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Bulk olein is one of the products produced by Palm Oil Processing Company. Bulk cooking oil controls 75 percent of the production market share in Indonesia and about 77.5 percent of households in Indonesia use bulk cooking oil because the price is cheaper than packaged cooking oil. Demand for olein in the future is predicted to be continued to increase, so it is necessary to estimate future sales so that production activities become more effective and efficient. The method used in this study is the double moving average (DMA), which is one of the forecasting methods with data that has a trend. The calculation will be done by comparing the result of 3 moving, 4 moving and 5 moving. Forecasting error is calculated using mean absolute percentage error (MAPE). The calculation results show that the average MAPE from DMA with 5 moving has the smallest value. To verify these results, an analysis of the processed data was carried out, namely looking for data with the furthest distance from the linear line, namely t3 data and t7 data. The data is omitted in data processing and then the MAPE error value is recalculated. The results obtained are that DMA with 3 moving results have the smallest error, which is 11.863 percent. For this reason, the chosen forecasting calculation is a double moving average with 3 moving.

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The need for high-quality crumb rubber in West Sumatra tends to increase. However, the amount and quality of rubber from suppliers belong to weak caused by the bad monitoring systems, the supply cannot be met properly, and there is a lot of shrinkage in rubbers purchased by the company. Therefore this research was carried by implementing the Decision Support System (DSS) which was expected to help facilitate supplier data searches and evaluate the supplier's performance. The first stage in this research was designing DSS included the use of Unified Modeling Language (UML) diagram and database design. Next, built an applicable software using Personal Home Page (PHP), My Structured Query Language (MySQL), and Apache. An advantage of DSS designed was to accommodate differences and changes in rubber supplier assessment criteria according to the consideration of each crumb rubber industry in West Sumatra. There were 3 of 11 main crumb rubber criteria assessed. The results of these 3 criteria were obtained highest weight, namely Dryness (0.18), cleanliness (0.15), and consistency of quality (0.10). While the previous performance obtained the lowest weight (0.05). This meant that the criteria of dryness, cleanliness, and consistency of quality, will be the main considerations for companies in ranking and evaluating suppliers who work with companies.

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