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All Journal Jurnal Terapan Abdimas JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Sains dan Informatika Journal of Computer Networks, Architecture and High Performance Computing Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Bulletin of Information Technology (BIT) Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Jurnal Sains dan Teknologi SATIN - Sains dan Teknologi Informasi Ahsana: Jurnal Penelitian dan Pengabdian kepada Masyarakat Jurnal Imiah Pengabdian Pada Masyarakat (JIPM) Jurnal Teknik Informatika dan Teknologi Informasi
Pratiwi Susanti
Program Studi Informatika, Fakultas Informatika, Universitas PGRI Madiun
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Veterinary Other

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Pemanfaatan Metode TOPSIS dalam Menentukan Rekomendasi Laptop Unggulan di Marketplace Tokopedia Pratiwi Susanti; Saifulloh Saifulloh; Alim Citra Aria Bima; Muh Nur Lutfi Aziz; Latjuba Sofyana STT
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 5 No. 1 (2025): April: Jurnal Teknik Informatika dan Teknologi Informasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jutiti.v5i1.5357

Abstract

The increasing public demand for laptop devices, particularly through marketplace platforms like Tokopedia, results in challenges when selecting a laptop that meets users' needs and preferences. Explore the key laptop specifications that are most important to consumers, such as battery life, RAM, and storage options. Discuss current market trends in laptop sales, including the most popular brands and models among users on platforms like Tokopedia. Highlight the importance of user reviews and testimonials in guiding potential buyers toward their ideal laptop choice. Provide tips for effective comparison shopping on marketplace platforms to help users narrow down their options. Analyze how different consumer preferences (e.g., gaming vs. productivity) influence the types of laptops that are in demand. This study aims to build a Decision Support System (DSS) for selecting the best laptop using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The study was conducted by identifying the main criteria, such as price, RAM, CPU, memory, and dimensions of the laptop, which were then used in the TOPSIS calculation process to determine the best alternative from 15 laptop choices. The results of the study show that the TOPSIS method is able to provide accurate and swift recommendations in choosing a laptop based on user preferences. We implement the system as a website, enabling users to input their preferences and receive automatic laptop recommendations. We expect this study to assist users in making laptop purchasing decisions more effectively and efficiently
Implementation of Machine Learning Models for Predicting Internet Service Provider Customer Churn Moch Yusuf Asyhari; Pratiwi Susanti; Yessi Yunitasari
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.
Pelatihan Media Digital Interaktif Blooket Integrasi AI dalam Pembelajaran Modern di SD Yessi Yunitasari; Inung Diah Kurniawati; Yoga Prisma Yuda; Pratiwi Susanti
Jurnal Imiah Pengabdian Pada Masyarakat (JIPM) Vol 4 No 1 (2026): Juli - September
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In the era of 21st-century education, digital literacy has emerged as a crucial competency that extends beyond basic technical skills to encompass critical thinking, information evaluation, and digital ethics. However, educators face significant challenges in maintaining student engagement amidst high levels of digital distraction. This article describes the implementation of training designed to strengthen digital literacy in instruction through the integration of AI and the interactive platform Blooket. The training aimed to enhance educators' competence in utilizing digital technology effectively, creatively, and pedagogically. A participatory training approach was employed, combining lectures, demonstrations, hands-on practice, and post-training evaluation. The results indicate an improvement in participants' understanding of digital literacy, their ability to integrate AI into instruction, and their skills in using Blooket as an interactive and engaging tool for learning assessment. Furthermore, participants demonstrated increased motivation to develop technology-based instruction. Thus, the training proved effective in enhancing teachers' digital competencies and fostering instructional innovation in the era of digital transformation
Co-Authors Abdul Rozaq Ahmad, Khairul Adila Aldida, Jovanza Denis Alim Citra Aria Bima Aminuyati Astuti, Anggun Yuli Eka, Muhammad Rendy Fatim Nugrahati Jayadi, Puguh Juwari Juwari Kurniawati, Inung Diah Kurniawati, Inung Diah Latjuba Sofyana STT Moch Yusuf Asyhari Moch. Yusuf Asyari Muh Nur Lutfi Aziz Nasrul Rofiah Hidayati, Nasrul Rofiah Nugrahanti, Fatim Puguh Jayadi Putrian, Aurisha Lutvinda R. Bekti Kiswardianta, R. Bekti Riza Akhsani Setyo Prayoga Saifulloh Saifulloh saifulloh Saifulloh, saifulloh Shamsuddin, Norin Rahayu Syamsiar, Syamsiar Tajuddin, Taniza Yessi Yunitasari Yoga Prisma Yuda