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All Journal Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan Sinergi JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI Forum Geografi Jurnal Geocelebes Journal of Science and Applicative Technology JIPF (Jurnal Ilmu Pendidikan Fisika) Jurnal Sains Teknologi dan Lingkungan (JSTL) Indonesian Mining Journal Angkasa: Jurnal Ilmiah Bidang Teknologi Jurnal Ilmu Fisika KURVATEK G-Tech : Jurnal Teknologi Terapan DEVICE Indonesian Community Journal International Journal of Hydrological and Environmental for Sustainability JOMPA ABDI: Jurnal Pengabdian Masyarakat Prosiding Seminar Nasional Rekayasa Teknologi Industri dan Informasi ReTII Sewagati Jurnal Teknologi Mineral dan Batubara Indonesian Mining Journal Masyarakat: Jurnal Pengabdian
Rizqi Prastowo
Institut Teknologi Nasional Yogyakarta
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Pemodelan Artificial Neural Network (ANN) Untuk Identifikasi Bangunan Daerah Rawan Longsor Sari, Sely Novita; Pratama, Bagus Gilang; Prastowo, Rizqi
Device Vol 14 No 1 (2024): Mei
Publisher : Fakultas Teknik dan Ilmu Komputer (FASTIKOM) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/device.v14i1.6701

Abstract

Identifikasi bangunan daerah rawan longsor adalah suatu hal yang penting dalam mitigasi bencana alam. Longsor dapat terjadi di mana saja dan kapan saja, dan dapat menyebabkan kerugian yang besar baik dari segi manusia maupun materiil (fadli dkk, 2023). Oleh karena itu, penting untuk mengidentifikasi bangunan yang berada di daerah rawan longsor agar dapat mengambil tindakan pencegahan yang tepat. Metode yang dapat digunakan untuk identifikasi bangunan di daerah rawan longsor adalah artificial neural network (ANN). ANN adalah suatu model komputasi yang terinspirasi dari sistem saraf biologis yang terdiri dari sejumlah unit pemrosesan sederhana yang disebut neuron. ANN dapat belajar dari data dan menyesuaikan bobot koneksi antar neuron untuk menghasilkan keluaran yang diinginkan. ANN memiliki kemampuan untuk mengenali pola, mengklasifikasikan data, dan memprediksi hasil. Berdasarkan analisis data klasifikasi dinding sederhana di Kecamatan Kalirejo, Kecamatan Kokap, Kabupaten Kulon Progo, Yogyakarta, menggunakan Artificial Neural Network (ANN), presentase prediksi setiap data dari pemodelan ANN menunjukkan bahwa indikator Bangunan Tidak Aman mencapai 100%, dengan 89% prediksi Bangunan Aman, dan 82,7% prediksi Bangunan Aman berdasarkan History Accuracy. Hasil tersebut diukur dengan merujuk pada kurva model validasi yang semakin meningkat dan stabil, mencapai nilai akurasi rata-rata di atas 80%, yakni sebesar 88%.
Penggunaan Metode Elbow untuk Pemilihan Jumlah Klaster dalam Identifikasi Bahan Material Shelter Modular SARI, SELY NOVITA; Pratama, Bagus Gilang; Prastowo, Rizqi
Retii 2024: Prosiding Seminar Nasional ReTII ke-19 (Edisi Penelitian)
Publisher : Institut Teknologi Nasional Yogyakarta

