR) calculation to ensure judgment consistency. System implementation using PHP, HTML, and MySQL demonstrates improved selection efficiency, reduced recording errors, and data-based ranking of the best lecturers. User testing evaluation confirms optimal system functionality with a consistency rate (CR\u0026thinsp;\u0026lt;\u0026thinsp;0.1). This system is expected to support strategic university decision- making more fairly and measurably.\u003c/p\u003e","manuscriptTitle":"Decision Support System for Determining the Best Lecturer at Wiraraja University Using the AHP (Analytical Hierarchy Process) Method","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 05:37:55","doi":"10.21203/rs.3.rs-7390791/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b5505058-d60f-49db-971e-405322fa964a","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53339835,"name":"Theoretical Computer Science"},{"id":53339836,"name":"Computer Architecture and Engineering"}],"tags":[],"updatedAt":"2025-08-19T05:37:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-19 05:37:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7390791","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7390791","identity":"rs-7390791","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}