Application of The Fuzzy Grid Partition-Based Mamdani Method to Decision Support System for Determining Salary Increase Eligibility

Main Article Content

Murni Marbun
Sandhuri -
Aishwarya -

Abstract

Fuzzy grid partition has been used to produce appropriate and optimal output. The output of several fuzzy inference methods such as the Tsukamoto method and the Mamdani method have been improved by applying grid partitions. This study aims to apply the fuzzy grid partition-based mamdani method to determine the feasibility of increasing employee salaries. The stages of the method are carried out starting with determining the number of partitions, forming fuzzy sets, carrying out the process of implicit rules, carrying out rule composition by selecting the maximum value of feasible and infeasible decisions, and finally carrying out the defuzzification process to obtain the calculation of the crips value. Attributes or features for selecting the eligibility for a salary increase are employee status, class status, years of service and benefits received. The results of the research get a decision for each employee whether it is appropriate to receive a salary increase or not. From one sample data tested on sample X7, the result of defuzzification (Z) is 5. Based on the table of feasible and inappropriate decisions, the value of Z = 5 is in a feasible decision

Article Details

How to Cite
[1]
M. Marbun, S. -, and A. -, “Application of The Fuzzy Grid Partition-Based Mamdani Method to Decision Support System for Determining Salary Increase Eligibility”, JUSIKOM PRIMA, vol. 6, no. 2, pp. 17-22, Feb. 2023.
Section
Articles

References

E. Junianto and A. F. Rozi, “Sistem Pendukung Keputusan Menentukan Kelayakan Kenaikan Gaji Karyawan Menggunakan Metode Topsis The Decision Support System to Determine the Eligibility of Employee Salary Increase Using the Topsis Method,” J. Inf. Syst. Artif. Intell., vol. 1 No 1, no. 84, p. 55283, 2020.

M. Marbun and B. Sinaga, “Sistem Pendukung Keputusan Penilaian Hasil Belajar Mahasiswa Dengan Metode Topsis Di STMIK Pelita Nusantara Medan,” J. Mantik Penusa, vol. 1, no. 2, pp. 9–15, 2017.

P. Meilina, N. Rosanti, and N. Astryani, “Sistem Pendukung Keputusan Penentuan Jumlah Produksi Barang Dengan Metode Fuzzy Tsukamoto Berbasis Android,” in Seminar Nasional Sains dan Teknologi, 2017, no. November, pp. 1–2.

B. Firmansyah and A. M. Wihandar, “Sistem Pendukung Keputusan Monitoring & Evaluasi Kinerja Dosen Program Studi Informatika fakultas Ilmu Komputer IBI Kosgoro 1957 Menggunakan Metode …,” J. Nas. Inform., vol. 1, no. 2, pp. 127–142, 2020.

D. D. Handayani, “Implementasi Fuzzy Logic Mamdani Untuk Menentukan Kelayakan Implementasi Fuzzy Logic Mamdani Untuk Menentukan,” no. June, 2019.

T. Y. Akhirina and M. Sonny, “Fuzzy Inference System (FIS) dengan Metode Tsukamoto dan Mamdani dalam Menentukan Kelayakan Kenaikan Gaji Karyawan,” J. Komtika, vol. 1, no. 2, pp. 7–14, 2017.

M. Marbun, W. Ramdhan, D. Priyanto, M. Zarlis, and Z. Nasution, “Philosophy of Fuzzy Logic as Fundamental of Decision Making Based on Rule,” J. Phys. Conf. Ser., vol. 1230, no. 1, 2019.

A. Marbun Murni, Sandhuri, “Analysis of Application of Fuzzy Grid Partition on Mamdani Method Fuzzy Inference System,” JUSIKOM PRIMA (Jurnal Sist. Inf. dan Ilmu Komputer), vol. 6, no. 1, pp. 68–74, 2022.

F. Rastic Andrari, M. Maimunah, and Nurmala Dewi Qadarsih, “Penerapan Metode Fuzzy Mamdani Dalam Menentukan Harga Jual Ponsel Pintar Bekas (Studi Kasus Pada Kayyis Cellular Depok),” J. Ilm. Komput. Graf., vol. 14, no. 2, pp. 253–262, 2021.