The Classification of Public Complaints through Smart City Application

Abstract This research aimed to classify the data of public complaints of people in Tangerang City by applying a pattern of the complaint data from the LAKSA application that has been categorized. In finding the pattern, it used one of the data mining methods, namely classification. The classification algorithm search process was performed by comparing the accuracy of several selected algorithms. The algorithms were k-nearest neighbor, random forest, support vector machine, and AdaBoost. These algorithms were tested to achieve maximum potential. Thus, the results showed support vector machine with linear kernel is a classification algorithm with the highest accuracy that reached 89.2%