Peran Rencana Produksi Harian dalam Meningkatkan Produktivitas UMKM Sektor Minuman: Studi Kasus Kang Dawet Kekinian
Keywords:
Production Planning, Productivity, Culinary MSME, Operational Efficiency, Daily Production PlanAbstract
This study examines how daily production planning can improve productivity at Kang Dawet Kekinian, a micro-scale beverage MSME in Medan, Indonesia, which faces demand fluctuations that often result in overstock and understock conditions. The research designs a written Daily Production Plan (DPP) based on a moving average demand forecast and evaluates its role in controlling raw materials and labor time. Using a qualitative single-case study approach, data were collected through semi-structured interviews, non-participant observation, and operational documentation, including purchasing records and daily sales data. The findings indicate that a structured DPP supports more consistent achievement of the daily output target of approximately 100 cups, reduces waste through disciplined stock audits and standardized recipes, and optimizes labor hours by clarifying task sequences. In addition, the study identifies the use of a standby fund as a practical complementary strategy to maintain operational continuity when raw material supplies are low or deliveries are delayed. Overall, the study offers an implementable and low-cost production planning model for culinary MSMEs and highlights managerial steps to enhance operational efficiency under conditions of high demand variability by adapting formal production planning logic to the resource constraints typical of MSMEs, thereby making planning actionable without the need for complex systems.
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Alexopoulos, K., Nikolakis, N., & Xanthakis, E. (2022). Digital transformation of production planning and control in manufacturing SMEs: The mold shop case. Applied Sciences, 12(21). https://doi.org/10.3390/app122110788
Alhikmah, P., Budiharti, N., & Galuh, J. W. H. (2024). Perencanaan kapasitas produksi alen-alen menggunakan metode rough cut capacity planning (RCCP) (studi kasus UMKM Pak Miran). Jurnal Valtech, 7(1), 179–192. https://doi.org/10.36040/valtech.v7i1.9288
Arifa, I., Choiri, A., Wibowo, W., Aminuddin, A., & Panggabean, N. A. (2025). Peran UMKM dalam meningkatkan perekonomian nasional. PESHUM: Jurnal Pendidikan, Sosial dan Humaniora, 4(4), 5376–5385. https://doi.org/10.56799/peshum.v4i4.9530
Ben-Ammar, O., Dolgui, A., Hnaien, F., & Ould-Louly, M. A. (2022). Supply planning and inventory control under lead time uncertainty: A literature review and future directions. IFAC-PapersOnLine, 55(10), 2749–2754. https://doi.org/10.1016/j.ifacol.2022.10.138
Birkmaier, A., Imeri, A., & Reiner, G. (2024). Improving supply chain planning for perishable food: Data-driven implications for waste prevention. Journal of Business Economics, 94(6), 1–36. https://doi.org/10.1007/s11573-024-01191-x
Brozović, D., Jansson, C., & Boers, B. (2025). Strategic flexibility and growth of small and medium-sized enterprises: A study of enablers and barriers. Management Decision, 63(6), 1914–1935. https://doi.org/10.1108/md-05-2022-0577
Cañas, H., Mula, J., Campuzano-Bolarín, F., & Poler, R. (2022). A conceptual framework for smart production planning and control in industry 4.0. Computers & Industrial Engineering, 173, 108659. https://doi.org/10.1016/j.cie.2022.108659
Eunike, A., Setyanto, N. W., Yuniarti, R., Hamdala, I., Lukodono, R. P., & Fanani, A. A. (2021). Perencanaan produksi dan pengendalian persediaan (Edisi revisi). https://books.google.co.id/books/about/Perencanaan_Produksi_dan_Pengendalian_Pe.html
Gioia, D. G., Felizardo, L. K., & Brandimarte, P. (2023). Simulation-based inventory management of perishable products via linear discrete choice models. Computers & Operations Research, 157, 106270. https://doi.org/10.1016/j.cor.2023.106270
Kiymaz, H., Haque, S., & Choudhury, A. A. (2024). Working capital management and firm performance: A comparative analysis of developed and emerging economies. Borsa Istanbul Review, 24(3), 634–642. https://doi.org/10.1016/j.bir.2024.03.004
