PENERAPAN ALGORITMA FP-GROWTH UNTUK MENGANALISA POLA PEMBELIAN KONSUMEN PADA TOKO PAGARUYUNG DIESEL
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Date
2023-12
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Publisher
Elfitra
Abstract
Pagaruyung Diesel store in Duri City has experienced Growth in both customers and
product variety. The issue at hand is an imbalance in product inventory. Therefore,
decisions need to be made based on the highest sales to efficiently manage inventory and
enhance customer service. In this regard, transaction sales data is utilized to identify
customer purchasing behavior. Data mining technology serves as a valuable tool in
inventory information identification at Pagaruyung Diesel store. This technology employs
pattern matching strategies and algorithms to uncover relationships within the data. One
of the approaches used is the FP-Growth Algorithm, which allows the identification of
common Item sets within the data. In this study, the FP-Growth Algorithm is applied to
analyze purchasing patterns. The aim of this research is to implement the FP-Growth
Algorithm method to analyze purchasing patterns at Pagaruyung Diesel store. The results
are expected to assist in inventory management and decision-making. The research
findings indicate that by using sales data for automotive spare parts from January to June
2022, the FP-Growth Algorithm method produces 5 association Rules with a Minimum
Support of 1% and a Minimum Confidence of 50%. These results demonstrate that the
FP-Growth Algorithm can be effectively applied to analyze purchasing patterns at
Pagaruyung Diesel store.
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Keywords
Data Mining, FP-Growth Algorithm, Purchase Patterns
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