Nugroho, Daffa Agung (2025) Implementasi Data Mining Untuk Prediksi Penjualan Produk Kerajinan Prasegi Art Dengan Algoritma C4.5. Undergraduate thesis, Politeknik Negeri Jember.
![[img]](https://sipora.polije.ac.id/style/images/fileicons/text.png) |
Text (Abstract)
Abstract.pdf - Submitted Version Available under License Creative Commons Attribution Share Alike. Download (174kB) |
|
Text (Bab 1 Pendahuluan)
Bab 1 Pendahuluan.pdf - Submitted Version Available under License Creative Commons Attribution Share Alike. Download (184kB) |
|
Text (Daftar Pustaka)
Daftar Pustaka.pdf - Submitted Version Available under License Creative Commons Attribution Share Alike. Download (180kB) |
|
Text (Laporan Lengkap)
SKRIPSI - DAFFA AGUNG NUGROHO.pdf - Submitted Version Restricted to Registered users only Download (3MB) | Request a copy |
Abstract
Micro, Small, and Medium Enterprises (MSMEs) like Prasegi Art require data-driven strategies to identify best-selling products in order to improve sales effectiveness on e-commerce platforms. This study aims to design and implement a product popularity classification system for Prasegi Art’s handicraft products using the C4.5 algorithm. The system development method used is the Waterfall model, which includes the stages of requirements analysis, design, implementation, and testing. This study utilizes historical transaction data aggregated to obtain the total sales of each product. The C4.5 model was built using three categorized input attributes: product category name, product type ('Standard' or 'Custom'), and price range ('Low', 'Medium', 'High'). The goal of this model is to classify products into one of three popularity classes: 'Not Popular' (total sales < 5 units), 'Moderately Popular' (total sales 5–20 units), or 'Highly Popular' (total sales > 20 units). The result of this study is a functional system built with Laravel that can automatically classify products, with the C4.5 model achieving an accuracy of 36.36% on test data. Although the model's performance is relatively low, the system provides a foundational step toward data-driven decision-making for production and marketing strategies based on historical sales data
| Item Type: | Thesis (Undergraduate) | ||||||
|---|---|---|---|---|---|---|---|
| Contributors: |
|
||||||
| Uncontrolled Keywords: | data mining, C4.5 algorithm, product classification, e-commerce, MSMEs, Prasegi Art, product popularity | ||||||
| Subjects: | 100 - Rumpun Matematika dan Ilmu Pengetahuan Alam (MIPA) > 120 - Matematika > 123 - Ilmu Komputer 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 458 - Teknik Informatika 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 461 - Sistem Informasi 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 463 - Teknik Perangkat Lunak |
||||||
| Divisions: | Jurusan Teknologi Informasi > Prodi D4 Teknik Informatika (Sidoarjo) > Tugas Akhir | ||||||
| Depositing User: | Daffa Agung Nugroho | ||||||
| Date Deposited: | 06 Aug 2025 04:18 | ||||||
| Last Modified: | 06 Aug 2025 04:18 | ||||||
| URI: | https://sipora.polije.ac.id/id/eprint/45402 |
Actions (login required)
 |
View Item |
