Publication Date: 2023/07/22
Abstract: In the midst of increasingly innovative and competitive competition, it takes the ability to capture the development of market demand in industries engaged in the manufacturing industry. Maintaining market trust and making consumers loyal to the company is one of the methods so that the company can survive in the midst of competition. The objectives to be achieved from this research are: to analyze the appropriate forecasting method for the demand for Surimi Itoyori products, to analyze the best forecasting method for Surimi Itoyori products, . By using descriptive quantitative method. The results of this study indicate that the Tracking Signal limit for Surimi Itoyori Products has the potential to have a stationary pattern and a trend. From the results of the research, the forecasting methods obtained are Stationary Data with Additive Seasonal Effects, Stationary Data with Multiplicative Seasonal Effects, Holt-Winter's Method for Additive Seasonal Effects, and Holt -Winter's Method for Multiplicative Seasonal Effects meets the Tracking signal limit and can be used to forecast surimi products and the results of the comparison of the smallest MSE value, the smallest MAD and the Tracking Signal limit for Surimi Itoyori Products have obtained the selected forecasting results and 3. In the manufacture of MPS products it is necessary to carry out the second iteration to adjust the master production schedule with the delivery quantity. The large factory capacity compared to the demand for surimi, the potential of the surimi factory can be maximized by producing other products in the form of surimi products besides itoyori, frozen fish, and reprocessing or freezing services without worrying about disrupting the itoyori surimi production process. So furthermore during peak and low seasons surimi can be put to good use by optimizing its production capacity .
Keywords: Component; Surimi Itoyori Products; Forecasting Method; Master Production Schedule (MPS); Request.
DOI: https://doi.org/10.5281/zenodo.8174223
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23JUL2191.pdf
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