IMPROVING MATERIAL SHORTAGE FOR SMALL-MEDIUM ENTERPRISES (SME) IN PEST CONTROL INDUSTRY
Abstract
Abstract: Micro, Small, and Medium Enterprises (SME) are the main pillars of the Indonesian economy because they have a strong foundation in driving the wheels of the national economy. Inventory is an essential factor in SME production costs to boost competitive advantage. Conventionally, Local SMEs in the pest control industry do not yet have a method or system of inventory control for pest control raw materials. This study tries to conduct in-depth research of local SMEs in the pest control industry to minimize the shortage of raw materials. An observation of this study found out that material shortage in local SME could happen every month that caused stop supply to customers. The objective of this paper proposes an appropriate and efficient stock of pest control material to improve the shortage problem. For achieving the research objective, the approach used a case study on Nuvaq material inventory in an SME in Jakarta, Indonesia.. The forecasting technique with minimal error is the Linear Regression method giving results with the smallest forecast errors. It can be seen from the smallest MAD, MAPE, SEE, and MSE. The economic order quantity is 100 Liter Nuvaq Material, reorder points can be made when the supply is 36 Liters, and safety stock for Nuvaq raw materials is 16 liters.
References
Agung, D., & Hasbullah, H. (2019). Reducing the Product Changeover Time Using Smed & 5S Methods in the Injection Molding Industry. Sinergi, 23(3), 199. https://doi.org/10.22441/sinergi.2019.3.004
Attarian, F., Javanmard, H., Mardani, A., Kish, E., & Soltan, H. (2009). Production Planning in the Inventory Limited Capacity Setting Assuming Permissible Storage Shortage Using Dynamic Programming Model. Lecture Notes in Engineering and Computer Science, 2176(1), 640–644.
Bahagia, Senator Nur. ”Sistem Inventori”, Departemen Teknik Industri Institut Teknologi Bandung, 2003.
Gaspersz, Vincent. Production Planning and Inventory Control, PT. Gramedia Pustaka Utama, Jakarta, 2003.
Godichaud, M., & Amodeo, L. (2019). EOQ models with stockouts for disassembly systems. IFAC-PapersOnLine, 52(13), 1681–1686. https://doi.org/10.1016/j.ifacol.2019.11.442
Hasbullah, H. (2021). Pricing of Medical Instrument Products for Domestic Production through Investment Feasibility Analysis Hasbullah1. 12(June), 9–18. https://doi.org/10.21512/comtech.v12i1.6605
Hasbullah, H., & Santoso, Y. (2020). Overstock Improvement by Combining Forecasting , EOQ , and ROP. Jurnal PASTI, XIV(3), 230–242.
Hartini, S. 2011. Teknik Mencapai Produksi Optimal. Bandung: Lubuk Agung
Heizer Jay, Render Barry. 2005. Operations Management. Jakarta: Salemba Empat.
Katarina Zita Anggriana. 2015. Analisa Perencanaan dan Pengendalian Persediaan Produk Busbar Berdasarkan sistem MRP di PT. TIS. Jurnal PASTI, Vol.9, No.3 :320-337
Kore, E. L. R., & Septarini, D. F. (2018). ANALISIS KINERJA USAHA MIKRO KECIL DAN MENENGAH (UMKM) (Studi Kasus Pada UMKM Sektor Industri Kecil Formal Di Kabupaten Merauke). Jurnal Ilmu Ekonomi & Sosial, 9(1), 22–37. https://doi.org/10.35724/jies.v9i1.703
Indroprasto, Erma Suryani. 2012. Inventory Control Analysis of Products Using EOQ Method Using Genetic Algorithms To Streamline Inventory Costs. Engineering Journal ITS, Vol. 1
Lindawati. (2003). Perencanaan bahan baku di CV. Soloindo Tama. Universitas Kristen Petra. http://dewey.petra.ac.id_jiunkpe_3882_html
Maryani, E., Purba, H. H., & Sunadi, S. (2020). Process Capability Improvement Through DMAIC Method for Aluminium Alloy Wheels Casting. Journal of Industrial Engineering & Management Research, 1(4), 19-26. https://doi.org/10.7777/jiemar.v1i4.98
Purwanto, A. (2020). Design of Food Product Using Quality Function Deployment in Food Industry. Journal of Industrial Engineering & Management Research, 1(1), 1-16. https://doi.org/10.7777/jiemar.v1i1.20
Ptak, C. A., & Smith, C. (2011). Orlicky's material requirements planning. New York: McGraw-Hill.
Rossit, D. A., Tohmé, F., & Frutos, M. (2019). A data-driven scheduling approach to smart manufacturing. Journal of Industrial Information Integration, 15, 69–79. https://doi.org/10.1016/j.jii.2019.04.003
Nur, R., & Suyuti, M. A. (2020). Mini Press Tool as Learning Practical: Designing, Manufacturing, and Analysis. Journal of Industrial Engineering & Management Research, 1(2), 9-14. https://doi.org/10.7777/jiemar.v1i2.34
Shao, X. F., Liu, W., Li, Y., Chaudhry, H. R., & Yue, X. G. (2021). Multistage implementation framework for smart supply chain management under industry 4.0. Technological Forecasting and Social Change, 162(September 2020). https://doi.org/10.1016/j.techfore.2020.120354
Sofjan, Assauri 2008. Manajemen Produksi Dan operasi. Jakarta : Lembaga Penerbit FEUI. hal. 237
Sofyan, Diana Khairani, ST.,MT. 2013. Perencanaan Dan Pengendalian Produksi. Yogyakarta : Graha Ilmu. hal.49
Sofyan, Diana Khairani, ST.,MT. 2013. Perencanaan Dan Pengendalian Produksi. Yogyakarta : Graha Ilmu. hal.49
Zhong, R. Y., Huang, G. Q., Lan, S., Dai, Q. Y., Chen, X., & Zhang, T. (2015). A big data approach for logistics trajectory discovery from RFID-enabled production data. International Journal of Production Economics, 165, 260–272. https://doi.org/10.1016/j.ijpe.2015.02.014