Analysis of Community Service Satisfaction Levels at the Pematangsiantar Environmental Service Using the Fuzzy Mamdani Method

Authors

  • Joel Tindaon STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Muhammad Ridwan Lubis STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Ika Okta Kirana STIKOM Tunas Bangsa, Pematangsiantar, Indonesia

DOI:

https://doi.org/10.55123/jomlai.v1i2.953

Keywords:

Satisfaction Level, Society Service, Environment, Pematangsiantar, Fuzzy Mamdani

Abstract

Currently, there are still many weaknesses and shortcomings in public services carried out by government officials, so that they have not been able to meet the quality expected by the community. This is indicated by the lack of good public services delivered through the mass media. Given that the main function of the government is to serve the community, the government must strive to improve the quality of service for the better. In this study, an analysis of the level of community service satisfaction at the Pematangsiantar environmental service will be carried out using the Fuzzy Mamdani method. Data was collected by means of observation, literature study and interviews with the Pematangsiantar Environmental Service Office. The data used consists of several variables: Number of Respondents (Variable 1), Total Response Results (Variable 2) and Output Results (Variable 3). Based on 45 respondents with a total of 43 responses, the satisfaction output obtained is 560. Based on 50 respondents, 49 responses are obtained, so the service satisfaction output is 578. The conclusion is based on the calculation of the Mamdani Fuzzy model in 2021, the community is satisfied for the services provided by the Pematangsiantar environmental service based on the range of values ​​that have been generated.

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Published

2022-09-26

How to Cite

Tindaon, J., Lubis, M. R., & Kirana, I. O. (2022). Analysis of Community Service Satisfaction Levels at the Pematangsiantar Environmental Service Using the Fuzzy Mamdani Method. JOMLAI: Journal of Machine Learning and Artificial Intelligence, 1(2), 173–184. https://doi.org/10.55123/jomlai.v1i2.953

Issue

Vol. 1 No. 2 (2022): June

Section

Articles

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Copyright (c) 2022 Joel Tindaon, Muhammad Ridwan Lubis, Ika Okta Kirana

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