Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Teknik Ilmu dan Aplikasi

H2O ALGORITHM FOR JATROPHA CURCAS DISEASE IDENTIFICATION WITH FEATURE SELECTION USING GENETIC ALGORITHM Rahmat Ramadhani; Triando Hamonangan Saragih; Muhammad Haekal
Jurnal Teknik Ilmu dan Aplikasi Vol. 4 No. 1 (2023): Jurnal Teknik Ilmu dan Aplikasi
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jtia.v4i1.2788

Abstract

Jatropha curcas is a plant that can be used as a substitute for diesel fuel. Lack of knowledge of farmers and the limited number of experts and extension agents into the problem of dealing with the disease Jatropha curcas plant which resulted in lower quality of Jatropha curcas. H2O Algorithm can be used for Jatropha Curcas disease identification. Based on previous research, H2O Algorithm gave 96.066%. In this research, we used Genetic Algorithm to do feature selection. H2O algorithm with feature selection gave average accuracy 97.03%, that means were better than without feature selection. The parameters that we got are number of populations 600, crossover rate 0.8 and mutation rate 0.2, and number of iterations 400. However, the time spent using feature selection is so longer than without feature selection.