ANALISIS PERENCANAAN PRODUKSI GUNA MENGOPTIMALKAN BIAYA PRODUKSI DENGAN METODE AGGREGATE PLANNING DI PT. PUTRA BUNGSU

PRATAMA, MUHAMMAD YUDI (2023) ANALISIS PERENCANAAN PRODUKSI GUNA MENGOPTIMALKAN BIAYA PRODUKSI DENGAN METODE AGGREGATE PLANNING DI PT. PUTRA BUNGSU. Skripsi thesis, Fakultas Teknik dan Ilmu Komputer Teknik Industri.

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Abstract

Muhammad Yudi Pratama, 2023 " PRODUCTION PLANNING ANALYSIS TO OPTIMIZE PRODUCTION COSTS WITH THE AGGREGATE PLANNING METHOD AT PT. YOUNGEST SON". Industrial engineering thesis report, Faculty of Engineering and Computer Science, Pancasakti University, Tegal 2023. The primary objective of this investigation is to assess the projected production demand for the upcoming year. This forecast will serve as a foundational basis for managerial decision-making within the company to ascertain the most suitable course of action. In tandem, the utilization of aggregate planning aims to pinpoint an operational approach for production that optimizes efficiency and effectiveness, thereby aligning production with the stipulated plans and consequently bolstering company revenues. The research encompassed the evaluation of three distinct techniques: the simple moving average method, the weighted moving average method, and the exponential smoothing method. From the study's findings, it can be deduced that the exponential smoothing forecast technique, characterized by an alpha coefficient of 0.50 and exhibiting a Mean Absolute Percentage Error (MAPE) of 54.57%, was chosen as the preferred forecasting method for the period spanning May 2023 to April 2024. In conjunction, the adopted aggregate planning strategies encompass the Power control method, Overtime method, and Mixed method. Throughout the research conducted at PT. Youngest Son, during the period extending from May 2023 to April 2024, the overtime method emerged as the most advantageous strategy. This approach demonstrated superior efficiency and effectiveness when compared to the alternatives, notably yielding an optimal total cost of Rp. 1,345,000,000,-. Keywords : simple moving average, weighted moving average and exponential smoothing method.

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