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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.
Identification of Underground Rivers Using Very Low Frequency Electromagnetic and Graphical User Interface Matrix Laboratory: Implications for Groundwater Exploration Umam, Rofiqul; Sismanto, Sismanto; Umar, Emi Prasetyawati; Siregar, Rahmat Nawi; Maula, Frida Yassar; Takahashi, Hirotaka
Jurnal Ilmiah Pendidikan Fisika Al-Biruni Vol 14 No 2 (2025): Jurnal Ilmiah Pendidikan Fisika Al-Biruni
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/jipfalbiruni.v14i2.27746

Abstract

The research aims to detect underground rivers using 2D mapping and minimal-noise data. In this research, 2-dimensional (2D) mapping of underground rivers in karst areas was carried out using the geophysical method of very low-frequency electromagnetic waves, namely VLF-EM (Very Low Frequency Electromagnetic Method). Electromagnetic wave analysis is based on differences in object frequencies, which reflect subsurface resistivity and conductivity and are captured by the VLF-EM detector. The measurement results were analyzed using three filter equations (Moving Average, Fraser, and Karous H-Jelt) and the Graphics User Interface Matrix Laboratory (GUI-MatLab) Software. Apart from that, the use of GUI-MatLab aims to create VLF-EM data processing software that is better for 2D interpretation display and more efficient in processing (requiring data entry only once). The research area was located in the karst rock area of Gunung Kidul Regency, Yogyakarta, Indonesia, at coordinates 8.020°S and 110.36°E. The VLF-EM measurements and GUI-MatLab interpretation detected the presence of underground river flow crossing three villages in the study area (Timun Sari, Mojo Sari, and Peyuyon), with accurate results (conductive objects were easily distinguished). Therefore, based on this study, it is recommended that productive boreholes be drilled in the 3 villages where VLF measurements were taken. The productive borehole drilling is recommended in 3 villages.
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 dan Ilmu Keguruan, Universitas Islam Negeri (UIN) Syekh Wasil Kediri

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.
Development of portable color detector: its application for determination of Munsell Soil Color Syafutra, Heriyanto; Anam, Muhammad Khoirul; Ahmad, Faozan; Nadalia, Desi; Heryanto, Rudi; Antarnusa, Ganesha; Umam, Rofiqul; Takahashi, Hirotaka
SAINS TANAH - Journal of Soil Science and Agroclimatology Vol 22, No 1 (2025): June
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/stjssa.v22i1.91351

Abstract

Soil color is a crucial indicator in soil science and agriculture; it provides information about soil properties and conditions. Typically, surveyors determine soil color by visually comparing the soil samples to the Munsell Soil Color Chart (MSCC). However, the accuracy of this method can be influenced by lighting conditions and the observer's subjectivity, leading to potential inconsistencies. This study introduces a portable color sensor device designed to improve the accuracy and consistency in determining the soil color and its MSCC notation compared to traditional visual methods. The device integrates a TCS3200 color sensor with a microcontroller to automate the color determination process. The device was validated by operating it to determine the color of 12 test paper sheets and four test soil types. The device can determine the color of the tested paper and soil well (100% accuracy); the result is displayed on the Liquid Crystal Display. It consistently achieved 100% accuracy for all measurements with varying ambient light intensity. The device is designed to be portable and easy to use, thus supporting field use for surveyors. Therefore, this device offers significant advantages in soil classification, fertility assessment, and environmental monitoring.