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

Abstract

Modular shelters have become a popular solution for temporary infrastructure construction, especially in disaster-affected areas. One of the main challenges is selecting the appropriate materials, which can be addressed through cluster analysis to group materials based on similar characteristics. The Elbow Method is used to determine the optimal number of clusters in this analysis, with the "elbow" point on the graph indicating that four clusters are ideal. The K-Means algorithm is then applied to group material data based on the centroid of each cluster. The application of the Elbow Method has proven effective in determining the optimal number of clusters for material identification in modular shelter construction. By analyzing the relationship between the number of clusters and inertia, the Elbow Method successfully indicates that four clusters are the most appropriate. The Elbow graph shows a significant "elbow" after the third and fourth clusters, where the decrease in inertia slows down, indicating that adding more than four clusters does not significantly improve data grouping. Quantitatively, clustering with four clusters provides a balance between data variation and ease of interpretation. Each cluster exhibits distinct characteristics based on the average values of structural and architectural attributes, with variability measured through standard deviation
PENELITIAN DISTRIBUSI SUMBER DAYA ANDESIT BERDASARKAN DATA RESISTIVITAS MENGGUNAKAN METODE GEOELEKTRIK SCHLUMBERGER Aldri, Riaferdo; Isjudarto, Agustinus; Prastowo, Rizqi
KURVATEK Vol 10 No 2 (2025): Energy Management and Sustainable Environment
Publisher : Institut Teknologi Nasional Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33579/krvtk.v10i2.6408

Abstract

Penelitian ini bertujuan untuk mengidentifikasi sebaran batuan andesit di Kecamatan Bener, Kabupaten Purworejo, Jawa Tengah, menggunakan metode geolistrik konfigurasi Schlumberger. Sebanyak 37 titik pengukuran dilakukan dengan bentangan kabel 200 meter untuk memperoleh data tahanan jenis bawah permukaan. Hasil inversi resistivitas menunjukkan nilai berkisar diatas 900 Ωm yang menandakan keberadaan batuan andesit segar dengan kondisi fisik padat dan belum mengalami pelapukan. Model 3D memperlihatkan sebaran andesit yang dominan pada arah baratlaut–tenggara dengan kedalaman antara 0,1 hingga 0,4 km dari permukaan. Persebaran ini berasosiasi dengan struktur vulkanik Formasi Andesit Tua yang berkembang di wilayah tersebut. Secara umum, hasil penelitian menunjukkan bahwa metode geolistrik efektif untuk memetakan distribusi batuan beku bawah permukaan dan memberikan informasi geologi yang penting bagi perencanaan pemanfaatan sumber daya alam di Kecamatan Bener.
PENDUGAAN SUMBER AIR TANAH DI DAERAH DESA KREMBANGAN, KEC. PANJATAN, KAB. KULON PROGO, D.I. YOGYAKARTA DENGAN METODE GEOLISTRIK KONFIGURASI SCHLUMBERGER Prastowo, Rizqi; Sugarbo, Oky; Hidayat, Eko Wahyu
Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan Vol. 9 No. 3 (2025): Vol. 9 No. 3, November 2025
Publisher : Lembaga Penelitian dan Pengabdian Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jss.v9i3.513

Abstract

Desa Krembangan memiliki kondisi geologi yang beragam, mulai dari dataran berlempung di bagian selatan hingga perbukitan batugamping yang kering di bagian utara. Variasi karakter batuan tersebut menyebabkan distribusi air tanah yang tidak merata, sehingga sebagian masyarakat, terutama di wilayah tengah dan utara, mengalami kesulitan dalam memperoleh air bersih pada musim kemarau. Kegiatan pengabdian masyarakat ini bertujuan untuk memberikan informasi awal mengenai potensi akuifer melalui survei geolistrik resistivitas menggunakan konfigurasi Schlumberger. Dua lintasan pengukuran sepanjang masing-masing 200 meter ditentukan berdasarkan kondisi geomorfologi dan aksesibilitas lapangan. Akuisisi data dilakukan dengan metode sounding, yaitu memperbesar jarak elektroda arus secara bertahap untuk memperoleh penetrasi kedalaman yang lebih baik. Hasil pengukuran kemudian diolah menggunakan pemodelan inversi resistivitas untuk menghasilkan penampang bawah permukaan. Nilai resistivitas rendah (<1 Ωm) diinterpretasikan sebagai zona jenuh air. Berdasarkan hasil pemodelan, akuifer teridentifikasi pada kedalaman sekitar 15–18 meter dengan ketebalan bervariasi antara 0,5 hingga 2 meter. Informasi ini diharapkan dapat digunakan sebagai dasar dalam penentuan lokasi sumur bor yang lebih tepat, sehingga mampu meningkatkan ketersediaan air bersih bagi masyarakat Desa Krembangan secara berkelanjutan.
Hydrological Effects on Rock Mass Quality and Rippability of Heterogeneous Karstic Limestone Wijaya, Andy Erwin; Misdiyanta, Partama; Prastowo, Rizqi; Mitsui, Yoshitaka; Yongthong, Keodouangdy; Radhitya, Berwyn Dzaky
International Journal of Hydrological and Environmental for Sustainability Vol. 5 No. 1 (2026): 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.v5i1.1122

