Analysis of Student Satisfaction Levels with Study Program Management Services Using Sugeno's Fuzzy Inference Method
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Abstract
This research aims to analyze the level of student satisfaction with study program management services at the Faculty of Islamic Economics and Business (FEBI) IAIN Ponorogo using the Sugeno fuzzy inference method with the help of the Fuzzy Toolbox in the MATLAB application. The data used is primary data collected from 1036 respondents, namely active students from the Sharia Economics, Sharia Banking and Zakat and Waqf Management Study Programs. The evaluation includes five service factors: Tangible, Reliability, Responsiveness, Assurance, and Empathy, which are measured using a Likert scale. The analysis process begins with creating a fuzzy set for each variable, using the fuzzy implication function, compiling 19 fuzzy rules, and ending with defuzzification to obtain a concrete value for the level of satisfaction. The research results show that the Sugeno fuzzy method can effectively capture variations in student responses and provide accurate results regarding their level of satisfaction. This method makes it easier for the Faculty Quality Control Team team to evaluate and improve the quality of academic services, thereby making a significant contribution to continuous improvement in the management of study programs at FEBI IAIN Ponorogo.
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Bakır, M., & Atalık, Ö. (2021). Application of Fuzzy AHP and Fuzzy MARCOS Approach for the Evaluation of E-Service Quality in the Airline Industry. Decision Making: Applications in Management and Engineering, 4(1), 127–152. https://doi.org/10.31181/dmame2104127b
Borse, K., & Agnihotri, P. G. (2019). Prediction of Crop Yields Based on Fuzzy Rule-Based System (FRBS) Using the Takagi Sugeno-Kang Approach (pp. 438–447). https://doi.org/10.1007/978-3-030-00979-3_46
Budy Santoso, Zohrahayaty, & Azminuddin I. S. Azis. (2020). Machine Learning and Reasoning Fuzzy Logic Algoritma, Manual, Matlab, & Rapid Miner. Deepublish.
Kusumadewi, S. ., & Purnomo, H. (2010). Fuzzy Logic Application for Decision Support. Graha Ilmu.
Macioł, A., Macioł, P., & Mrzygłód, B. (2020). Prediction of forging dies wear with the modified Takagi–Sugeno fuzzy identification method. Materials and Manufacturing Processes, 35(6), 700–713. https://doi.org/10.1080/10426914.2020.1747627
Mughaffir Yunus, & Marlina Marlina. (2023). Analisis Tingkat Kepuasan Mahasiswa Umpar Terhadap Pelayanan Berbasis Internet Menggunakan Metode Fuzzy Tsukamoto. Jurnal Sintaks Logika (JSilog) Jurnal Penelitian Ilmiah Teknik Informatika, 3(3).
Prabowo, T., Machfud, I., & Lestari, D. (2022). Penerapan Fuzzy – Service Quality Terhadap Tingkat Kepuasan Pelayanan BPJS Ketenagakerjaan. Journal Automation Computer Information System, 2(1), 82–90. https://doi.org/10.47134/jacis.v2i1.38
Sihaloho, T. P., Nasution, M. K. M., & Situmorang, Z. (2020). Level of student satisfaction on lecturer performance with fuzzy inference system (FIS) tsukamoto method. IOP Conference Series: Materials Science and Engineering, 725(1), 012130. https://doi.org/10.1088/1757-899X/725/1/012130
Slamet Nur Huda. (2018). Sistem Penunjang Keputusan Pemilihan Rumah Kontrakan untuk Keluarga di Kota Malang Menggunakan Metode Fuzzy Sugeno. J-INTECH Journal of Information and Technology , 6(1).
Sugiyono. (n.d.). Metode penelitian pendidikan : (pendekatan kuantitatif, kualitatif dan R & D).
Sujarwata. (2018). Buku Ajar Sistem Fuzzy dan Aplikasinya. Deepublish.
Wicaksono, D. E. (2021). Analisis Tingkat Kepuasan Pelanggan terhadap Layanan di Rumah Makan Pacitan dengan Pendekatan Fuzzy Mamdani.
Yunan, A., & Ali, M. (2020). Study and Implementation of the Fuzzy Mamdani and Sugeno Methods in Decision Making on Selection of Outstanding Students at the South Aceh Polytechnic. Jurnal Inotera, 5(2), 152–164. https://doi.org/10.31572/inotera.Vol5.Iss2.2020.ID127