PENERAPAN METODE TIME SERIES DALAM FORECASTING PENJUALAN PADA “NASI GORENG BACOT”

Putrajaya, Bagas Adil (2024) PENERAPAN METODE TIME SERIES DALAM FORECASTING PENJUALAN PADA “NASI GORENG BACOT”. Undergraduate thesis, UPN Veteran "Jawa Timur".

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Abstract

The restaurant industry in Indonesia has experienced significant growth, driving the need for data-driven strategies to remain competitive. This study aims to apply and compare time series methods in forecasting sales at "Nasi Goreng Bacot" restaurant. The methods used are Simple Moving Average (SMA), Weighted Moving Average (WMA), and Single Exponential Smoothing (SES), with a focus on sales data from the year 2023. The research results indicate that SMA provides the most accurate predictions, with a Mean Absolute Error (MAE) value of 296.67, Mean Squared Error (MSE) of 129055.6, and Mean Absolute Percentage Error (MAPE) of 3.02%. WMA and SES, although useful in certain data conditions, show higher error rates in this case. This study confirms the effectiveness of SMA in the context of stable and less fluctuating restaurant sales data. With these results, restaurants can plan their inventory of raw materials and workforce more efficiently, reduce waste, and improve customer satisfaction.

Item Type: Thesis (Undergraduate)
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorBrastama Putra, AgungNIDN0024118503UNSPECIFIED
Thesis advisorHadiwiyanti, RizkaNIDN0727078602UNSPECIFIED
Subjects: T Technology > T Technology (General) > T58.6-58.62 Management Information Systems
Depositing User: Bagas Adil Putrajaya
Date Deposited: 23 Jul 2024 08:18
Last Modified: 23 Jul 2024 08:18
URI: https://repository.upnjatim.ac.id/id/eprint/27105

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