Majalah Bisnis & IPTEK
Vol. 16 No. 1 (2023): Majalah Bisnis & IPTEK

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

Fadli Emsa Zamani (STMIK Mardira Indonesia, Bandung)
Toni Kusnandar (STMIK Mardira Indonesia, Bandung)
Fikri Emsa Silmi (STMIK Mardira Indonesia, Bandung)
Rizal Rachman (Universitas Adhirajasa Reswara Sanjaya, Bandung)



Article Info

Publish Date
15 Apr 2023

Abstract

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. The initial step in examining the public satisfaction index through the utilization of Artificial Intelligence involves the application of the K-Means Cluster algorithm, which will generate multiple clusters based on their shared characteristics. The values utilized by each group consist of the integers 1, 2, 3, and 4. Subsequently, an assessment is conducted on each formed group in order to ascertain the most favorable outcomes. The study yielded clusters that were deemed optimal, with smaller values indicating areas in which the services could be enhanced. The present study aims to investigate the impact of Artificial Intelligence (AI) on public service quality, as measured by the Community Satisfaction Index (CSI). Specifically, we employ the K-Means clustering algorithm to analyze the data collected from a representative sample of community members. By utilizing AI techniques, we seek to gain insights into.

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Journal Info

Abbrev

bistek

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Library & Information Science Social Sciences

Description

The focus areas of the journal include, but are not limited to: Related to the fields of Accounting and Management as well as the Context of Business and Science and Technology in Indonesia, also intended as a medium of communication between academics who are interested in business and science and ...