Optimasi Fuzzy Inference System Tsukamoto Menggunakan Algoritme Genetika Untuk Mengetahui Lama Waktu Siram Pada Tanaman Strawberry - Muhammad Khaerul Ardi; Budi Darma Setiawan; Mochammad Ali Fauzi (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2018)
Soil is a crusial component for plant growth. There are many parameters that used for soil examination, and one of its parameter is soil's dampness. Laboratorium Benih Balai Pengkajian Teknologi Pertanian Jawa Timur is one of the work units that has a duty to examine the soil for plant nursery purpose. However, due to the conventional tools that they used sometimes the examination result is not as accurate as they expected. Because of that problem the author did some research to make a smart computing system that can be implemented on a tool that can maintain the soil's dampness automatically. Fuzzy Inference System Tsukamoto is used to calculate how long does it take to water the plants by using two variable inputs; initial dampness and water volume. Genetic algorithm is used to get an optimal membership function by optimizing the boundaries of each membership function. The output of this research will display the optimal time to water the plants. From the examination result we got an error value for about 4,9570, but after optimization the number is reduced to 0,3790. With that result we can conclude that using Fuzzy Inference System Tsukamoto and optimized with genetic algorithm is able to calculate how much time that it takes to water the plants and still able to get a good outcome.