Analysis of Public Service Satisfaction using Artificial Intelligence K-Means Cluster

Public service refers to the provision of goods, services, and support by the government to meet the community's desires and needs. In order to assess the efficacy of this service, a metric for gauging service quality, referred to as the Community Satisfaction Index, has been devised. This data offers insights into the level of satisfaction within the community regarding a particular service. This study utilizes the K-Means Cluster algorithm, a form of unsupervised machine learning, to categorize data based on similarities and dissimilarities into distinct clusters. The objective of this study is to gain insight and conduct an analysis of the level of satisfaction within the community regarding the information services offered by the Communication and Information Department of West Java Province. Furthermore, the objective of this study is to ascertain the categorization of the public satisfaction index by using the K-Means Cluster technique, employing an artificial intelligence methodology. This approach will enable the identification of the public satisfaction index as well as the identification of specific indicators that necessitate enhancement.