Forecasting Harga Komoditi Pokok Jambu Mete di Sumba Barat Daya dengan Menggunakan Metode Supervised Machine

Yotan Hendra Huan; Andry Ananda Putra Tanggu Mara; Titus Kurra

doi:10.53863/kst.v5i02.927

Authors

Yotan Hendra Huan Program Studi Teknik Informatika, STIMIKOM Stella Maris Sumba, Indonesia
Andry Ananda Putra Tanggu Mara Program Studi Teknik Informatika, STIMIKOM Stella Maris Sumba, Indonesia
Titus Kurra Program Studi Teknik Informatika, STIMIKOM Stella Maris Sumba, Indonesia

DOI:

https://doi.org/10.53863/kst.v5i02.927

Keywords:

Cashew, Commodities, Machine Learning, Forecasting

Abstract

Cashew (Anacardium Occidentale L) is one of the plantation crop commodities which has economic significance and quite potential because its production can be used as raw material for the food industry. According to the Big Indonesian Dictionary (KBBI), commodities are raw materials for agricultural products, merchandise, primary goods and local crafts that can be used as export commodities, such as wheat, curry, coffee, etc. Southwest Sumba Regency is one of the places where cashew is produced to increase farmers' income, but the potential of the cashew crop must be balanced with the right price. Many researchers carry out forecasting using various methods, but in this research, the technique used is supervised learning, namely linear regression, which has a relatively high level of accuracy. This research uses the Linear Regression method to produce accurate price forecasts and to know the influence of future rises and falls in cashew prices in the Southwest Sumba district. The forecasting results in this research were Rp. 14,272/Kg with an RMSE value of 0.794.

Keywords: Cashew, Commodities, Machine Learning, Forecasting

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