Open AccessFORECASTING RICE INVENTORY IN INDONESIA USING THE ARIMA ALGORITHM METHOD
Author(s) -
Faisal Rizki Kurniawan,
Rudi Sutomo
Publication year - 2021
Publication title -
journal of multidisciplinary issues
Language(s) - English
Resource type - Journals
ISSN - 2798-6454
DOI - 10.53748/jmis.v1i2.15
Subject(s) - autoregressive integrated moving average , economic shortage , novelty , stock (firearms) , agriculture , globalization , computer science , econometrics , economics , agricultural economics , time series , engineering , geography , machine learning , mechanical engineering , linguistics , philosophy , theology , archaeology , government (linguistics) , market economy
Objective – The global development of the world is increasingly developing, and complex accompanied by the era of globalization, making various sectors of need to follow these developments. The agricultural sector, which is the main sector, especially in the need for food for every society, especially in Indonesia, is also touched by technological developments. Planning the supply of rice needed monthly is crucial so that there is no excess or shortage of the required rice stock.Methodology – Made predictions from the amount of rice stock data using the CRISP-DM method to analyze the data and use the ARIMA Algorithm.Findings – This research predicts the amount of rice production that will be carried out in the next few months by applying the forecasting or prediction method using the CRISP - DM method and using the ARIMA algorithm.Novelty – This study predicts the amount of stock of an item using Rapidminer tools.