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All Journal JoDENS: Journal of Digital Ecosystem for Natural Sustainability
Prisselix, Juven
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Computer Science & IT Decision Sciences, Operations Research & Management

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Implementasi Regresi Linear Untuk Memprediksi Hasil Impor Jumlah Barang Konsumsi Tahun 2021-2036 Anthonius; Luise, Charles Calvin King; Prisselix, Juven
Journal of Digital Ecosystem for Natural Sustainability Vol 1 No 2 (2021): Desember 2021
Publisher : Fakultas Komputer - Universitas Universal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63643/jodens.v1i2.38

Abstract

Import is a very important activity for a country and the value always changing every year, this thing can affect the foreign exchange of a country. When a country consumed a lot goods, it resulted in the country to do a lot of import activity as well. By doings so, the economy would be unbalanced and so the country will has a lot of debts. With that in mind, predicting the import activity in the future can be essential to prevent the country from being unbalanced in terms of economy. The purpose of this research is to predict the future import activity by using Linear Regression Algorithm and applying Cross-Industry Standard Process for Data Mining (CRISP-DM) method. This method uses to find the value of regression equation, as well as getting error analysis through accuracy of predictions using MAD, MSE, and MAPE using R. Studio software. The results that was obtained for 2021 amounted to 6745.298 tons and 2022 amounted to 6578.703 tons. As for the resulting error analysis, MAD value is 2652.901, MSE value is 10002316 and MAPE value is 255.17%.
Co-Authors Anthonius Luise, Charles Calvin King