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All Journal Journal of Computer Networks, Architecture and High Performance Computing SOROT: Jurnal Pengabdian Kepada Masyarakat
Asyhari, Moch Yusuf
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Engineering Mechanical Engineering Other

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Implementation of Machine Learning Models for Predicting Internet Service Provider Customer Churn Asyhari, Moch Yusuf; Susanti, Pratiwi; Yunitasari, Yessi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 4 (2025): Articles Research October 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i4.7012

Abstract

The telecommunications industry faces an extremely high level of competition, where the phenomenon of customer churn presents a significant challenge due to its impact on revenue decline and increased costs associated with acquiring new customers. This study aims to develop a churn prediction model using the Decision Tree algorithm and implement it in a web-based application to support customer retention strategies. The CRISP-DM methodology is employed, covering Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. Experimental results show that the Decision Tree algorithm demonstrates strong performance in identifying non-churn customers, with a precision of 0.82, a recall of 0.91, and an F1-score of 0.86. However, its performance on the churn class remains limited, with a precision of 0.63, a recall of 0.44, and an F1-score of 0.52, highlighting the importance of addressing imbalanced data distribution to preserve existing data. The model underwent Learning Curve and Validation Curve analysis. The Learning Curve indicates a relatively stable model with a small gap, suggesting good generalization. The Validation Curve reveals that optimal performance is achieved at a moderate tree depth, avoiding the risk of overfitting at greater depths. Nevertheless, the main advantage of the Decision Tree is its interpretability, which highlights significant factors such as contract type, subscription duration, and additional services. The integration of the model into a web-based application also provides practical benefits through rapid churn risk monitoring, supporting the company’s strategic decision-making.
Sosialisasi dan Pengembangan Situs Web di Madrasah Aliyah Ma’arif 1 Ponorogo Asyhari, Moch Yusuf; Aria Bima, Alim Citra; Yunitasari, Yessi; Cahyono Putro, Moh. Rizal Bagus; Cahyo, Wahyu Nur
SOROT : Jurnal Pengabdian Kepada Masyarakat Vol 3 No 2 (2024): Juli
Publisher : Fakultas Teknik dan Ilmu Komputer (FASTIKOM) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/sorot.v3i2.7507

Abstract

Madrasah Aliyah Ma'arif 1 Ponorogo has introduced website development as a response to developments in information technology. This website is an important need in strengthening communication with students, parents and the community in today's digital era. The main problems faced are low access to school information and lack of interaction with the wider community. The solution to overcome this, website development facilitates easy access to information such as school profiles, academic programs, extracurricular activities, student achievements, as well as religious and social activities. The development method involves needs analysis, structured planning, comprehensive material collection, design and development, implementation, user training and outreach, and regular evaluation. The main goal is to strengthen the school's image at local and national levels, as well as increase community involvement in supporting modern and efficient education. This activity contributes to the development of information technology-based education, with a focus on increasing information accessibility and interaction of various lines in the context of Islamic education.
Co-Authors Aria Bima, Alim Citra Cahyo, Wahyu Nur Cahyono Putro, Moh. Rizal Bagus Susanti, Pratiwi Yunitasari, Yessi