https://matjournals.net/engineering/index.php/JoETSE <p>Journal of Electronics and Telecommunication System Engineering is a peer-reviewed journal in the field of Telecommunication published by the MAT Journals Pvt. Ltd. JoETSE is a print e-journal focused towards the rapid Publication of fundamental research papers on all areas of Electronics and Telecommunication System Engineering. This Journal involves the basic principles of dealing with the Electronic systems and technologies, Network design and protocols, Communication protocols, Fibre optic communication and related technologies, Satellite and Space Communications and emerging trends and challenges in the field of electronics and telecommunication system engineering. The Journal aims to promote high-quality Research, Review articles, and case studies mainly focussed on but not limited to the following Topics Telecommunication Systems, Wireless Communication, signal and image processing, optical communications, navigation systems, Transmission systems, Internet Technologies, Mobile Communications, and Radar Imaging . This Journal involves the comprehensive coverage of all the aspects of Electronics and Telecommunication System Engineering.</p> MAT JOURNALS PRIVATE LIMITED en-US Journal of Electronics and Telecommunication System Engineering https://matjournals.net/engineering/index.php/JoETSE/article/view/4260 <p><em>Customer churn prediction is an important analytics problem in the telecom sector because losing an existing subscriber can reduce recurring revenue and increase the cost of customer acquisition. This paper presents a machine learning-based framework for identifying customers who are likely to discontinue telecom services. The workflow covers data cleaning, duplicate removal, missing-value treatment, categorical encoding, numerical scaling, class-imbalance handling, feature selection, model training, and evaluation on an unseen test set. Five classifiers are considered: Logistic Regression, K-Nearest Neighbor, Support Vector Machine, Random Forest, and gradient boosting using an XGBoost-style model. Special attention is given to telecom variables such as contract type, tenure, monthly charges, technical support, payment method, internet service, online security, and billing behavior. Rather than relying only on accuracy, the framework evaluates precision, recall, F1-score, and confusion matrices so that false alarms and missed churners can be interpreted from a business perspective. The study is structured as an original methodology and implementation framework using a publicly available telecom churn dataset. Numerical results, values, and feature rankings are intentionally left for completion after the actual experiment is executed, avoiding unsupported performance claims. The framework provides a practical basis for early intervention and customer-retention decision support while allowing future integration of explainable artificial intelligence and time-dependent customer behavior.</em></p> BC Hemapriya Prem Kumar BR Roshan R Nishan JN Ranjith Kumar KR Copyright (c) 2026 Journal of Electronics and Telecommunication System Engineering 2026-10-08 2026-10-08 1 14