Masruchiyah, N., Murti, W., & Kurniati, A. (2024). Pemberdayaan sumber daya manusia pada era digital untuk meningkatkan produktivitas kerja UMKM. Jurnal Green Growth dan Manajemen Lingkungan, 14(1), 78–93. https://doi.org/10.21009/jgg.141.06
Millers, M., & Gaile-Sarkane, E. (2021). Management practice in small and medium-sized enterprises: Problems and solutions from the perspective of open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 7(4), 214. https://doi.org/10.3390/joitmc7040214
Minh, N. D. (2023). Toyota’s production efficiency improvement management: Best practice for productivity evaluation and operation improvement. Journal of Advances in Management Research, 20(3), 385–408. https://doi.org/10.1108/jamr-02-2022-0042
Mor, R. S., Bhardwaj, A., Singh, S., & Sachdeva, A. (2019). Productivity gains through standardization of work in a manufacturing company. Journal of Manufacturing Technology Management, 30(6), 899–919. https://doi.org/10.1108/jmtm-07-2017-0151
Mtisi, S. (2022). The qualitative case study research strategy as applied on a rural enterprise development doctoral research project. International Journal of Qualitative Methods, 21. https://doi.org/10.1177/16094069221145849
Panggabean, N. A., Wibowo, W., Fatiha, N., Qomar, M. B., & Ramadhani, B. N. (2025). Pengaruh pertumbuhan ekonomi dan pengangguran terhadap tingkat kemiskinan di Sumatera Utara. J-CEKI: Jurnal Cendekia Ilmiah, 4(4), 1396–1409. https://doi.org/10.56799/jceki.v4i4.8824
Panigrahi, R. R., Shrivastava, A. K., & Kapur, P. K. (2024). Impact of inventory management practices on the operational performances of SMEs: Review and future research directions. International Journal of System Assurance Engineering and Management, 15(5), 1934–1955. https://doi.org/10.1007/s13198-023-02216-4
Panigrahi, R. R., Shrivastava, A. K., & Nudurupati, S. S. (2024). Impact of inventory management on SME performance: A systematic review. International Journal of Productivity and Performance Management, 73(9), 2901–2925. https://doi.org/10.1108/ijppm-08-2023-0428
Rahim, A., Derang, T. W. D., Putriani, P., & Afifah, N. (2025). Analisis komparatif metode moving average dan exponential smoothing untuk peramalan produksi brownies chips pada UMKM Agriku Kota Parepare. Prosiding Seminar Nasional Pembangunan dan Pendidikan Vokasi Pertanian, 6(1), 320–330. https://doi.org/10.47687/snppvp.v6i1.1778
Rahmani, M., Romsdal, A., Sgarbossa, F., Strandhagen, J. O., & Holm, M. (2022). Towards smart production planning and control: A conceptual framework linking planning environment characteristics with the need for smart production planning and control. Annual Reviews in Control, 53, 370–381. https://doi.org/10.1016/j.arcontrol.2022.03.008
Realyvásquez-Vargas, A., Flor-Moltalvo, F. J., Blanco-Fernández, J., Sandoval-Quintanilla, J. D., Jiménez-Macías, E., & García-Alcaraz, J. L. (2019). Implementation of production process standardization: A case study of a publishing company from the SMEs sector. Processes, 7(10). https://doi.org/10.3390/pr7100646
Rodrigues, M., Miguéis, V., Freitas, S., & Machado, T. (2024). Machine learning models for short-term demand forecasting in food catering services: A solution to reduce food waste. Journal of Cleaner Production, 435, 140265. https://doi.org/10.1016/j.jclepro.2023.140265
Silver, E. A., Pyke, D. F., & Thomas, D. J. (2016). Inventory and production management in supply chains (4th ed.). https://doi.org/10.1201/9781315374406
Utari, W., & Hutasuhut, S. (2024). Pengaruh pengembangan UMKM terhadap kesejahteraan masyarakat di Kota Medan. Innovative: Journal of Social Science Research, 4(5), 7645–7652. https://doi.org/10.31004/innovative.v4i5.15283
Wibowo, W., & Choiri, A. (2025). Transformasi digital dalam manajemen sumber daya manusia (SDM): Tren, tantangan, dan prospek masa depan. Jurnal Maritim, 6(2), 75–90. https://doi.org/10.51742/ojsm.v6i2.1456
Widita, A. A., Lechner, A. M., & Widyastuti, D. T. (2024). Spatial patterns and drivers of micro, small and medium-sized enterprises (MSMEs) within and across Indonesian cities: Evidence from highly granular data. Regional Science Policy & Practice, 16(11), 100137. https://doi.org/10.1016/j.rspp.2024.100137
