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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Galih Ariwanda
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Prediksi Harga Cabai Rawit di Kota Malang Menggunakan Algoritme Extreme Learning Machine (ELM) Galih Ariwanda; Imam Cholissodin; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 6 (2019): Juni 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cayenne is a commodity for food that cannot be separated from the daily needs of people in Indonesia. Cayenne for the people in Malang City is consumed to maintain metabolism and body temperature to keep warm and vitamin C which can help maintain the health of the human body. Prices of cayenne in Malang City always fluctuate changes every day. Fluctuation changes that make the price of cayenne are difficult to predict well. In addition, the prices given by traders are always varied, cayenne pepper is also one of the contributing commodities of inflation and prevents the difference in prices obtained by consumers and farmers so that they are not harmed by each other. Therefore, it is necessary to predict the price of cayenne in Malang so that consumers and the government can take preventive measures against the existing problems. The prediction process is divided into several process including pre-processing, normalization of data, predictions using the Extreme Learning Machine algorithm, and the results of errors with MAPE. Based on the results of testing using cayenne price data from January 1, 2017 to December 31, 2018 in Malang City, the smallest MAPE value was 2.087% with 2 features, the number of neurons in the hidden layer was 5, the percentage of training data and testing data 90%:10%, and the activation function is Binary Sigmoid.
Co-Authors Imam Cholissodin Tibyani Tibyani