PREDIKSI STATUS PESANAN MENGGUNAKAN METODE CLASSIFICATION C.45 PADA TOKO STUFTECH.ID

• FADLI RAHMAN LATARISSA
• MUHAMAD ARIEF FIRDAUS
• YANUAR DZAKY PRADANA
• 2025

---

The increase in transactions on e-commerce platforms such as Shopeenecessitates the development of accurate order status predictionsystemstooptimizeservicesandreduceordercancellationsanddelays.This study aims to build a classification model for predicting orderstatus (completed or canceled) at StufTech.Id store using the C4.5algorithm. The dataset consists of transaction attributes such aspayment method, shipping location category, and shipping cost. Theclassification process was conducted using RapidMiner throughpreprocessing, decision tree generation, and model evaluation stages.The analysis shows that the “Shipping Region Category” attribute hasthe highest information gain and was selected as the root node. Theresulting model achieved an accuracy of 86%, with 100% recall forcompleted orders but only 6.67% for canceled ones. These findingsindicate that the C4.5 algorithm is effective in predicting successfultransactions but requires improvement in identifying potentialcancellations.Implementingthismodelcanhelpbusinessownersmakeproactive operational decisions.

• C4.5 algorithm
• classification
• Shopee
• order prediction
• e-commerce

https://repository.bsi.ac.id/repo/74674/PREDIKSI-STATUS-PESANAN-MENGGUNAKAN-METODE---CLASSIFICATION-C.45-PADA-TOKO-STUFTECH.ID
Anda dapat membaca file tugas akhir ini di repository.