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Forecast of sugar demand in retail using SARIMA and decomposition models case study: a retail store in Indonesia Sari, Titi; Sakti, Sekar
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.006

Abstract

This study discusses forecasting demand in a retail store, focusing on sugar, which is a staple food in Indonesia, as the research object. Despite its importance and forecast challenge, there is no research has been done on sugar at the retail level. This study aims to find the most suitable forecast model that can capture data patterns well to give a good prediction of sugar sales in a retail store in Indonesia by comparing SARIMA and decomposition models. This study uses a stationary test and ACF pattern analyses to prepare the data, a residual test to avoid forecast bias, cross-validation to check the forecast model performance, and MAPE as the performance indicator. SARIMA (0,0,0)(0,1,1)8 and multiplicative decomposition with 3 periods of double-moving average models are chosen. Both models have similar patterns but different slopes because the decomposition model is more sensitive to data patterns, resulting in different MAPEs, which are 15.22% and 13.64%.  Despite the popularity of SARIMA, decomposition can be an interesting alternative to use since it can capture trend data patterns better. However, the short forecast period is preferable for the decomposition model to avoid high trend slope prediction in the long run, leading to more frequent forecast activity and higher resources compared to SARIMA.
PENGENDALIAN PERSEDIAAN BAHAN BAKU MENGGUNAKAN METODE ANALISIS ABC, PERAMALAN, DAN ECONOMIC ORDER QUANTITY (EOQ) PADA PT. XYZ Maharani, Maya Putri; Sari, Titi
J@ti Undip: Jurnal Teknik Industri Vol 20, No 2 (2025): Mei 2025
Publisher : Departemen Teknik Industri, Fakultas Teknik, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jati.20.2.95-103

Abstract

Di era globalisasi, efisiensi pengelolaan persediaan menjadi kunci daya saing perusahaan. PT. XYZ, produsen obat tradisional, makanan, dan minuman, menghadapi tantangan akibat sistem persediaan yang tidak optimal, seperti ketiadaan safety stock dan reorder point, yang mengganggu produksi dan kepuasan pelanggan. Penelitian ini bertujuan untuk menganalisis pengelolaan persediaan bahan baku di PT. XYZ dengan menerapkan metode Analisis ABC, peramalan, dan Economic Order Quantity. Metode penelitian melibatkan observasi, wawancara, dan studi pustaka untuk memperoleh data mengenai kebutuhan bahan baku. Hasil penelitian menunjukkan bahwa pada kategori A yakni 20% dari total keseluruhan bahan baku yakni sebanyak 16 bahan baku dari 84 bahan baku di PT. XYZ, yang memerlukan perhatian lebih dalam pengelolaannya. Berdasarkan hasil pengukuran data pada ARIMA dengan model tentatif dari ketiga model yang ada, yang terbaik adalah 0;1;1 karena memiliki nilai signifikan dengan nilai MSE, MAD, dan MAPE masing-masing secara berurutan yakni 123,179, 15,3, dan 1,645. Metode EOQ dan Analisis ABC terbukti efektif meningkatkan efisiensi persediaan. Dengan menerapkan metode EOQ, maka perusahaan dapat menghemat biaya persediaan sampai 41% pada bahan baku kategori A. Abstract[Raw Material Inventory Control Using ABC Analysis, Forecasting, and Economic Order Quantity (EOQ) Methods at PT. XYZ] In the era of globalization, the efficiency of inventory management is key to a company's competitiveness. PT XYZ, a manufacturer of traditional medicines, food, and beverages, faces challenges due to a non-optimal inventory system, such as the absence of safety stock and reorder points, which disrupts production and customer satisfaction. This study aims to analyze the management of raw material inventory at PT XYZ by applying the ABC Analysis, forecasting, and Economic Order Quantity methods. The research method involves observation, interviews, and literature studies to obtain data on raw material requirements. The results showed that category A, which is 20% of the total raw materials, namely 16 raw materials out of 84 raw materials at PT XYZ, requires more attention in their management. Based on the results of measuring data on ARIMA with a tentative model of the three existing models, the best is 0; 1; 1 because it has a significant value with MSE, MAD, and MAPE values of 123.179, 15.3, and 1.645 respectively. The EOQ method and ABC analysis have proven effective in improving inventory efficiency. By applying the EOQ method, the company can save up to 41% on inventory costs for Category A raw materials.Keywords: ARIMA; Cost Efficiency; Stock Optimization; EOQ; Inventory Management; Planning