Optimization of Weekday Inventory Allocation Based on Sales Targets at the Indomaret Point Rest Area at KM 65 B Using a Constraint Coefficient Matrix and Linear Programming
DOI:
https://doi.org/10.61730/zcrmtn27Keywords:
Indomaret Point, Linear Programming, Matriks Koefisien Kendala, Optimasi StokAbstract
Purpose: This study aims to formulate an optimal inventory allocation strategy for weekdays at Indomaret Point Rest Area KM 65 B in order to improve profitability and achieve sales targets more effectively amid capital and shelf-capacity constraints. Methods: The analysis focuses on identifying the optimal combination of products based on contribution margins, capital availability, and storage limitations. Results: The findings reveal that inventory optimization is achieved by prioritizing product x9, which provides the highest contribution margin of Rp3,212 per unit, along with product x1 to maintain stable daily sales volume. The proposed optimization model recommends stocking a total of 434 units with a required capital investment of Rp1,376,733. The model also demonstrates the ability to reduce the risk of dead stock while improving Sales Per Day (SPD) target achievement. Conclusions: The implementation of Linear Programming through the Simplex method can support more efficient inventory management and enhance profitability in modern retail operations. The optimization model provides a practical basis for improving logistics and stock allocation decisions. Originality/value: This study contributes by applying a mathematical optimization approach to inventory allocation in a modern retail context, particularly in minimizing dead stock risk and maximizing sales performance under operational constraints.
References
Akbar, Y. R., & Mar'aini. (2022). Optimasi produksi pada industri kecil dan menengah Karya Unisi dengan penerapan model linear programming. Jurnal Inovasi Penelitian, 2(8), 2883–2892.
Anton, H., & Rorres, C. (2013). Elementary linear algebra: Applications version (11th ed.). John Wiley & Sons.
Dantzig, G. B. (1963). Linear Programming and Extensions. Princeton University Press.
Fauzi, M. A. (2021). Algoritma simpleks dalam penentuan kombinasi stok barang pada usaha ritel modern. Jurnal Sains Manajemen, 7(1), 15–28.
Heizer, J., Render, B., & Munson, C. (2017). Operations management: Sustainability and supply chain management (12th ed.). Pearson.
Hillier, F. S., & Lieberman, G. J. (2015). Introduction to operations research (10th ed.). McGraw-Hill Education.
Kurniawan, D., & Setiawan, A. (2022). Implementasi metode simpleks dalam optimasi keuntungan pada gerai ritel modern. Jurnal Ekonomi dan Bisnis, 11(1), 45–56.
Mulyono, S. (2017). Riset operasi. Lembaga Penerbit Fakultas Ekonomi Universitas Indonesia.
Pratama, R. A., & Hidayat, M. N. (2023). Analisis sensitivitas dan matriks koefisien kendala pada model pemrograman linier pengadaan barang. Jurnal Matematika Terapan, 8(3), 210–222.
Putra, A. S. (2020). Model linear programming untuk efisiensi modal kerja pada minimarket di area transit. Jurnal Logistik dan Rantai Pasok, 3(2), 77–85.
Silver, E. A., Pyke, D. F., & Thomas, D. J. (2017). Inventory and production management in supply chains (4th ed.). CRC Press.
Subagyo, P., Asri, M., & Handoko, T. H. (2000). Dasar-Dasar Operations Research. BPFE.
Taha, H. A. (2017). Operations research: An introduction (10th ed.). Pearson.
Winston, W. L. (2004). Operations research: Applications and algorithms. Cengage Learning.
Yulianto, E. (2024). Manajemen rantai pasok dan optimasi stok ritel menggunakan pendekatan kuantitatif. Jurnal Industri dan Bisnis, 12(1), 88–102.
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Copyright (c) 2026 Loranty Folia Simanjuntak, Felysha Putri Saulina Siregar, Rut Yosepina Sinaga, Gita Andhara Nasution, Wajra Ceyna Cakti Tarigan
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