ANALISIS PERBANDINGAN METODE MOVING AVERAGE SERTA EXPONENTIAL SMOOTHING MENGGUNAKAN PYTHON PADA SISTEM PERAMALAN (Studi Kasus : PT Sinar Berlian Gemilang)

Alima, Suci Nur (2023) ANALISIS PERBANDINGAN METODE MOVING AVERAGE SERTA EXPONENTIAL SMOOTHING MENGGUNAKAN PYTHON PADA SISTEM PERAMALAN (Studi Kasus : PT Sinar Berlian Gemilang). Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

The thesis is done at PT. Sinar Berlian Gemilang as a company distribution of spare parts for heavy equipment. The problem that arises is the company difficulty forecasting future sales demand and lack of methods in planning stock sales and sales performance. By using Moving Average and Exponential Smoothing methods through actual data, companies can gain insight into sales and demand patterns better decision making. This thesis proposes a solution in the form of sales forecasting system using Python Programming. Moving Method Average and Exponential Smoothing are used to predict sales based on period. Mean Absolute Deviation (MAD) Value for Moving Average 12 periods is 192.93 and for Exponential Smoothing 23 periods is 203.90. The average result of the Tracking Signal value for the Moving Average is 1.88, while for Exponential Smoothing is 0.03

Item Type: Thesis (Undergraduate)
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorKusumantara, Prisa Marga0025118203UNSPECIFIED
Thesis advisorFitri, Anindo Saka0025039303UNSPECIFIED
Subjects: T Technology > T Technology (General)
T Technology > TN Mining engineering. Metallurgy
Divisions: Faculty of Computer Science > Departemen of Information Systems
Depositing User: suci nur alima
Date Deposited: 25 Jul 2023 01:23
Last Modified: 25 Jul 2023 01:23
URI: http://repository.upnjatim.ac.id/id/eprint/16304

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