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
Abstract
Abstract-Service 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 three input variables used namely clarity of information, 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.
Full Text:
PDFReferences
M. Martin and L. Nilawati, "Fuzzy Mamdani Model for Assessing the Level of Satisfaction with Public Complaint Services," J. Inform., vol. 5, no. 2, pp. 237–247, 2018, doi: 10.31311/ji.v5i2.4170
Perwira, Y., & Lubis, R. K. (2021). Application Of Fuzzy Logic In The Measurement System Of Student Satisfaction Level Towards Lecturers Based On The Fuzzy Infrence Analysis Of The Mamdani, Sugeno And Tsukatomo Method System. INFOKUM, 10(1), 91-104.
Cárdenas-Cuervo, R. A., Serna-Uran, C. A., & Gomez-Marin, C. G. (2023, December). Analysis of Users’ Requirements for Public Waste Management Services Using Fuzzy Inference. In MENDEL (Vol. 29, No. 2, pp. 169-180)
Muqorobin, M., & Ma'ruf, M. H. (2022). Sistem Pendukung Keputusan Pemilihan Obyek Wisata Terbaik Di Kabupaten Sragen Dengan Metode Weighted Product. Jurnal Tekinkom (Teknik Informasi dan Komputer), 5(2), 364-376..
Mebawondu, J. O., Dahunsi, F. M., & Adewale, O. S. (2020). Hybrid intelligent model for real time assessment of voice quality of service. Scientific African, 9, e00491.
Hassan, R., Majeed, A. A., & Muqorobin, M. (2023). Fingerprint Data Security System Using Aes Algorithm on Radio Frequency Identification (RFID) Based Population System. International Journal of Informatics Technology (INJIT), 1(1), 14-20..
Pourjavad, E., & Shahin, A. (2018). Hybrid performance evaluation of sustainable service and manufacturing supply chain management: An integrated approach of fuzzy dematel and fuzzy inference system. Intelligent Systems in Accounting, Finance and Management, 25(3), 134-147..
Martínez, M. P., Cremasco, C. P., Gabriel Filho, L. R. A., Junior, S. S. B., Bednaski, A. V., Quevedo-Silva, F., ... & Padgett, R. C. M. L. (2020). Fuzzy inference system to study the behavior of the green consumer facing the perception of greenwashing. Journal of Cleaner Production, 242, 116064..
Altinsoy, U., Aktepe, A., & Ersoz, S. (2023). A model proposal for measuring service quality of eduaction with fuzzy rule-based approach and fuzzy ranking and an application. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-14.
Andrenacci, N., Genovese, A., & Ragona, R. (2017). Determination of the level of service and customer crowding for electric charging stations through fuzzy models and simulation techniques. Applied Energy, 208, 97-107.
A. Z. Ahmad, R. Hardianto, A. Armada, and K. Anggraini, "Analysis of the Level of Community Satisfaction with Public Services at the Tembilahan District Police," Zo. J. Sis. Inf., vol. 3, no. 2, pp. 143–156, 2022, doi: 10.31849/zn.v3i2.8502.
L. L. Van FC and L. Lisnawita, "Analysis of Customer Satisfaction with CV After-Sales Services. Family Using the Fuzzy-Logic Method," INOVTEK Polbeng - Seri Inform., vol. 2, no. 1, p. 64, 2017, doi: 10.35314/isi.v2i1.118.
A. R. Vinanda, S. A. Wicaksono, and F. Amalia, "Development of a Web-Based Professional Certification Institution Assessment Information System (Case Study: SMK Negeri 4 Malang)," J. Pememb. Technol. Inf. and Computer Science., vol. 3, no. 6, pp. 6220–6229, 2019.
A. . and Y. . L. Rindengan, Fuzzy Systems. 2019.
R. B. Ginting, "Function Analysis of Max-Min and Max-Prod Implications in Decision Making," Creat. Inf. Technol. J., vol. 1, no. 2, p. 128, 2015, doi: 10.24076/citec.2014v1i2.16.
Rahmawati, R., Mulyani, S., Handayani, S. R., Nurlaela, S., Noviani, R., Arifah, S., ... & Muqorobin, M. (2023). Pemanfaatan Bonggol Jagung Untuk Peningkatan Pendapatan Di Desa Ledokdawan Kecamatan Geyer Kabupaten Grobogan Jawatengah. Budimas: Jurnal Pengabdian Masyarakat, 5(2).
Muqorobin, M. (2023). The Decision Support System for Selecting the Best Teacher for Birull Walidaini Using the SAW Method. International Journal of Computer and Information System (IJCIS), 4(3), 105-112.
Muqorobin, M., Rais, N. A. R., & Efendi, T. F. (2021, December). APLIKASI E-VOTING PEMILIHAN KETUA BEM DI INSTITUT TEKNOLOGI BISNIS AAS INDONESIA BERBASIS WEB. In Prosiding Seminar Nasional & Call for Paper STIE AAS (Vol. 4, No. 1, pp. 309-320).
Muqorobin, M., & Fitriyadi, F. (2023). Sistem Informasi Pariwisata Di Singkawang Kalimantan Barat Berbasis Website Sebagai Media Promosi. JUTIE (Jurnal Teknologi Sistem Informasi dan Ekonomi), 1(1), 1-9..
Rais, N. A. R., & Muqorobin, M. (2021). Analysis Of Kasir Applications In Sales Management Information Systems at ASRI Store. International Journal of Computer and Information System (IJCIS), 2(2), 40-44.
Muqorobin, M., Utomo, P. B., Nafi’Uddin, M., & Kusrini, K. (2019). Implementasi Metode Certainty Factor pada Sistem Pakar Diagnosa Penyakit Ayam Berbasis Android. Creative Information Technology Journal, 5(3), 185-195.
Rokhmah, S., & Utomo, I. C. (2020). Binary Log Analysis on MySQL to Help Investigation Process Against Database Privillege Attacks. International Journal of Computer and Information System (IJCIS), 1(1), 11-15.
Prasetya, A., Muqorobin, M., & Fitriyadi, F. (2021). Operating System Development Based on Open Source Software in Online Learning Systems. International Journal of Computer and Information System (IJCIS), 2(2), 45-48.
Muqorobin, A., Dahono, P. A., & Purwadi, A. (2017, September). Optimum phase number for multiphase PWM inverters. In 2017 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) (pp. 1-6). IEEE.
Muqorobin, M., Utomo, P. B., Nafi’Uddin, M., & Kusrini, K. (2019). Implementasi Metode Certainty Factor pada Sistem Pakar Diagnosa Penyakit Ayam Berbasis Android. Creative Information Technology Journal, 5(3), 185-195.
Rijanto, E., Muqorobin, A., & Nugraha, A. S. (2011). Design of a yaw positioning control system for 100 kW horizontal axis wind turbines based on on/off control with dead band and hysteresis. Int J Appl Eng Res, 6(19), 2327-40.
DOI: https://doi.org/10.29040/ijcis.v5i1.152
Article Metrics
Abstract view : 69 timesPDF - 39 times
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 4.0 International License.
