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All Journal Moneter : Jurnal Keuangan dan Perbankan
Pungky Nabella Saputri
Dian Nuswantoro University
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Implementation Of Extreme Gradient Boosting Algorithm For Predicting The Red Onion Prices Pungky Nabella Saputri; Farrikh Alzami; Filmada Ocky Saputra; Pulung Nurtantio Andono; Rama Aria Megantara; L Budi Handoko; Chaerul Umam; Firman Wahyudi
Moneter: Jurnal Keuangan dan Perbankan Vol. 11 No. 1 (2023)
Publisher : Universitas Ibn Khladun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (656.456 KB) | DOI: 10.32832/moneter.v11i1.55

Abstract

Red Onion or the Latin name Allium Cepa is included in the group of vegetable plants that are needed by the public for food needs. Red Onions are one of the seasonal crops so their availability can change in the market which causes price instability due to a lack of supply of production by several factors: 1) not yet it's harvest time, 2) crop attacked disease pests and fungi, and 3) weather factor. Therefore, a study is needed to predict red onion prices, so that it can be used as information for the government to stabilize red onion prices. The method used in this study is CRISP-DM and the Extreme Gradient Boosting algorithm to predict the price of red onions by taking data samples from Tegal and Pati Cities. The results of this study are that the Extreme Gradient Boosting algorithm is able to produce Tegal District Root Mean Square Error (RMSE) values of 5107.97% and Mean Absolute Percentage Error (MAPE) values of 0.17%. For prediction results with Pati Regency data samples, it produces a Root Mean Square Error (RMSE) value of 6049.74% and a Mean Absolute Percentage Error (MAPE) of 0.17%.
Co-Authors Alzami, Farrikh Chaerul Umam Filmada Ocky Saputra Firman Wahyudi L. Budi Handoko Megantara, Rama Aria Pulung Nurtantio Andono