Article Per Year (5 Year)
p-Index From 2021 - 2026
3.916
P-Index
This Author published in this journals
All Journal Jurnal Informatika Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial IJCIT (Indonesian Journal on Computer and Information Technology) Indonesian Journal on Software Engineering (IJSE) Jurnal Teknik Komputer AMIK BSI Jurnal Pilar Nusa Mandiri JITK (Jurnal Ilmu Pengetahuan dan Komputer) Techno Nusa Mandiri : Journal of Computing and Information Technology JURNAL TEKNOLOGI DAN OPEN SOURCE Journal of Information System, Applied, Management, Accounting and Research EVOLUSI : Jurnal Sains dan Manajemen Jurnal Tekinkom (Teknik Informasi dan Komputer) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Infortech Jurnal Pengabdian Masyarakat Asia Jurnal Sistem Informasi Jurnal AbdiMas Nusa Mandiri Reputasi: Jurnal Rekayasa Perangkat Lunak Simpatik: Jurnal sistem Informasi dan Informatika Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Informatics and Computer Engineering Journal Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Journal of Accounting Information System EVOLUSI : Jurnal Sains dan Manajemen
Ratih Yulia Hayuningtyas
Universitas Bina Sarana Informatika
Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Library & Information Science Mathematics Physics Public Health Social Sciences Other

Published : 41 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 41 Documents
Search

 1   2   3   4   5 
Penerapan Algoritma XGBoost Dalam Menganalisa Keberlanjutan Pelanggan Tour dan Travel Ratih Yulia Hayuningtyas; Wina Yusnaeni; Ida Darwati
Evolusi : Jurnal Sains dan Manajemen Vol. 13 No. 2 (2025): Periode September 2025
Publisher : LPPM Universitas Bina Sarana Informatika Kampus Kabupaten Banyumas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/evolusi.v13i2.9748

Abstract

Customer churn is a term used to describe customer loss in the business world. Customer churn is a major challenge in the business world, impacting every company. One example is the tour and travel industry, the impact of customer churn in tour and travel businesses can include decreased profits and increased operational costs because acquiring tour and travel customers is more expensive than retaining them. Every company has a strategy for customer retention, one of which is implementing machine learning. This study uses public data to determine customer churn using the XGBoost algorithm. Extreme Gradient Boost (XGBoost) works by gradually building a model to improve prediction accuracy. In this study, the XGBoost model works through several stages: data processing, dataset division, algorithm testing, which ultimately results in model accuracy, evaluation, and ROC and AUC curves. The results of this study with the XGBoost model produced an accuracy of 87.7%, precision of 74.4%, recall of 74.4%, F1-Score of 74.4%, and an AUC value of 0.95. In addition, this study also produced an application to predict customers who do not yet have a label
Co-Authors Adnan Labib Hamdani Christian Silaban Defri Arifin Dominggus Jabi Duwi Cahya Putri Buani Fadli Romadhon Trisnanto Hastuti, Regita Tri Ibnu Sina Alafgani Ida Darwati Ida Darwati Ilham Darussalam Ispandi Ispandi Ispandi Linda Marlinda Marlina Marlina Muhammad Aldyanto Bayu Pratama Muhammad Dicky Setyawan Muhammad Nur Alamsyah Muhammad Nur Alamsyah Nia Nuraeni Nia Nuraeni Nia Nuraeni Nia Nuraeni Nurul Hakim Puji Astuti Puji Astuti Retno Sari Retno Sari Retno Sari Retno Sari Retno Sari Rosi Kusuma Serli Sari Hartini Septian Dika Nugraha Siregar, Melita Theo Chostha Ochktavia Wina Yusnaeni