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All Journal SemanTIK : Teknik Informasi
Janter Manuel Gultom
STIKOM Tunas Bangsa Pematangsiantar
Computer Science & IT Control & Systems Engineering

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PERAMALAN TINGKAT PRODUKTIVITAS KEDELAI DI INDONESIA MENGGUNAKAN ALGORITMA BACKPROPAGATION Irvan Leonardo Sirait; Janter Manuel Gultom; Joel Tindaon; Rizki Josua Tampubolon; Widya Juli Mawaddah
semanTIK Vol 4, No 2 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (823.569 KB) | DOI: 10.55679/semantik.v4i2.5196

Abstract

The soybean is an important food commodity in Indonesia. That's because soybean is one of the main sources of vegetable protein for the community. Therefore this research is done to know how big the development of productivity level of soybean in Indonesia in the future, so that later can be used as a reference for government and farmer to maximal again in managing soybean crop to avoid import soybean from other countries. The data used in this research is data of soybean productivity by the province in Indonesia year 2005-2015. The algorithm used is an Artificial Backpropagation Neural Network. This research uses 5 architecture, the best architecture is 5-12-1 with 82% accuracy percentage and MSE value equal to 0,00904753. Thus, this model is good enough to predict soybean productivity in every province of Indonesia.Keywords— Forecasting, Productivity, Soybean, Indonesia, BackpropagationDOI : 10.5281/zenodo.2528152
Co-Authors Irvan Leonardo Sirait Joel Tindaon Rizki Josua Tampubolon Widya Juli Mawaddah