Grouping Public Complaints in the City of Tangerang Using K-Means Clustering Method

Author:

Madyatmadja Evaristus Didik1,Rahmah Astari Karina1,Putri Saphira Aretha1,Pralambang Yusdi Ari1,Wicaksana Gede Prama Adhi1,Raihan Muhammad D.1

Affiliation:

1. Information Systems Department, School of Information Systems, Bina Nusantara University, Jakarta, Indonesia

Abstract

The government's efforts in developing electronic-based government services by utilizing information technology are referred to as the concept of e-government. Tangerang City is one of the cities that applies e-government in an application called Tangerang LIVE. In the Tangerang LIVE application, a LAKSA feature is used as a place for complaints from the people of Tangerang. This research was conducted to classify complaint data and determine the priority of groups of complaints received from the LAKSA feature. The technique used to conduct this research is clustering using the unsupervised learning method and the k-means algorithm, which will classify and predict the class for each document. In addition, an analysis of the priority complaint data was carried out based on the group that was received the most. The analysis carried out is to find out the class predictions for each complaint received, and then labeling will be given so that the complaint belongs to a more specific group. The results of the predictions will be displayed in the browser using web services.

Publisher

IGI Global

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