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All Journal Telematika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Respati Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Pengabdian Mitra Masyarakat (JPMM) Jurnal Pengabdian Teknik dan Ilmu Komputer (PETIK) Jikom: Jurnal Informatika dan Komputer Jurnal Abdimastek (Pengabdian Masyarakat Berbasis Teknologi) Journal Of Artificial Intelligence And Software Engineering
Faruk Alfiyan
Sekolah Tinggi Ilmu Komputer PGRI Banyuwangi
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Medicine & Pharmacology Social Sciences Other

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Journal : Journal Of Artificial Intelligence And Software Engineering

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Implementation Of Fuzzy Sugeno Method To Determine The Production Amount Of Android-Based Oyster Mushroom Baglogs Budiarto, Sony Panca; Alfiyan, Faruk Alfiyan
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6285

Abstract

The agricultural industry is one of the key sectors of the global economy. Along with the increasing demand for agricultural products, the challenge to improve production efficiency and productivity is also increasingly urgent. Oyster mushroom (Pleurotus ostreatus) is one of the agricultural commodities that has great potential to be developed, has high nutritional value, and growing demand in the global market. In facing the challenges of increasing oyster mushroom production, there are several problems that must be overcome. One of them is determining the right amount of oyster mushroom baglog needed to match the increasing demand and supply of oyster mushrooms. The decision-making process in determining the optimal amount of baglog production is often complex and requires in-depth analysis of various variables. In this study, researchers used the Fuzzy Inference System (FIS) Sugeno method to determine the optimal amount of oyster mushroom baglog production. The Sugeno method was chosen because it can produce clear rule-based solutions by better considering the correlation between input variables. The FIS will be developed based on previous baglog demand, inventory, and production data. The system is developed based on Android Mobile using React Native. The results of measuring the validation value and accuracy of Sugeno fuzzy applications in predicting the number of oyster mushroom baglog needs get a MAPE value of 1.88%; the prediction method used is in the very good category.
Co-Authors Aidina, Eca Dwi Yulian RL Eko Heri Susanto Indartono, Nur Ahmadi Khoirul Umam Moh Yanu Adianwar Novandi, Aditya Rizky Rifki Indriyani Sony Panca Budiarto Sumbaga, Moch. Surya Aji Uchrowiya, Latifatul