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All Journal International Journal of Electrical and Computer Engineering Journal of Applied Science, Engineering, Technology, and Education
Awad, Mohammed
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Other

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An efficient enhanced k-means clustering algorithm for best offer prediction in telecom Fraihat, Malak; Fraihat, Salam; Awad, Mohammed; AlKasassbeh, Mouhammd
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2931-2943

Abstract

Telecom companies usually offer several rate plans or bundles to satisfy the customers’ different needs. Finding and recommending the best offer that perfectly matches the customer’s needs is crucial in maintaining customer loyalty and the company’s revenue in the long run. This paper presents an effective method of detecting a group of customers who have the potential to upgrade their telecom package. The used data is an actual dataset extracted from call detail records (CDRs) of a telecom operator. The method utilizes an enhanced k-means clustering model based on customer profiling. The results show that the proposed k-means-based clustering algorithm more effectively identifies potential customers willing to upgrade to a higher tier package compared to the traditional k-means algorithm. Our results showed that our proposed clustering model accuracy was over 90%, while the traditional k-means accuracy was under 70%.
Digital Resilience in War-Affected Contexts: An MIS Framework for Restoring ICT Learning and Freelancing Capacity Awad, Mohammed
Journal of Applied Science, Engineering, Technology, and Education Vol. 8 No. 1 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci4545

Abstract

ICT learning systems in war-affected regions face continuous disruption caused by damaged infrastructure, unstable connectivity, mobility restrictions, and psychological stress. These conditions interrupt digital-skills development and limit access to online freelancing opportunities. This paper proposes a Digital Resilience MIS Framework designed to restore and sustain ICT learning during active conflict. The framework is developed from two ICT training programs implemented in Gaza during the 2025 war, both of which operated throughout severe instability. Analysis of program documentation shows that learning continuity depended on five interconnected pillars: resilient infrastructure; adaptable instructional workflows; structured monitoring and information flow; human-centered psychosocial support; and coordinated organizational decision-making. When combined, these elements enabled the programs to maintain attendance, progress through technical content, and complete practical projects despite external disruptions. The framework offers a practical model for institutions seeking to preserve digital learning and freelance-readiness in fragile settings and contributes to MIS scholarship by demonstrating how resilience principles can be operationalized in active conflict environments.
Co-Authors AlKasassbeh, Mouhammd Fraihat, Malak Fraihat, Salam