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All Journal Jurnal Media Computer Science
Achras Zapota Alrahim
Program Studi Informatika, Fakultas Ilmu Komputer, Universitas Dehasen Bengkulu
Computer Science & IT

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The Implementation Of Extreme Learning Machine Methods In Predicting The Total Production Of Palm Oil (Case Study In pt. Bumi Raflesia Indah) Achras Zapota Alrahim; Indra Kanedi; Eko Suryana
Jurnal Media Computer Science Vol 1 No 2 (2022): Juli
Publisher : Fakultas Ilmu Komputer Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (476.141 KB) | DOI: 10.37676/jmcs.v1i2.2702

Abstract

PT. Bumi Raflesia Indah is one of the companies that manages palm oil production. In the palm oil industry there is a collection of information that can be extracted and developed for the advancement of the industry. The data has been processed using the office application package, namely Microsoft Excel. However, the data is only for filing for PT. Bumi Raflesia Indah and was not reviewed for information in the data. Application of Prediction of Total Palm Oil Production Results at PT. Bumi Raflesia Indah was created using the Visual Basic.Net programming language and SQL Server 2008 database by applying the Extreme Learning Machine Method. In the application of the Extreme Learning Machine Method, predictions are made to determine the amount of production for 12 months in 2021 based on trend data analysis of palm oil production for 12 months in 2020. Based on the results of the tests that have been carried out, the Prediction Application for the Amount of Palm Oil Production at PT. Bumi Raflesia Indah is successfully carried out, and can provide predictive information on the amount of palm oil production for 12 months in the following year, as well as the functionality of the application has been running as expected
Co-Authors Eko Suryana Kanedi, Indra Kanedi