Model Fuzzy Mamdani Untuk Penilaian Tingkat Kepuasan Pelayanan Pengaduan Masyarakat

Abstract

AbstrakKualitas pelayanan adalah salah satu keunggulan kompetitif, karena pelayanan yang baik adalah salah satu faktor dasar yang mampu mempengaruhi tingkat kenyamanan penerima layanan. Pelayanan publik oleh aparatur pemerintah dewasa ini masih banyak dijumpai kelemahan, sehingga belum dapat memenuhi kualitas yang diharapkan masyarakat. Penelitian ini ditujukan untuk melihat seberapa besar kepuasan pelayanan, dan pengaruh tingkat pelayanan terhadap tingkat kepuasan berdasarkan Logika Fuzzy Inference System Model Mamdani. Ada empat variabel input yang digunakan yaitu kejelasan informasi, kejelasan persyaratan, kemampuan petugas dan ketersediaan sarana dan prasarana untuk menghasilkan output kepuasan pelayanan. Berdasarkan tahapan-tahapan menggunakan Logika Fuzzy Inference System Model Mamdani mulai dari pembentukan himpunan fuzzy, aplikasi fungsi impilkasi, komposisi aturan sampai proses penegasan (defuzzyfikasi), dapat dibuktikan adanya korelasi antara variabel-variabel input sehingga dapat menentukan output hasil kepuasan pelayanan. Hasil penelitian ini diharapkan dapat digunakan oleh pihak instansi, sebagai pendukung sistem keputusan terhadap hasil penilaian yang diberikan oleh masyarakat untuk pelayanan yang dirasakan. Pengembangan penelitian ini kedepan nya akan diuji coba kembali dengan menambahkan lebih banyak variabel dan akan dibuat sebuah interface untuk memudahkan pemprosesan hasil penilaian kualitas pelayanan pengaduan masyarakat. Kata Kunci: Pelayanan, Fuzzy Mamdani, Logika Fuzzy.AbstractService quality is one of the competitive advantages, because good service is one of the basic factors that can affect the comfort level of service recipients. Public services by the government apparatus today are still often found to be weak, so that they cannot meet the quality expected by the community. This study is intended to see how much service satisfaction is, and the effect of service levels on satisfaction levels based on Mamdani Model Fuzzy Inference System Logic. There are four input variables used namely clarity of information, clarity of requirements, ability of officers and availability of facilities and infrastructure to produce service satisfaction output. Based on the stages using Mamdani Model Fuzzy Inference System Logic starting from the formation of fuzzy sets, application of the implementation function, composition of the rules until the confirmation process (defuzzyfication), it can be proved the correlation between input variables so that it can determine the output of service satisfaction. The results of this study are expected to be used by the agency, as a support system for the decision on the results of the assessment given by the community for perceived services. The future development of this research will be re-tested by adding more variables and an interface will be created to facilitate the processing of the results of the quality assessment of public complaints services. Keywords: Service, Fuzzy Mamdani, Fuzzy Logic.

Implementasi Metode Fuzzy Mamdani Untuk Menentukan Tingkat Jumlah Pernikahan Dini Tahun 2022 Kabupaten Barru

“…Fuzzy Inference System Model Mamdani sering juga dikenal dengan nama metode MAX-MIN. Metode ini diperkenalkan oleh Ebrahim Mamdani pada tahun 1975 [10]. Fuzzy Mamdani salah satu teknik yang digunakan dalam sistem kecerdasan buatan (Artificial Intelligence) untuk mengatasi ketidakpastian dan kompleksitas dalam pengambilan keputusan.…”

Fuzzy Mamdani Model for Assessing the Level of Service Satisfaction for Requirements of Social Welfare Services at the "Prof. Dr. Soeharso" Integrated Center in Surakarta

“…Good service quality in an agency is a basic factor that can influence the level of comfort. In controlling service quality in the future, service quality is needed to prevent poor service quality from occurring from the start [1].…”

“…The aim of this research is to find out the weaknesses or shortcomings of each element in providing services, as well as see how much service satisfaction there is and the influence of service levels on satisfaction levels based on the Fuzzy Inference System Model Mamdani Logic. [1] with the title Fuzzy Mamdani Model for Assessing the Level of Satisfaction with Public Complaint Services uses system design starting from the formation of Fuzzy sets, application of implication functions (formation of Fuzzy rules), composition of Fuzzy rules, and confirmation (defuzzification) [2]. The research results show service satisfaction if the value of clarity of information is 80, clarity of requirements is 78, ability of officers is 80 and availability of infrastructure is 81.…”

Prediction of flood depth detection system from rainfall with normal, alert and hazard levels based on fuzzy logic

“…Fuzzy logic is a constituent of soft computing (Nilawati & Nusa Mandiri Jakarta, 2018). Fuzzy logic is a component of artificial intelligence utilized to address uncertainties in problem causality (Jufriadi et al, 2020).…”