Optimasi Fungsi Keanggotaan Fuzzy Inference System Tsukamoto dengan Particle Swarm Optimization pada Penentuan Jumlah Produksi Gula (Studi Kasus : Pabrik Gula Kebonagung Malang)

Nur Intan Savitri Bromastuty (Fakultas Ilmu Komputer, Universitas Brawijaya)
Budi Darma Setiawan (Fakultas Ilmu Komputer, Universitas Brawijaya)
Indriati Indriati (Fakultas Ilmu Komputer, Universitas Brawijaya)

Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 2 No 8 (2018): Agustus 2018

Production is an activity that resulted in goods and services with the usage of resources called production factor. The usual factors for sugar productions is farming area, sugar cane rendement, sugar cane amount, amount of labors, mechine operations, supporting materials and grinding time. Based on previous studies, the major factors that applies to PG. Kebonagung Malang are sugar cane amount, rendement, labor, and machine operations. Studies that estimate sugar production amount already exist, but it's still not optimal. This research was meant to optimize the estimation of sugar production of PG. Kebonagung Malang with particle swarm optimization method to optimize tsukamoto fuzzy inference system. Testing was done with varying particle counts and varying iteration. Computation speed decreases when the number of iterations and particles count increases. Every test with different particle count and iterations results in different fitness value.