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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) bit-Tech Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Formosa Journal of Science and Technology (FJST) Jurnal Inovasi Pengabdian Masyarakat Jurnal Ilmu Komputer (JIK) Journal of Social Science and Business Studies Jitu: Jurnal Informatika Utama Dinamika: Jurnal Pengabdian Masyarakat Spectrum: Multidisciplinary Journal
Eriana, Emi Sita
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Physics Social Sciences Other

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Utilizing Cobit 4.1 and Balance Scorecard to Manage Information Technology Business Process in Higher Education Institution Eriana, Emi Sita; Susanti, Leni
Journal of Social Science and Business Studies Vol. 2 No. 3 (2024): JSSBS
Publisher : Yayasan Gema Bina Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61487/jssbs.v2i3.89

Abstract

Pamulang University's Information Technology Strategy Plan aims to develop a comprehensive strategy to maximize IT efficiency and effectiveness in the institution. Using the COBIT 4.1 approach, SWOT analysis, and Balanced Scorecard, this plan identifies strengths, weaknesses, opportunities, and threats in the current IT infrastructure and develops an integrated strategy for IT development. COBIT 4.1 provides a framework for managing and controlling IT by ensuring that IT processes support business objectives and meet stakeholder needs. The SWOT analysis explores the internal and external factors that influence IT at Pamulang University, while the Balanced Scorecard helps in establishing balanced strategic metrics and objectives across multiple perspectives, including financial, customer, internal processes, and learning and growth. This strategic plan is expected to improve IT management, support the achievement of Pamulang University's goals and facilitate data-based decisions for innovation and continuous improvement.
Implementation of Natural Language Processing Based Chatbot as a Virtual Assistant in Science Learning Eriana, Emi Sita; Subariah, Risah
Jurnal Penelitian Pendidikan IPA Vol 11 No 10 (2025): October
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i10.12747

Abstract

Inadequate conceptual understanding and declining learning motivation remain major challenges in science education. To address these issues, this study implemented a Natural Language Processing (NLP)-based chatbot as a virtual assistant designed to provide adaptive feedback and personalized guidance in science learning. A mixed-methods approach was employed, integrating quantitative and qualitative phases within a quasi-experimental pretest–posttest control group design involving 240 tenth-grade students in Jakarta over eight weeks. Quantitative data from the Science Achievement Test (SAT) and Science Learning Motivation Scale (SLMS) were analyzed using an independent samples t-test, while qualitative data from interviews and learning analytics were used to explain behavioral and motivational changes. The experimental group showed a substantial improvement in conceptual understanding, increasing from a mean pretest score of 42.5 to 88.4, compared to 44.1 to 62.7 in the control group (t(238) = 11.34, p < 0.001, d = 1.56). Motivation scores also increased significantly across all dimensions (p < 0.001), particularly in self-efficacy (η²p = 0.198). Learning analytics indicated higher interaction frequencies and longer engagement times. Students reported five perceived benefits: 24/7 accessibility, personalized explanations, increased questioning confidence, support for complex concept visualization, and stronger self-driven learning motivation. Overall, the NLP-based chatbot effectively enhanced science learning outcomes and motivation.
Co-Authors Afrizal Zein Akhyar, Iscan Nul Ardiansyah, Azril Ardiansyah, Muhammad Zikri Barokah, Nova Rizki Djoha, Deni Saptudin Dzikri, Muhammad Tri Putro Alfaz Fahlevi, Muhamad Fahdhan Farizy, Salman Haerudin, Heri Iskandar, Fikih Nur Jayawarsa, A.A. Ketut Karimah, Mufidah Leni Susanti Muhammad Rizqi Pramudya, Muhammad Rangga Rizkyansah, Satriyo Rozali, Christien Sri Wahyuni Subariah, Risah Yandira, Avita Zaenuddin, Imam Zein, Afrizal