Penerapan Rantai Markov dalam Memprediksi Jumlah Produksi Kelapa Sawit dan Luas Lahan Panen di Enam Kabupaten Provinsi Sumatera Utara

Abstract

The Markov Chain is a method that can be used to determine or predict future opportunities that serves to help decision making, where the conditional chances of future events depend only on present events not on past events. In this study, the Markov chain was applied to the plantation sector to predict the amount of oil palm production and the area of harvested land for six districts in North Sumatera Province in the future. The data used in this study is secondary data obtained from the Badan Pusat Statistic (BPS) of North Sumatera, namely data on the amount of oil palm production and the area of harvested land in six districts in North Sumatera Province for the period 2006 to 2020. This study aims to determine the opportunity for the transfer (transition) of the amount of oil palm production and the area of harvested land which is divided into four limited states, namely the opportunity for a state to rise drastically, a state of rise, a state of descent and a state of drastic decline. The results of the study obtained inform that the amount of oil palm production and harvested land area in six districts in North Sumatera Province will increase in line with the increase in the area of harvested land every year and the amount of oil palm production decreases along with the decrease in the area of harvested land due to the diverted land function.