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All Journal IJISCS (International Journal of Information System and Computer Science)
Dessry Maeye Khelany
Information System, ITBA Dian Cipta Cendikia Kotabumi, North Lampung
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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THE C45 ALGORITHM METHOD IN PREDICTING DAMAGED GOODS CASE STUDY: SEMULI RAYA INDOMARET SHOP Dessry Maeye Khelany; Nurmayanti Nurmayanti; Sigit Mintoro
IJISCS (International Journal of Information System and Computer Science) Vol 7, No 2 (2023): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v7i2.1515

Abstract

Indomaret Semuli Raya is a company that competes in the industrial world. In the industrial world, the quality of products marketed is an important indicator for Indomaret Semuli Raya to be able to stand during intense competition from other companies. Product quality is certainly the thing that attracts consumers. In dealing with problems that occur in the company, it must make the right decision in determining the product strategy to be sold, to get the right decision, sufficient item data is needed to be analyzed. This research raises the issue of whether or not goods are worth selling in the category of damaged goods at Indomaret Semuli Raya in the period from February to March 2023. Data mining is used in this study, specifically the C4.5 Algorithm Method. The author chose the C4.5 Algorithm method because it can be used to determine whether or not damaged goods are unfit for sale. Algorithm C4.5 will determine damaged goods based on the attributes that become the standard for the eligibility of goods. The attributes referred to in this study are Overweight, Brackage, Sell by, and Moisture and temperature. The aftereffects of manual computations by means of Microsoft Succeed utilizing the C4.5 Calculation have a precision of 90.00% then demonstrated by the RapidMiner application with an exactness of 90.00%.
Co-Authors Nurmayanti Nurmayanti Sigit Mintoro