Published date: Oct 08 2024

Journal Title: KnE Social Sciences

Issue title: 4th International Conference in Social Science (4th ICONISS): Governance and Poverty Alleviation

Pages: 312–321

DOI: 10.18502/kss.v9i27.17115

Rahmadini Payla Juarsarahmadinipayla@lecturer.unri.ac.idDepartment of Agricultural Technology, Universitas Riau, Pekanbaru

Mhd. Andry KurniawanDepartment of Agricultural Technology, Universitas Riau, Pekanbaru

Ariandini SimalangoDepartment of Agroindustrial Technology, Universitas Riau, Pekanbaru

Shiva Adinda FirdausDepartment of Agroindustrial Technology, Universitas Riau, Pekanbaru

Yellow noodle SMEs face the challenge of aligning their workforce with the fluctuating customer demand. Addressing this issue involves scaling up production staffing during peak yellow noodle demand. This study aimed to determine when and how much production labor should be added. Workforce expansion occurred through contractual arrangements during demand surges. This study used the K-Means clustering method to determine demand clusters. Each cluster underwent detailed analysis to calculate the precise number of required production workers. The study used the noodle sales in 2021–2022. Results showed that yellow noodle SMEs had eight permanent workers. Demand clusters were categorized into three classes. High-demand periods were observed in May and December, while moderate demand occurred in January, February, March, April, June, July, and August. September, October, and November constituted the low-demand cluster. Based on these findings, the study recommended adding one worker during high-demand and moderate-demand periods to maintain operational efficiency. Remarkably, no workforce additions were advised during the low-demand phase to optimize resource allocation and cost-effectiveness. In summary, this research addresses labor management challenges for yellow noodle SMEs. Leveraging data-driven approaches and cluster analysis offers SMEs a strategic framework to enhance workforce planning thereby improving operational efficiency and cost-effectiveness.

Keywords: yellow noodle SMEs, workforce demand clustering, operational efficiency

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