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Forecasting of jansen's rice inventory control using monte carlo and markov chain techniques Hasni Indah Sari; Sajaratud Dur; Hendra Cipta
International Journal of Basic and Applied Science Vol. 11 No. 2 (2022): Sep: Basic and Applied Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v11i2.99

Abstract

Rice is an essential commodity in Indonesia because of its role as a staple food, which most Indonesians consume daily as a carbohydrate intake. In its development to meet these needs, many things affect the stability of the availability and price of this rice. They are starting from climatic conditions, logistics systems, and the state of the domestic market and the international rice market. On the other hand, the increase in national rice consumption from year to year will continue to grow along with the rise in population. This research aims to apply the Monte Carlo and Markov Chain method to control Jansen rice supplies at the Jansen Rice Mill, Paluh Wave Street, Percut Sei Tuan District, Deli Serdang Regency, North Sumatra Province. The data used is data on rice demand from 2016 to 2021. Monte Carlo forecasts for the next few years, and Markov Chain provides what percentage of opportunities for rice demand to increase or decrease.