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All Journal snimed Jurnal Teknoin TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Sistemasi: Jurnal Sistem Informasi JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jiko (Jurnal Informatika dan komputer) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Riset Informatika EDUMATIC: Jurnal Pendidikan Informatika bit-Tech Jurnal Teknologi Dan Sistem Informasi Bisnis JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Automata Jurnal Ilmiah Intech : Information Technology Journal of UMUS International Journal of Social Science and Religion (IJSSR) J-SAKTI (Jurnal Sains Komputer dan Informatika) INOVTEK Polbeng - Seri Informatika
Chanifah Indah Ratnasari
Universitas Islam Indonesia
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences

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Journal : bit-Tech

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Measuring e-Filing Adoption as an e-Government Service Using the Technology Acceptance Model Putri, Syifa Aliya; Ratnasari, Chanifah Indah
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2804

Abstract

The digital transformation of public services in Indonesia, as mandated by Presidential Regulation No. 95 of 2018 on SPBE (Electronic-Based Government System), has led to the development of e-Filing—an electronic tax return reporting system that allows taxpayers to submit their Annual Tax Return (SPT) online. However, adoption among individual taxpayers remains uneven. This study investigates the factors influencing the acceptance and use of e-Filing among individual taxpayers registered at KPP Pratama Banjarmasin using the Technology Acceptance Model (TAM). Employing a quantitative explanatory approach, data were collected from 100 purposively selected respondents through structured questionnaires and analyzed using PLS-SEM. The findings reveal that perceived ease of use significantly influences users’ attitudes, and positive attitudes, in turn, strongly predict the intention to continue using e-Filing. However, perceived usefulness shows no significant effect on either user attitudes or usage intentions, highlighting a key divergence from core TAM assumptions. Moreover, intentions to use the system significantly influence actual usage, while ease of use and usefulness do not directly drive usage intentions. This study contributes uniquely by identifying a gap between perceived system benefits and actual behavioral intent, especially in the context of infrequent or assisted use among taxpayers. It recommends broader research that includes varied demographic groups and adopts extended models like UTAUT to explore external influences such as digital literacy, policy enforcement, and user support.
Personalized Skincare Recommendation System Based on Ontology and User Preferences Jannatin, Asista Ainun; Ratnasari, Chanifah Indah
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2857

Abstract

Personalized skincare product selection remains a complex but critically important challenge, as tailoring recommendations to individual skin profiles directly enhances treatment efficacy and fosters consumer trust. Traditional systems, such as content-based and collaborative-filtering, often fail to capture semantic interactions among skin types, concerns, and ingredients. To address these limitations, we propose an innovative ontology-based skincare recommendation system that integrates structured dermatological knowledge with semantic reasoning. Leveraging the Methontology framework, we developed an ontology composed of twelve core classes such as Product, Ingredient, Skin Type, and Skin Concern and more than twenty-five object properties to model interrelated concepts. The knowledge base was populated via web scraping from three prominent platforms (Sociolla, Beautyhaul, Skinsort), yielding over 3,800 products and 28,000 ingredients. We augmented this dataset with dermatological literature to ensure clinical validity. The architecture employs Apache Jena Fuseki and SPARQL for inference, with a React-Node.js web interface. Users input skin type, concerns, and sensitivities, which are translated into RDF triples and processed through semantic rules to generate personalized recommendations. An evaluation based on the Technology Acceptance Model (TAM) assessed Perceived Usefulness and Ease of Use. Ten diverse respondents rated the system with an average score of 4.5 out of 5 (SD=0.3) and endorsed the relevance of recommendations with a score of 4.8. Our findings demonstrate that semantic technologies can significantly enhance personalization and transparency in skincare solutions. This work lays a robust foundation for future innovations in beauty technology, clinical decision support, and consumer health platforms.
Co-Authors Abdullah Azzam Agy Audia Iskandar Ahmad Fathan Hidayatullah, Ahmad Fathan Aulia Safira Ahda Diah Hanifah Putri Dian Dwi Ramadhan Fatimah Azzahra Fattah, Fardhan Saifullah Ilmiana, Indah Rahma Jannatin, Asista Ainun Khirana Dwicahyo Khukuh Anugrah Yuwamahendra Linda Rosita Luthfi Syukriansyah Fitra Mina Rofida Rahmatina Mohammad Reza Ali Firdaus Muhammad Mellano Anantatia Nabila, Nabila PandiAstuti, Dien NoorFawziah Pratama, Nanda Zakir Shihab Putri, Syifa Aliya Rafi Arribaath Alfaresy Rizkina Maulida Safira Rizquina, Apriza Zicka Sallu Muharomah Satrio Wisnugroho Selviana Desi Permatasari Septia Rani Siti Latifah Mubasiroh Sri Haryati Sri Kusumadewi Willy Wildan Kamal Yogiswara Yogiswara