Hibridisasi Algoritma Fuzzy Analytic Hierarchy Process dengan Fuzzy Ultiple Attribute Decision Making Simple Attribute Weighting

Abstract

Pada penelitian ini dilakukan perbaikan serta peningkatan penelitian Dooki, et al, dimana diperoleh nilai rata-rata Efficiency Rate (ER) yang hanya sebesar 77.82 % yang masih dirasakan terlalu rendah. Pada penelitian Dooki, Bolhasani serta Fallah ini dilakukan hibridisasi algoritma Fuzzy Analytic Hierarchy Process (FAHP) dengan Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) untuk memilih inspektur kepala bank terbaik berdasarkan beberapa kriteria kualitatif dan kuantitatif dengan berbagai prioritas. Metode Fuzzy AHP dan TOPSIS digunakan untuk menentukan bobot kriteria dan pemeringkatan masing-masing inspektur yang dipilih. Pada penelitian ini telah dilakukan perbaikan serta peningkatan penelitian Dooki dan Bolhasani serta Fallah dengan melakukan perbaikan menggunakan algoritma FAHP dengan Simple Additive Weighting (SAW), dimana dilakukan dengan menerapkan Algoritma FAHP pada proses pembobotan dan SAW untuk proses pemeringkatan pada menentukan kenaikan pangkat pegawai. Hasil percobaan pemeringkatan dalam penentuan kenaikan pangkat pegawai diperoleh bahwa algoritma Hibridisasi memiliki nilai Efficiency Rate (ER) yang lebih baik dan diikuti dengan algoritma Fuzzy AHP serta Fuzzy SAW, yang berarti penelitian ini telah berhasil melakukan perbaikan penelitian Dooki dan Bolhasani serta Fallah sebesar 22.18 %.

In this research, there is improvement of Dooki et al. (2017) research, where the average value of Efficiency Rate (ER) is only 77.82% which is still too low. In Dooki, Bolhasani and Fallah's research, hybridization of Fuzzy Analytic Hierarchy Process (FAHP) algorithm was adopted by Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) to select the best bank chief inspector based on several qualitative and quantitative criteria with various priorities. The AHP and TOPSIS Fuzzy Methods are used to determine the criteria and ranking weight of each of the selected inspectors. In this research, there have been improvements of Dooki and Bolhasani and Fallah research by improving the FAHP algorithm with Simple Additive Weighting (SAW), which is done by applying FAHP Algorithm to the weighting process and SAW for the ranking process to determine the promotion of employee. The result of the ranking experiment in determining the promotion of employees was obtained that the hybridization algorithm has better Efficiency Rate (ER) and followed by Fuzzy AHP algorithm and Fuzzy SAW, which means that this research has succeeded in improving Dooki and Bolhasani and Fallah research by 22.18%.