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Analysis of Effectiveness Lot Sizing Based on Design of Experiment Nugraha, Evan; Puspawardhani, Gianti; Norina, Rida
Community Engagement and Emergence Journal (CEEJ) Vol. 6 No. 3 (2025): Community Engagement & Emergence Journal (CEEJ)
Publisher : Yayasan Riset dan Pengembangan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/ceej.v6i3.8647

Abstract

Lot sizing techniques have been widely analyzed by experts, because ordering costs, storage costs, and lot sizes have a significant impact on the total cost of ordering. This study uses lot sizing techniques including Wagner-Whitin algorithm, Silver-Meal algorithm, Least Unit Cost, Least Total Cost, Part Period Balancing, Period Order Quantity, Groff algorithm, and Lot for Lot. The data used is taken from a chemical raw material procurement company, including ordering and storage costs. The initial analysis concluded that the Silver-Meal algorithm and the Groff algorithm have relative biases that are close to the Wagner-Whitin algorithm. The second analysis concluded that for the lot sizing technique, the calculated F value (84.3) was greater than the F table value (2.1), indicating a significant effect of the lot sizing technique on the relative bias percentage. Furthermore, the demand analysis shows that the calculated F value (80.0) is greater than the F table value (2.6), indicating a significant influence of the demand on the percentage relative bias
Analysis of Effectiveness Lot Sizing Based on Design of Experiment Evan Nugraha; Gianti Puspawardhani; Rida Norina
Community Engagement and Emergence Journal (CEEJ) Vol. 5 No. 6 (2024): Community Engagement & Emergence Journal (CEEJ)
Publisher : Yayasan Riset dan Pengembangan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/ceej.v6i3.8647

Abstract

Lot sizing techniques have been widely analyzed by experts, because ordering costs, storage costs, and lot sizes have a significant impact on the total cost of ordering. This study uses lot sizing techniques including Wagner-Whitin algorithm, Silver-Meal algorithm, Least Unit Cost, Least Total Cost, Part Period Balancing, Period Order Quantity, Groff algorithm, and Lot for Lot. The data used is taken from a chemical raw material procurement company, including ordering and storage costs. The initial analysis concluded that the Silver-Meal algorithm and the Groff algorithm have relative biases that are close to the Wagner-Whitin algorithm. The second analysis concluded that for the lot sizing technique, the calculated F value (84.3) was greater than the F table value (2.1), indicating a significant effect of the lot sizing technique on the relative bias percentage. Furthermore, the demand analysis shows that the calculated F value (80.0) is greater than the F table value (2.6), indicating a significant influence of the demand on the percentage relative bias
Integrating Digital SCOR and Quality Management in the Textile Industry Evan Nugraha; Rini Mulyani Sari; Rida Norina
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8314

Abstract

The growing complexity of textile supply chains has increased the need for digital capabilities that enhance operational coordination, process integration, and quality management. The integration of digital supply chain standards with quality management remains important for improving supply chain outcomes in the textile industry. This study examines the relationship between the SCOR Digital Standard (SCOR DS) and Supply Chain Performance (SCP), with Quality Management (QM) serving as a mediating mechanism. A quantitative explanatory approach was employed using data from 320 personnel involved in supply chain, production, quality, and operational activities in the textile industry. Data were collected through structured Likert-scale questionnaires and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). SCOR DS has a significant positive effect on QM (β = 0.454, p < 0.001) and SCP (β = 0.142, p = 0.009). QM also has a stronger positive effect on SCP (β = 0.484, p < 0.001). Furthermore, QM significantly mediates the relationship between SCOR DS and SCP (β = 0.220, p = 0.007). Digital supply chain capabilities based on SCOR DS can strengthen supply chain performance, particularly when supported by effective quality management. The findings provide an integrated perspective for aligning digital SCOR practices with quality management to improve textile supply chain performance.