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All Journal Jurnal Matematika UNAND Tensor: Pure and Applied Mathematics Journal
Nurfitri Imro'ah
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Computer Science & IT Mathematics

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Forecasting The Production of Crude Palm Oil (CPO) in Indonesia 2022 using the Grey(1.1) Model Nur'ainul Miftahul Huda; Nurfitri Imro'ah; Dea Rizki Darmawanti
Tensor: Pure and Applied Mathematics Journal Vol 3 No 1 (2022): Tensor: Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol3iss1pp1-10

Abstract

Crude Palm Oil (CPO) is a vegetable oil produced from oil palm fruit plants. Palm oil can be used for many things, including for various foods, cosmetics, hygiene products, and can also be used as a source of biofuel or biodiesel. Indonesia is a country with the most CPO production in the world. However, the development of CPO production must be appropriately managed to meet demand from other countries. Therefore, this study aims to predict CPO production in 2022. One of the appropriate statistical methods is the Grey(1.1) model. This model was chosen based on the availability of CPO production data by the Central Statistics Agency, which only presents annual data from 2017 - 2021. So, the number of observations that can be used to predict CPO production in Indonesia is only five observations. The Grey(1.1) model can cover problems in the availability of small amounts of data. There are three main steps in the modelling procedure with Grey(1,1) model, namely forming an Accumulated Generated Operation (AGO) sequence, then forming a Mean Generating Operation (MGO) sequence, and the last step is a prediction with Inverse AGO (1-AGO). This study obtained the 1-AGO sequence on the Grey(1.1) model for CPO production in Indonesia with outstanding accuracy, namely the Mean Absolute Percentage Error (MAPE) value of 0.01%. In addition, a prediction of CPO production in Indonesia for 2022 is made, which is 52590612.99 (an increase of 2339783.668 from 2021).
ANALYSIS OF FOREST FIRE CASES USING GSTAR(1;1) MODEL WITH SPATIAL ROOK CONTIGUITY WEIGHTS MATRIX IN WEST KALIMANTAN Muhammad Yahya Ayyash; Nur'ainul Miftahul Huda; Nurfitri Imro'ah; Hesty Pratiwi
Jurnal Matematika UNAND Vol. 15 No. 2 (2026)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.15.2.259-273.2026

Abstract

In West Kalimantan, forest and land fires cause damage to ecosystems, the loss of biodiversity, and detrimental repercussions on both health and the local econ- omy. Extreme weather and land clearance for agricultural and plantation purposes are the primary reasons. This study aims to investigate forest fires’ spatial and temporal pat- terns by employing the Generalized Space-Time Autoregressive (GSTAR)(1;1) approach with spatial rook contiguity weights. From January 2020 to March 2024, the data used consisted of the number of monthly forest fires that occurred in the Ketapang, Sanggau, Sintang, Landak, and Sekadau Regencies. According to the findings, the spatial pattern demonstrates strong interactions between regions in which flames in one area affect fires in other locations. The temporal pattern demonstrates that prior fires can impact fires that occur in the subsequent period, depending on the area. The model has an aver- age accuracy level of 13%, which indicates that this model has a reasonable degree of accuracy that can be used for making predictions. This study concluded that a better understanding of the spatial-temporal patterns of forest fires can improve early warning systems and rapid responses to probable future fires.
Co-Authors Dea Rizki Darmawanti Hesty Pratiwi Muhammad Yahya Ayyash NUR’AINUL MIFTAHUL HUDA