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All Journal Journal of Natural Sciences and Mathematics Research International Journal of Hydrological and Environmental for Sustainability Islamic Journal of Integrated Science Education
Takahashi, Hirotaka
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Education Environmental Science Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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An unsupervised machine learning algorithm approach using K-Means Clustering for optimizing Surface Wave Filtering in seismic reflection data Hartono, Hartono; Anwar, Haerul; Umam, Rofiqul; Takahashi, Hirotaka
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Surface waves often cause significant noise in seismic data, complicating the interpretation of subsurface structures. Traditional filtering methods, such as FK filtering, usually struggle with non-stationary noise and require extensive manual parameter tuning. This study explores the effectiveness of using K-means clustering, incorporating attributes such as amplitude, frequency, and phase to filter surface waves from seismic data. Synthetic seismic data were first generated to test the proposed method, ensuring its robustness before application to real field data. Attributes were extracted from each seismic trace, including instantaneous amplitude, frequency, and phase. These attributes were used as input parameters for the K-means clustering algorithm. The identified clusters corresponding to surface waves were then used to filter these waves from the seismic data. The K-Means clustering effectively differentiated surface waves from reflected waves in both synthetic and real seismic datasets. The method demonstrated that by including phase as an attribute, alongside amplitude and frequency, the accuracy of surface wave detection and filtering significantly improved. The synthetic data showed a clear separation of wave types, validating the method. When applied to real field data, the approach consistently removed surface waves, clarity of seismic reflections crucial for subsurface analysis.
Analysis of Subsurface Faults Using 3D Gravity Method Based On Satellite Image Data: Insights into Indo-Australian and Eurasian Plate Subduction in the Formation of An Accretionary Prism Dewi, Kadek Ciptani Satria; Siregar, Rahmat Nawi; Ningati, Trisna Ikhsan; Pulungan, Zumaida Nur; Indriyawati, Agapetalia; Takahashi, Hirotaka
International Journal of Hydrological and Environmental for Sustainability Vol. 4 No. 3 (2025): International Journal of Hydrological and Environmental for Sustainability
Publisher : CV FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/ijhes.v4i3.960

Abstract

This geophysical study employs the gravity method to analyze subsurface fault structures in the Simeulue Island region, located between 1°59′S–3°14′S and 95°06′E–96°59′E. The area lies within an active tectonic zone where the IndoAustralian Plate subducts beneath the Eurasian Plate, making it a critical site for understanding subduction dynamics and accretionary prism formation. Secondary gravity and topographic data were acquired from TOPEX satellite imagery. The primary objective is to identify gravity anomalies and delineate subsurface geological features such as faults, folds, and fractures—based on variations in the Earth's gravitational field caused by density contrasts between rock units. The gravity method is particularly effective due to its sensitivity to such density differences. Qualitative interpretation was conducted using Surfer 16, while quantitative modeling utilized Oasis Montaj. Results reveal high Bouguer anomaly values in the southwest, corresponding to the plate convergence zone, and low anomaly values extending from the southeast to northwest, associated with the accretionary prism. The 2D model illustrates the subduction of oceanic crust with a density of 3.43 g/cm³ beneath continental crust with a density of 2.67 g/cm³. The 3D model further reveals that subduction becomes evident at a depth of approximately 16.11 km, with the crustal thickness in the accretionary prism zone reaching around 19.92 km. The 3D approach provides a more comprehensive spatial visualization of the subduction geometry and density distribution, offering insights that surpass conventional 2D analysis. These findings contribute to a deeper understanding of regional geodynamics and may serve as a reference for seismotectonic studies and disaster mitigation efforts in the surrounding area.
Synthesizing A Framework and Establishing Content Validity of An Energy Literacy Instrument for Indonesian Students Usman, Musawwir; Pramudawardani, Hanis; Umam, Rofiqul; Takahashi, Hirotaka
Islamic Journal of Integrated Science Education (IJISE) Vol. 4 No. 3 (2025): November
Publisher : Program Studi Tadris IPA, Fakultas Tarbiyah (IAIN) Kediri, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/ijise.v4i3.6993

Abstract

Energy literacy is a critical competency for cultivating awareness, responsibility, and sustainable energy practices among students. This study aims to synthesizing a framework and establishing the content validity of an instrument designed to measure Indonesian students’ energy literacy across cognitive, affective, and behavioral domains. Employing a descriptive research design, the study was conducted in two stages: framework synthesis and expert validation. The synthesized framework integrated key constructs from established energy literacy models and contextualized them within Indonesia’s socio-educational setting. The initial instrument comprised 32 cognitive test items, 20 affective statements, and 15 behavioral statements. Content validation was performed by two expert lecturers and three science teachers, who assessed the relevance, clarity, and appropriateness of each item. Results indicated that all domains achieved the “very feasible” category, demonstrating strong content validity. Following revisions based on expert feedback, 59 items were retained: 30 cognitive, 17 affective, and 12 behavioral. The validated instrument offers a comprehensive and contextually relevant tool for evaluating students’ knowledge, attitudes, and behaviors toward energy, thereby supporting the advancement of energy education and sustainable practices in Indonesia.
Co-Authors Dewi, Kadek Ciptani Satria Haerul Anwar Hartono Hartono Indriyawati, Agapetalia Ningati, Trisna Ikhsan PRAMUDAWARDANI, HANIS Pulungan, Zumaida Nur Rofiqul Umam Siregar, Rahmat Nawi Usman, Musawwir