SAPUTRA, INDRA (2019) ANALISIS OPTIMALISASI PENGENDALIAN PERSEDIAAN SUB-MATERIAL DAN FORECASTING DALAM UPAYA PENURUNAN PROVISI DENGAN METODE ECONOMIC ORDER QUANTITY (EOQ) DAN MODEL TIME SERIES PADA PT. KATEXINDO CITRAMANDIRI. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
This research aims to analyze optimization of sub-material inventory control and forecasting in order to reduce provision in PT. Katexindo Citramandiri. The highest sub-material provision comes from label, button and polybag. Major factors of causing provision are foreasting error and Minimum Order Quantity (MOQ). This research methods used time series model and Economic Order Quantity (EOQ) with Microsoft Excel for tools. Forecasting analysis by time series model will compare result of 5 model such as moving average, exponential smoothing, holt’s model, trend projection,and winter’s model. Descriptive Quantitative used as a design to analyze the research. The result of this research shows that Exponential Smoothing model is more suitable for brand X with MAD 858,33, MSE 1237826, and MAPE 36,55%. Trend Projection model analysis is more suitable for brand Y with MAD 858, MSE 1237826, MAPE 36,55%. With same model, brand Z shows result with MAD 69, MSE 6530,024 and MAPE 28,53%. The contribution of time series model that can reduce provision of forecast error is Rp. 46.226.445 or 50,64%. EOQ optimization in brand A, B, C shows 2 conditions where EOQ = 0 and EOQ > 0. The contribution of EOQ that can reduce provision of MOQ issue where EOQ = 0 is Rp.91.270.607 or 94,58%. The contribution of EOQ that can reduce provision of MOQ issue where EOQ > 0 is Rp.67.258.028 or 69,70%. Keyword: EOQ, Time Series Model, MOQ, Provision, Forecasting, Moving Average, Exponential Smoothing, Holt’s Model, Trend Projection, Winter’s model, MAD, MSE, MAPE. Penelitian ini bertujuan untuk menganalisis optimalisasi pengendalian persediaan sub-material dan forecasting dalam upaya penurunan provisi pada PT. Katexindo Citramandiri. Provisi persediaan sub-material tertinggi terdiri dari label, button dan polybag. Faktor penyebab provisi terbesar berasal dari kesalahan peramalan dan Minimum Order Quantity (MOQ). Metode yang digunakan pada penelitian ini adalah model time series pada peramalan dan Economic Order Quantity (EOQ) dengan alat analisis Microsoft Excel. Analisis peramalan dengan model time series dilakukan dengan perbandingan 5 metode yaitu moving average, exponential smoothing, holt’s model, trend projection, dan winter’s model. Desain yang digunakan pada penelitian ini adalah deskriptif kuantitatif. Hasil penelitian ini menunjukkan bahwa analisis model Exponential Smoothing lebih cocok diterapkan pada merek X yang menghasilkan nilai MAD 858,33, MSE 1237826, dan MAPE 36,55%. Analisis model Trend Projection lebih cocok diterapkan pada merek Y menghasilkan nilai MAD 858, MSE 1237826, MAPE 36,55%. Dengan model yang sama merek Z menghasilkan nilai MAD 69, MSE 6530,024 dan MAPE 28,53%. Kontribusi provisi kesalahan peramalan yang dapat diturunkan oleh analisis model time series sebesar Rp. 46.226.445 atau 50,64% Hasil optimalisasi EOQ pada merek A, B, C menghasilkan dua kondisi EOQ = 0 dan EOQ > 0. Kontribusi provisi MOQ yang dapat diturunkan jika EOQ = 0 sebesar Rp.91.270.607 atau 94,58%. Kontribusi provisi MOQ yang dapat diturunkan jika EOQ > 0 sebesar Rp.67.258.028 atau 69,70%. Kata Kunci: EOQ, Model Time Series, MOQ, Provisi, Forecasting, Moving Average, Exponential Smoothing, Holt’s Model, Trend Projection, Winter’s model, MAD, MSE, MAPE.
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