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

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Prediksi Harga Cabai menggunakan Metode Long-Short Term Memory (Case Study : Kota Malang) Michael David; Imam Cholissodin; Novanto Yudistira
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 3 (2023): Maret 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Chili peppers are fruits or plants of the genus Capsicum. Fruits can be classified as spices or vegetables. As a spice, chili peppers are very popular in Southeast Asia as a food flavor enhancer. Chilies have some nutritional content in 100 grams of it, which content: Water, energy, protein, fat, carbohydrates, fiber, calcium, etc. Chili also has several benefits, including: Relieve pain, maintain digestive health, maintain blood sugar levels, etc. In Malang, chili prices fluctuate, so the price of chili is difficult to predict. This makes the government worried in maintaining the stabilization of chili prices so that they remain affordable and the chili price inflation in Malang City will be good. In this research, several prediction processes were carried out, including, consisting of pre-processing, data normalization, training and prediction using the Long Short-Term Memory method, and error results using the Mean Square Error (MSE). Based on the tests that have been done using daily data on cayenne pepper prices from January 1 2021 to July 31 2022 in Malang City using the Long Short-Term Memory method, the smallest MSE result is 0.0155 with a proportion of training data and testing data of 70%; 30%, with 21 sequence data, 128 hidden units and 150 epochs.
Co-Authors Imam Cholissodin Novanto Yudistira