Forecasting Palm Oil Production in North Sumatera Using the Adaptive Neuro Fuzzy Inference System Method

Riezky Purnama Sari; Adinda Tri Hidayati; Fairus Fairus

doi:10.30598/pijmathvol4iss1pp1-6

Riezky Purnama Sari Mathematics Department, Faculty of Science and Technology, Universitas Samudra, Indonesia
Adinda Tri Hidayati Mathematics Department, Faculty of Science and Technology, Universitas Samudra, Indonesia
Fairus Fairus Mathematics Department, Faculty of Science and Technology, Universitas Samudra, Indonesia

DOI: https://doi.org/10.30598/pijmathvol4iss1pp1-6

Keywords: Forecasting, Palm Oil Production, Adaptive Neuro Fuzzy Inference System

Abstract

Indonesia is an agricultural and maritime country because it is the country that has the largest agriculture and plantations in ASEAN. One of them is palm oil production, because palm oil is believed to not only be able to produce various types of butter, cooking oil or soap, but can also be a substitute for fuel oil. In the province of North Sumatra itself, oil palm is a crop that has potential and produces very high profits. Therefore, forecasting is used to determine future palm oil production results using the ANFIS method in order to increase or catalyze palm fruit. The data source used in this research comes from the Central Statistics Agency (BPS) of North Sumatra. The aim of this research is to determine the results of forecasting palm oil production in North Sumatra using the ANFIS model. So we got results from forecasting palm oil production in North Sumatra which experienced fluctuations throughout the period January 2023 to December 2024 with a forecasting accuracy level of 92% and a MAPE value of 12.778179% with MAPE criteria of 10% - 20% which was considered 'Good '. So it can be concluded that the forecasting results were carried out well and can be used for future forecasting.

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