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Methods in Science and Technology Studies
Published by PT. Teknologi Futuristik Indonesia
ISSN : -     EISSN : 31234232     DOI : https://doi.org/10.64539/msts
Core Subject : Engineering,
Engineering
The Methods in Science and Technology Studies (MSTS) (e-ISSN: 3123-4232) is a peer-reviewed and open-access scientific journal, managed and published by PT. Teknologi Futuristik Indonesia in collaboration with Universitas Qamarul Huda Badaruddin Bagu and Peneliti Teknologi Teknik Indonesia. The journal publishes research that focuses on methods, models, analytical approaches, and systematic studies in science, technology, and science- and technology-based education. It aims to support the development and application of scientific and technological methods in addressing research problems and practical challenges. The journal accepts original research articles and review papers that present methodological frameworks, experimental and analytical methods, computational models, and applied studies in science, technology, and education, including interdisciplinary and applied perspectives. Scope includes: Natural and applied sciences Engineering and technology studies Computational, mathematical, and data-driven methods Machine learning, artificial intelligence, and information technology Decision-making, optimization, and forecasting methods Science and technology–based education studies Legal and regulatory studies related to science and technology The journal provides a focused platform for methodological and applied studies in science, technology, education, and related regulatory contexts.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 12 Documents
 1   2 
How to Utilize Generative AI to Compose Music through the Diary for the Possibility about User Experience and Service? Woo, Nahyun; Choi, Jeahyun; Yang, Hongmi; Kim, Minju; Choi, Jeongbin; Jang, Soonkyu
Methods in Science and Technology Studies Vol. 2 No. 1 (2026): June Article in Process
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/msts.v2i1.2026.403

Abstract

This study explores the potential of generative AI to transform diary writing into a music-based creative activity, addressing the growing significance of AI-generated content in everyday cultural practices. While prior research has examined diary-based music composition and AI music interfaces, few studies have empirically evaluated the integration of generative AI music with diary content in terms of emotional response, service perception, and usability. To bridge this gap, this study aimed to design a conceptual AI-based diary app that converts personal diary entries into lyrics and automatically generates genre-specific music reflecting contextual data (e.g., date, weather, location, and emotion). An experimental evaluation was conducted with 73 participants who listened to four AI-generated songs composed from one month of diary entries and reviewed a prototype UI. Using a 5-point Likert scale, all key factors received positive evaluations above 4.0 (emotional enthusiasm: 4.39; emotional immersion: 4.31; sympathy: 4.21; convenience: 4.23; service immersion: 4.34; retention intention: 4.19). Multiple regression analysis revealed significant positive relationships between music immersion and service awareness (p < .01), with adjusted R² values ranging from 0.241 to 0.354. The System Usability Scale score averaged 86.13, exceeding the acceptability benchmark of 75. These findings indicate that diary-based AI music services can enhance emotional immersion and user retention through convenience and personalization. The study implies strong practical potential for generative AI-driven creative services and contributes empirical evidence for future AI-based cultural content design.
An Application of Manifold-Constrained Hyper-Connection in A Progressive Web App for Sovereign Debt Sustainability Analysis Charles, Don
Methods in Science and Technology Studies Vol. 2 No. 1 (2026): June Article in Process
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/msts.v2i1.2026.414

Abstract

Importance: The rise in Trinidad and Tobago’s (T&T’s) public debt from 61.9% of GDP in 2019 to 75.6% by 2024 highlights a fiscal vulnerability facing the country. Like many other Caribbean small open economies, it is highly susceptible to external shocks, that can rapidly escalate debt-to-GDP ratios, threatening long-term economic stability. Research Gap: While the IMF provides debt sustainability frameworks, their implementation requires advances mathematical skills and extensive data often unavailable in developing countries. Existing literature identifies vulnerability under current policies but offers limited actionable guidance on the specific fiscal adjustment required to achieve sustainability targets, creating an operational gap between diagnosis and practical planning. Objective: This study proposes and designs a computational framework for a PWA to derive the fiscal surplus required to bring the debt-to-GDP ratio to a sustainable level of 60% of GDP in 10 years. Methodology: The methodology forecasts 10-year GDP using Manifold-Constrained Hyper-Connections (mHC), computes target debt at 60% of GDP, calculates the difference from current debt, and amortizes this excess debt to determine required annual fiscal surplus. Key findings: Achieving the 60% target by 2034 requires reducing debt by US$2,072.57 million, necessitating a steady annual fiscal surplus of US$268.41 million at a 5% discount rate. Implications: This study contributes the first empirical mHC application for macroeconomic forecasting, a pragmatic debt sustainability framework operationalized with minimal data, and an accessible tool that integrates technical fiscal analysis for resource-constrained policymakers in developing economies.

Page 2 of 2 | Total Record : 12

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