Data Analisis Permintaan Barang dengan Metode Peramalan:

Fivtatianti Hendajani; Ire Puspa Wardhani; Susi Widayati; Soegijanto Soegijanto

doi:10.37366/ekomabis.v3i02.254

Fivtatianti Hendajani STMIK Jakarta STI&K
Ire Puspa Wardhani STMIK Jakarta STI&K
Susi Widayati STMIK Jakarta STI&K
Soegijanto Soegijanto STMIK Jakarta STI&K

DOI: https://doi.org/10.37366/ekomabis.v3i02.254

Keywords: Data Analysis, Forecasting Methods, Demand

Abstract

Di situasi saat ini dimana era pandemic operasional perusahaan berjalan dengan kekuatan organisasi dengan para pelaku manajemen yang berpikir keras bagaimana mengelola permintaan serta kebutuhan dan memasok kebutuhan kepada para pelanggannya. Penulisan artikel ini membahas tentang pengelolaan manajemen perusahaan dengan menggunakan metode peramalan permintaan dalam memenuhi permintaan para intermiten produk suku cadang pada sebuah perusahaan otomotif, dengan sebuah penelitian permintaan intermiten perusahaan yang menunjukkan pola fluktuatif, adanya permintaan dalam jangka waktu tertentu, dan penelitian ini menguji 2 metode peramalan dalam memprediksi permintaan suku cadang yaitu metode Metode ABC, Simple Exponential Smoothing (SES) dan Moving Average Exponential Smoothing dengan menggunakan data permintaan 2017-2020 untuk meramalkan permintaan pada tahun 2021. Kinerja metode peramalan ditentukan berdasarkan mean squared error, dan hasil penelitian ini menunjukkan bahwa penggunaan metode Simple Exponential Smoothing memiliki performansi yang paling baik. Tujuan utama dari penelitian ini adalah untuk membandingkan dan memilih metode peramalan terbaik untuk memprediksi kebutuhan dan permintaan kebutuhan suku cadang perusahaan.

In the current situation where the pandemic era has caused many companies to experience crises, the company's operational activities are carried out with organizational strength that makes management actors think hard in managing the needs and supplying the needs of their customers. This study discusses the management of the company by using the demand forecasting method in meeting the demand for intermittent spare parts products in an automotive company. In this study, the company's intermittent demand trend shows a fluctuating pattern with demand within a certain period of time. This study examines 2 forecasting methods in predicting the demand for spare parts, namely ABC analysis, the Simple Exponential Smoothing (SES) method and the Moving Average Exponential Smoothing using 2017-2020 demand data to forecast demand in 2021. The performance of the forecasting method is determined based on the mean squared error, and the research results This shows that the use of the Simple Exponential Smoothing method has the best performance. The main purpose of this study is to compare and choose the best forecasting method to predict the needs and demands of the company's spare parts needs

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Data Analisis Permintaan Barang dengan Metode Peramalan

Data Analysis for Demand Parts with Forecasting Method

Abstract

References