Integrasi forecasting pada rantai pasok manufaktur komponen otomotif Jepang di Indonesia dengan penerapan metode classic dan regresi - Rio Patria; Sumarsono Sudarto (Universitas Mercu Buana, 2020)
The need of spark plugs as a replacement component has a potential demand, especially for a Company from Japan which establish in the last 40 year ago as manufacture of spark plugs in Indonesia. Sales forecast of spark plugs that develop by Company for aftermarket class has big error. It makes a question ‘how to improve the accuracy of forecasting spark plugs in the aftermarket class to reduce losses in the supply chain process’, such as loss due to inventory, production and transportation. In this study, it was found that using ARIMA and MLR methods could increase level of accuracy than current forecasting method by Company. It was found that the increment in forecasting accuracy by using ARIMA and MLR was able to reduce operational costs up to 25.05% per year in overtime costs and 40.21% per year in finished goods inventory costs. In addition, reducing the cost of shipping materials by 24.90% per year, and reducing inventory costs on suppliers by 25.74% per year.