Saifudin, Muhamad Arif (2024) Implementasi Algoritma Asosiasi FP-Growth dan Algoritma Klasifikasi K-Means Terhadap Pola Pembelian Konsumen di Marketplace Shopee. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
Online shops are an alternative that is easier and more practical in transactions which is one of the impacts of technological and internet developments. Currently, many consumers prefer shopping or transactions online, which has many advantages, one of which is the Shopee marketplace. Shopee is one of the most visited e-commerce during the 2020 period. As the month of Ramadan approaches Idul Fitri, many consumers are looking for various Muslim fashion products or koko clothes. The need for Muslim clothing or koko clothes increases along with this moment. Pusatbusanamuslim1 is an online shop in the Shopee marketplace that sells various kinds of koko clothes or Muslim clothing. They must understand consumer purchasing patterns to optimize their sales so they can compete with other shops. Therefore, the K-Means Classification algorithm and the FP-Growth Association are used to analyze consumer purchasing patterns in the Shopee marketplace. The main aim of implementing these two methods is to produce product recommendations and customer segmentation. In implementing the K-Means Classification algorithm using the LRFM model for customer segmentation, the most optimal number of Clusters is then determined using the Elbow method, the results of which will later be labeled in the results of customer segmentation using the LRFM model. Meanwhile, to implement the FP-Growth Association algorithm, an FP-Tree will be built and the association rules will be searched with predetermined minimum support and minimum confidence values. From the test results with K-Means, an accuracy rate of 56% was obtained from 3 clusters (Cluster 0, Cluster 1, and Cluster 2) with Cluster 2 being the best cluster resulting from customer segmentation using the LRFM model. Meanwhile, from the results of implementing the FP-Growth algorithm, several association rules were obtained, including that Nibras Sarimbit Chesa Brown Couple is often purchased if the customer buys Nibras Sarimbit 70 Brown with a minimum support value of 0.50% and a lift ratio value of 4.6%. The dataset used is 349 product sales transaction data. Keywords: K-Means, FP-Growth, Pattern Analysis, Shopee, LRFM, FP-Tree
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | T Technology > T Technology (General) | ||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | Muhamad Arif Saifudin | ||||||||||||
| Date Deposited: | 19 Jan 2024 08:34 | ||||||||||||
| Last Modified: | 19 Jan 2024 08:34 | ||||||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/20259 |
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