Implementation Of the Mamdani Fuzzy Method to Evaluate the Performance of Lecturers in The Research Field
Downloads
Today, information technology, especially soft computing technology, has grown very rapidly. One of the soft computing technologies that has been widely developed is fuzzy logic, because it can be used to measure various phenomena that are ambiguous, disguised or fuzzy. One of the research topics that uses the application of fuzzy logic is the assessment system in the field of research. Research by Lecturers at the University of Graha Nusantara Padangsidimpuan in Simlitabmas Data Still in the Guidance Category to upgrade to the Middle Category UGN Padangsidimpuan lecturers are challenged to be able to develop, devote, and apply the knowledge needed in research. For that we need an application that can be used to calculate and record the performance of Lecturers on the resulting Research. The purpose of this study is to apply fuzzy logic with the Mamdani method in assessing the research performance of lecturers at the University of Graha Nusantara Padangsidimpuan. This research uses Mamdani Fuzzy Logic. Fuzzy Mamdani method is a way to map an input space into an output space. This method is a mathematical framework used to represent uncertainty, ambiguity, imprecision, lack of information, and partial truth. The stages of research using the Mamdani method are Creating Input Variables taken from Sinta-accredited Articles, Simlitabmas Grant Articles and Articles in International and National Journals. Finding the Max-Min Value of Each Variable. Creating a fuzzy set using the Mamdani method. Creating Assertions with Defuzzification using Matlab.
Abbasipayam, S., & Makrova, N. V. (2022). Fuzzy logic and intelligent control of engineering systems of buildings. Vestnik of Astrakhan State Technical University. Series: Management, Computer Science and Informatics. https://doi.org/10.24143/2073-5529-2022-1-22-32
Acosta-Prado, J. C., Lazo, J. G., & Tafur-Mendoza, A. A. (2021). Application of fuzzy logic in the relationship between information and communication technologies and economic performance. Journal of Intelligent and Fuzzy Systems. https://doi.org/10.3233/JIFS-189180
Ain, S. Q., Saifizi, M., Othman, S. M., Aziz, A. A., Mustafa, W. A., & Khairunizam, W. (2022). Temperature Control Using Fuzzy Controller for Variable Speed Vapor Compression Refrigerator System. Proceedings of International Conference on Artificial Life and Robotics. https://doi.org/10.5954/icarob.2022.os32-6
Alwendi, A. (2021). Optimalisasi Internet of Things untuk Meningkatkan Produksi pada Sektor Usaha Kecil dan Menengah di Masa Pandemi Covid-19. Jurnal Informatika Dan Rekayasa Perangkat Lunak. https://doi.org/10.36499/jinrpl.v3i1.3963
Alwendi, A., & Masriadi, M. (2021). APLIKASI PENGENALAN WAJAH MANUSIA PADA CITRA MENGGUNAKAN METODE FISHERFACE. Jurnal Digit. https://doi.org/10.51920/jd.v11i1.174
Anisah, S., Yulianto, T., & Faisol, F. (2021). Perbandingan Fuzzy Sugeno dan Fuzzy Mamdani Pada Analisis Minat Masyarakat Terhadap Produk Air Minum Dalam Kemasan Lokal dan Nasional di Madura. Zeta - Math Journal. https://doi.org/10.31102/zeta.2021.6.1.29-37
Aslam, N. (2020). Sustainable processing: Examples in process intensification & commercial catalysis. AIChE Annual Meeting, Conference Proceedings.
Baliuta, S., Kopylova, L., Kuievda, I., Kuevda, V., & Kovalchuk, O. (2020). Fuzzy logic energy management system of food manufacturing processes. Ukrainian Food Journal. https://doi.org/10.24263/2304-974x-2020-9-1-19
Budi Indra Gunawan, & Unan Yusmaniar Oktiawati. (2020). Server Room Temperature and Monitoring System Using Fuzzy Based on RobotDyn Microcontroller. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi). https://doi.org/10.29207/resti.v4i1.1207
Devaraj, R., Nasr, E. A., Esakki, B., Kasi, A., & Mohamed, H. (2020). Prediction and analysis of multi-response characteristics on plasma arc cutting of monel 400TM alloy using mamdani-fuzzy logic system and sensitivity analysis. Materials. https://doi.org/10.3390/MA13163558
Hardianto, H., & Nurhasanah, N. (2020). Identifikasi Penyakit pada Sel Darah Menggunakan Logika Fuzzy Mamdani. PRISMA FISIKA. https://doi.org/10.26418/pf.v7i3.38106
Izvozchikova, V. V, Tlegenova, T. E., & Markovin, V. V. (2022). Development of an intelligent learning system based on fuzzy logic. IOP Conference Series: Materials Science and Engineering. https://doi.org/10.1088/1757-899x/1227/1/012007
