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All Journal Jurnal Ilmiah Kursor Knowledge Engineering and Data Science Indonesian Journal of Data and Science Innovation in Research of Informatics (INNOVATICS) Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Masyarakat Bangsa
Admojo, Fadhila Tangguh
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PCA-counseled k-means and k-medoids with dimension reduction for improved in determining optimal aid clustering Jauhari, Achmad; Suzanti, Ika Oktavia; Anamisa, Devie Rosa; Admojo, Fadhila Tangguh
Jurnal Ilmiah Kursor Vol. 13 No. 1 (2025)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v13i1.460

Abstract

Assuring effective allocation requires targeted distribution of aid, which makes aid clustering a crucial component. For the purpose of using data-driven segmentation based on important characteristics to determine effective help targeting, accuracy in clustering is essential. The study explores the combination of Principal ComponentAnalysis (PCA), k-means, and k-medoids to enhance aid clusters, with the goal ofincreasing aid distribution accuracy and efficiency. The information gathered consists of 1600 records with 13 attributes. In order to standardized the data having two processes in it, preprocessing is first applied. When used with PCA, it makes measuring variance easier and preserves 80% of the variation by choosing five components. Thenumber of clusters may be determined with the use of PCA, k-medoids, and the k-means approach. Greater PCA-k-means silhouette coefficients, which indicate betterclustering ability, are highlighted by comparative analysis. This analysis shows thatPCA-k-means is an effective technique for creating accurate and unique clusters withina data set's structure.The clustering results using the PCA-k-means algorithm have produced the greatest accuracy in the silhouette score of 0.49 and the DBI score is 0.84.
Development of Mobile Quran App with Screen Time Monitoring Using DRM, Agile, and Sus-Use Testing Abdulhafidz, Yahya; Zaky, Umar; Admojo, Fadhila Tangguh
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 6 (2025): JUTIF Volume 6, Number 6, Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.6.5398

Abstract

The rapid growth of mobile applications has changed user behavior in the digital age, including how individuals interact with religious content. However, excessive use of social media has led to behavioral problems such as doom scrolling, zombie scrolling, and digital addiction, phenomena collectively known as “brain rot,” which negatively impact cognitive, emotional, and spiritual well-being. This study aims to develop and evaluate Quran Break, a mobile Quran application that integrates screen time monitoring as a digital behavior intervention to encourage users to stop scrolling and engage in reading the Quran. The methodology applies the Design Research Methodology (DRM) through four iterative stages, supported by an Agile development model with short, adaptive sprints that enable continuous feedback and improvement. 18 participants were involved in usability testing using the System Usability Scale (SUS) and the Usability, Satisfaction, Ease of Learning, and Ease of Use (USE) questionnaire. The results showed that the application achieved an average SUS score of 75 (Good) and a USE score of 87.7% (Very Good), indicating that Quran Break is effective, useful, and easy to use. This discovery contributes to the fields of Religious Informatics and Human-Computer Interaction (HCI) by integrating persuasive technology into faith-based digital systems, supporting digital well-being, and promoting a balanced interaction between technology use and spiritual activities.
Co-Authors Abdulhafidz, Yahya Achmad Jauhari, Achmad Ahsanawati Aziz, Huzain Devie Rosa Anamisa Fahmi Ajismanto Guntoro Barovih, Guntoro Hamada Zein Huzain Azis Ika Oktavia Suzanti Jabir, Siti Rahma Lajis, Adidah Manga’, Abdul Rachman Mualfah, Desti Muhammad Innuddin Nasir, Haidawati Naswin, Ahmad Nurul Rismayanti Radhitya, Made Leo Rezania Agramanisti Azdy, Rezania Agramanisti Salim, Yulita Saputri, Nurul Adha Oktarini Slamet Risnanto Syafie, Lukman Umar Zaky Utami, Aulia Putri Windiawati, Ai Wulan Yudha Islami Sulistya