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All Journal Jurnal Penelitian Sistem Informasi Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Aditya Dimas Dewanto
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Computer Science & IT Decision Sciences, Operations Research & Management

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Artificial Intelligence Applications in Piano Education : An Informatics-Based Literature Analysis Aditya Dimas Dewanto; Ari Sugiharto
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 3 No. 4 (2025): Juli : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v3i4.700

Abstract

This study examines the role of Artificial Intelligence (AI) in piano education through a qualitative review of six recent academic sources. AI technology has brought about significant transformations in music learning methods, particularly for the piano instrument. Various AI applications such as automated performance feedback systems, musical accompaniment generators, technical error detection devices, and adaptive learning platforms have enabled new approaches to teaching and learning. AI provides instant feedback, tailored exercises to individual abilities, and creates more interactive and flexible learning environments. These innovations are considered to support the development of students' technical skills more effectively, while increasing learning motivation through personalization and ease of access. Furthermore, this study examines the information systems that support these AI applications, including human-computer interaction, audio signal processing, and the use of machine learning models to recognize playing patterns and technical errors. While AI offers significant benefits, concerns arise regarding its limitations in understanding and responding to the emotional aspects of music. AI is not yet capable of fully supporting the development of subjective and complex musical expression. Over-reliance on this technology is also feared to undermine students' critical thinking, artistic sensitivity, and creativity. Therefore, this study emphasizes the importance of a balanced integration between AI technology and human pedagogical roles, with the teacher remaining the primary facilitator in fostering expression, interpretation, and artistic values in piano learning. The study recommends further research on emotionally responsive AI, blended learning models, and long-term evaluation of AI's impact on students' artistic and musical development.  
Geospatial Modeling of Megathrust Earthquake Hazards in Southern Java, Indonesia using GIS-Based Weighted Overlay Analysis Aditya Dimas Dewanto; Noviyanti Riendrasiwi
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 2 (2026): Mei: JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i2.3888

Abstract

Megathrust earthquakes occurring along subduction zones pose significant natural hazards, particularly in tectonically active regions such as Indonesia. The southern coast of Java is highly vulnerable due to its proximity to the Sunda megathrust, which has the potential to generate large-magnitude earthquakes and associated risks. This study aims to develop a GIS-based model to assess megathrust earthquake hazards in Southern Java, Indonesia. A quantitative geospatial approach was employed by integrating Geographic Information Systems (GIS) with a Multi-Criteria Decision Analysis framework using weighted overlay analysis. Several spatial parameters, including seismic activity, distance to the subduction zone, geological structure, and elevation, were processed and standardized before being combined into a composite hazard index. The results indicate a clear spatial pattern, where high hazard zones are concentrated in coastal and offshore areas near the subduction interface, while inland regions exhibit lower hazard levels. This spatial distribution reflects the influence of tectonic proximity on hazard intensity. The study demonstrates that GIS-based weighted overlay analysis is effective in integrating multiple hazard indicators into a unified spatial model. The resulting hazard map provides valuable insights for disaster risk reduction, spatial planning, and preparedness strategies in megathrust-prone areas. This research also contributes to the advancement of geospatial modeling frameworks for earthquake hazard assessment, particularly in regions with similar tectonic characteristics.
Co-Authors Ari Sugiharto Noviyanti Riendrasiwi