Keviczky, L., Bars, R., Hetthéssy, J., & Bányász, C. (2019). Introduction to MATLAB. In Advanced Textbooks in Control and Signal Processing. https://doi.org/10.1007/978-981-10-8321-1_1
Kimura, A., Kashino, K., Kurozumi, T., & Murase, H. (2008). A quick search method for audio signals based on a piecewise linear representation of feature trajectories. IEEE Transactions on Audio, Speech and Language Processing. https://doi.org/10.1109/TASL.2007.912362
Li, P. cheng, Chen, G. hua, Dai, L. cao, & Li, Z. (2010). Fuzzy logic-based approach for identifying the risk importance of human error. Safety Science. https://doi.org/10.1016/j.ssci.2010.03.012
Mittal, K., Jain, A., Vaisla, K. S., Castillo, O., & Kacprzyk, J. (2020). A comprehensive review on type 2 fuzzy logic applications: Past, present and future. Engineering Applications of Artificial Intelligence. https://doi.org/10.1016/j.engappai.2020.103916
Mudia, H. (2020). Comparative Study of Mamdani-type and Sugeno-type Fuzzy Inference Systems for Coupled Water Tank. Indonesian Journal of Artificial Intelligence and Data Mining. https://doi.org/10.24014/ijaidm.v3i1.9309
Ningrum, R. F., Siregar, R. R. A., & Rusjdi, D. (2021). Fuzzy Mamdani logic inference model in the loading of distribution substation transformer SCADA system. IAES International Journal of Artificial Intelligence. https://doi.org/10.11591/ijai.v10.i2.pp298-305
Rani Roopha Devi, K. G., & Mahendra Chozhan, R. (2020). Prediction of Sudden Cardiac Arrest Due to Diabetes Mellitus Using Fuzzy Based Classification Approach. In Lecture Notes on Data Engineering and Communications Technologies. https://doi.org/10.1007/978-3-030-43192-1_46
Rodríguez, A., Carricajo, I., Manteiga, M., Dafonte, C., & Arcay, B. (2008). STARMIND: Automated classification of astronomical data based on an hybrid strategy. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). https://doi.org/10.1007/978-3-540-87656-4_25
Rustum, R., Kurichiyanil, A. M. J., Forrest, S., Sommariva, C., Adeloye, A. J., Zounemat-Kermani, M., & Scholz, M. (2020). Sustainability ranking of desalination plants using mamdani fuzzy logic inference systems. Sustainability (Switzerland). https://doi.org/10.3390/su12020631
Sadi, S. (2020). DC Motor Speed Control Using Mamdani Fuzzy Logic Based on Microcontroller. Jurnal Teknik. https://doi.org/10.31000/jt.v9i2.3676
Sofhian, Sujaini, H., & Pratiwi, H. S. (2016). Dosen Terbaik Menggunakan Metode Promethee ( Studi Kasus?: Teknik Informatika Universitas Tanjungpura ). Jurnal Sistem Dan Teknologi Informasi (JUSTIN).
Suo, M., Li, S., Chen, Y., Zhang, Z., Zhu, B., & An, R. (2018). Effectiveness evaluation of fighter using fuzzy Bayes risk weighting method. The Aeronautical Journal, 122(1254), 1275-1300.
Tahri, M., Maanan, M., Tahri, H., Kašpar, J., Chrismiari Purwestri, R., Mohammadi, Z., & Marušák, R. (2022). New Fuzzy-AHP MATLAB based graphical user interface (GUI) for a broad range of users: Sample applications in the environmental field. Computers and Geosciences. https://doi.org/10.1016/j.cageo.2021.104951
Tariq, M. I., Tayyaba, S., Ali Mian, N., Sarfraz, M. S., Hussain, A., Imran, M., Pricop, E., Cangea, O., & Paraschiv, N. (2020). An analysis of the application of fuzzy logic in cloud computing. Journal of Intelligent and Fuzzy Systems. https://doi.org/10.3233/JIFS-179680
van Krieken, E., Acar, E., & van Harmelen, F. (2022). Analyzing Differentiable Fuzzy Logic Operators. Artificial Intelligence. https://doi.org/10.1016/j.artint.2021.103602
Wawan, W., Zuniati, M., & Setiawan, A. (2021). Optimization of National Rice Production with Fuzzy Logic using Mamdani Method. Journal of Multidisciplinary Applied Natural Science. https://doi.org/10.47352/jmans.v1i1.3
Wu, H., & Xu, Z. S. (2021). Fuzzy Logic in Decision Support: Methods, Applications and Future Trends. International Journal of Computers, Communications and Control. https://doi.org/10.15837/ijccc.2021.1.4044
Yetilmezsoy, K., Karakaya, K., Bahramian, M., Abdul-Wahab, S. A., & Goncalo?lu, B. ?. (2021). Black-, gray-, and white-box modeling of biogas production rate from a real-scale anaerobic sludge digestion system in a biological and advanced biological treatment plant. Neural Computing and Applications. https://doi.org/10.1007/s00521-020-05562-7
Yang, F., & Paindavoine, M. (2013). Implementation of an RBF neural network on embedded systems: real-time face tracking and identity verification. IEEE Transactions on Neural Networks, 14(5), 1162-1175.
Copyright (c) 2023 Alwendi Alwendi, Khairunnisa Samosir, Mingliang Suo, Yang Fan

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


















