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All Journal IJISTECH (International Journal Of Information System & Technology) IJISTECH
Adeputra, James
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Social Sciences

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Optimization of Spareparts Stock Data Management at PT. Astra Motor Kaltim 2 using the Trend Moment Method Adeputra, James; Pratiwi, Heny; Wahyuni, W
IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i6.380

Abstract

Spareparts inventory management is a crucial aspect of operations in automotive companies, including PT. Astra Motor Kaltim 2. An imbalance between demand and spareparts availability can lead to stockpiling or stock shortages, ultimately resulting in operational cost inefficiencies. Therefore, this study aims to analyze and forecast spareparts sales using the Trend Moment method to optimize stock management. The Trend Moment method is used to identify sales trend patterns for sparepart 44711K59A12, based on historical sales data from September 2024 to February 2025. The forecasted results are then adjusted using a seasonal index to improve accuracy. Forecast accuracy is evaluated using the Mean Absolute Percentage Error (MAPE), which provides an overview of how close the forecasted results are to the actual data. The results of the study show that the Trend Moment method can provide fairly accurate predictions in estimating the demand for sparepart 44711K59A12 in the upcoming periods. By implementing this method, the company can develop a more efficient stock procurement strategy, reduce the risk of overstocking or stockouts, and improve customer satisfaction. In conclusion, this forecasting approach can serve as a solution to enhance the effectiveness of spareparts inventory management at PT. Astra Motor Kaltim 2
Optimization of Spareparts Stock Data Management at PT. Astra Motor Kaltim 2 using the Trend Moment Method Adeputra, James; Pratiwi, Heny; Wahyuni, W
IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i6.380

Abstract

Spareparts inventory management is a crucial aspect of operations in automotive companies, including PT. Astra Motor Kaltim 2. An imbalance between demand and spareparts availability can lead to stockpiling or stock shortages, ultimately resulting in operational cost inefficiencies. Therefore, this study aims to analyze and forecast spareparts sales using the Trend Moment method to optimize stock management. The Trend Moment method is used to identify sales trend patterns for sparepart 44711K59A12, based on historical sales data from September 2024 to February 2025. The forecasted results are then adjusted using a seasonal index to improve accuracy. Forecast accuracy is evaluated using the Mean Absolute Percentage Error (MAPE), which provides an overview of how close the forecasted results are to the actual data. The results of the study show that the Trend Moment method can provide fairly accurate predictions in estimating the demand for sparepart 44711K59A12 in the upcoming periods. By implementing this method, the company can develop a more efficient stock procurement strategy, reduce the risk of overstocking or stockouts, and improve customer satisfaction. In conclusion, this forecasting approach can serve as a solution to enhance the effectiveness of spareparts inventory management at PT. Astra Motor Kaltim 2
Co-Authors Pratiwi, Heny W Wahyuni, W