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Maisarah Maisarah
Program Studi Statistika FMIPA ULM
Decision Sciences, Operations Research & Management Transportation

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PERAMALAN JUMLAH PRODUKSI BATUBARAMENGGUNAKAN METODE ARIMA (STUDI KASUS: PT ARUTMIN INDONESIA SITE ASAM-ASAM) Gadys Nauli Simanjuntak; Nur Salam; Maisarah Maisarah
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 17, No 1 (2023)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v17i1.9288

Abstract

In the world of industry and investment, the mining sector has an important role in producing natural resources in Indonesia. South Kalimantan Province is one of the regions which is very famous for being rich in natural resources, especially in the mining sector, especially energy minerals in the form of coal. In recent years, coal production at PT. Arutmin Asam Asam experienced an unstable amount of production. This study aims to obtain the best model and predict the amount of coal production at PT Arutmin Indonesia Site Asam-Asam, South Kalimantan Province using the ARIMA (Autoregressive Integrated Moving Average) method. The best Autoregressive Integrated Moving Average (ARIMA) method for predicting coal production at PT Arutmin Indonesia Site Asam-Asam is the ARIMA model (2,1,3) with a smaller Root Mean Square Error (RMSE) compared to other models, namely 92029.74. Forecasting results of coal production at PT Arutmin Arutmin Site Asam-Asam from January to August 2023 tend not to indicate stability or there will be increases and decreases in the forecasting results obtained.
PERAMALAN JUMLAH PRODUKSI TANDAN BUAH SEGAR (TBS) KELAPA SAWIT MENGGUNAKAN METODE FUZZY TIME SERIES (STUDI KASUS: PT KALIMANTAN SAWIT KUSUMA) Rizka Indriyani Pratiwi; Nur Salam; Maisarah Maisarah
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 17, No 2 (2023)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v17i2.9338

Abstract

Palm oil is a type of plantation crop that occupies an important position in the agricultural and plantation sectors. This is because oil palm is the largest producer of economic value per hectare in the world. The oil produced by palm oil comes from Fresh Fruit Bunches (FFB) which consist of various levels of maturity. PT Kalimantan Sawit Kusuma is experiencing instability in the amount of production, so forecasting is needed to estimate how to keep the amount of production stable. The method used is fuzzy time series (FTS), which is data forecasting that applies fuzzy sets as a basis for forecasting modeling by processing past data patterns to be applied in predicting future data. The goal is to obtain forecasting results for FFB production from April 2023 to December 2023 and obtain a Mean Absolute Percentage Error (MAPE) value. Forecasting results of Palm Oil FFB Production applying FTS Lee Order 1 in April 2023 to December 2023 are 8,412, 8,309, 8,309, 8,309, 8,309, 8,309, 8,309, 8,309 and 8,309 tons with a MAPE value of 9.07046%. While the forecasting results for Palm Oil FFB Production using FTS Lee Order 2 for April 2023 to December 2023 are 7,309, 8,559, 7,309, 8,559, 7,309, 7,309, 8,559 and 7,309 tons with a MAPE value of 4.80541%.
Co-Authors Gadys Nauli Simanjuntak Nur Salam Rizka Indriyani Pratiwi