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Boby Septia Pranata
Budi Darma
Computer Science & IT

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Penerapan Data Mining Algoritma FP-Growth Untuk Persediaan Sparepart Pada Bengkel Motor (Study Kasus Bengkel Sinar Service) Boby Septia Pranata; Dito Putro Utomo
Bulletin of Information Technology (BIT) Vol 1 No 2: Juli 2020
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

The strategy used by motorcycle workshop management is through software applications with information systems to obtain a new innovation. In the process of selling goods, it is expected to provide benefits for those who use information technology because it can improve sales quality by providing services and recommendations to sellers and buyers. can even provide promotions. For this reason, the application of the association rules analysis application was developed in finding patterns of the combination of relationships between item-sets and for processing data on the accumulation of sales of workshop tools so far unknown for use so that the accumulated data was mined and information extracted and extracted information which is useful or called data mining is then extracted and interpreted by the pattern of sales trend of tools to improve services that are often sold using the FP-Growth algorithm. FP-Growth is an alternative algorithm that can be used to determine the set of data that most often appears (Frequent Item Set) in a set of data and uses the concept of building trees in the search for Frequent Item Sets. This research was conducted by observing the variable data of equipment repairing equipment to improve service.
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