Abstract

The proposed study area is located approximately 1.9 km southwest of the main cement plant in Tuban, Indonesia. This research aims to evaluate the rippability characteristics of the limestone formation underlying the planned development site. The assessment is based on data obtained from a geotechnical borehole investigation (CR-1), integrated with previous subsurface exploration results. The site is designated for shallow foundation systems designed to withstand bearing pressures ranging from 300 to 800 kPa. Subsurface conditions are characterized by karstic limestone with complex hydrogeological features. The limestone exhibits high sensitivity to water infiltration, dissolution processes, and mechanical property degradation under saturated conditions. Significant spatial variability in rock mass quality and strength is observed over relatively short vertical and horizontal distances. The uppermost layer comprises residual lateritic (red) soil derived from in-situ weathering of the underlying limestone. The presence of limestone gravels and boulders within the residual soil indicates a transitional interface between the overburden and the more competent limestone strata. The limestone formation consists of heterogeneous materials, including highly porous honeycomb-textured rock and relatively intact, sound limestone, distributed irregularly across the site. This heterogeneity results in considerable variability in mechanical strength and excavation response. The findings provide essential insights into the rippability behavior of the limestone and its implications for foundation design and construction planning in karst environments.
Structural Interpretation of the Jonggol Mount Area, Kulon Progo, Yogyakarta, Using Gravity Inversion Modelling Setyo Pambudi; Prastowo, Rizqi; Setiahadiwibowo, Ajimas Pascaning
Jurnal Ilmu Fisika Vol 18 No 1 (2026): March 2026
Publisher : Jurusan Fisika FMIPA Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jif.18.1.67-79.2026

Abstract

The Mount Jonggol region in Kulon Progo, Yogyakarta, constitutes an important segment of the Sunda–Banda magmatic arc system; however, its subsurface structural configuration remains insufficiently understood. This study aims to interpret subsurface structures and lithological boundaries through derivative analysis and three-dimensional gravity inversion modelling. The gravity dataset was obtained from the Global Gravity Model Plus (GGMplus), which provides absolute gravity acceleration measurements with high spatial resolution. The data were processed using sequential corrections, including normal gravity, free-air, simple Bouguer, and terrain corrections, to generate the Complete Bouguer Anomaly (CBA). The resulting CBA data were analyzed using the First and Second Horizontal Derivative (FHD and SHD) methods to delineate structural discontinuities, fault planes, and density contrasts. Furthermore, three-dimensional inversion modelling was conducted to visualize subsurface density variations to a depth of approximately 3.5 km. The results indicate that Mount Jonggol is situated at the tectono-lithological boundary between the low-density Jonggrangan Formation (2.0–2.4 g/cc) and the high-density Old Andesite Formation (2.7–3.0 g/cc). The gravity anomaly pattern reveals a northwest–southeast-oriented magmatic corridor controlled by thrust and strike-slip fault systems, providing important insights into the tectono-magmatic evolution and uplift mechanisms of southern Central Java.
Co-Authors A.A Inung Arie Adnyano, A.A Inung Arie Abdul Latif Ashadi Agustinus Isjudarto Ahmad Said Akhmad Zamroni Al Hussein Flowers Rizqi Aldri, Riaferdo Amir Machmud Amir Machmud, Amir Andika Eko Prasetiyo Andika Eko Prasetiyo, Andika Eko Andyono B. Santoso Angger Bagus Prasetiyo Anggi Hermawan Anita Susiana Arimurti, Dyah Arum Bagus Gilang Pratama, Bagus Gilang Bahy, Muhammad Nauval Brahme, Nameeta Cengiz, Korhan Dandi Pranomo Eko Wahyu Hidayat, Eko Wahyu Fahrul Nurfajri Mokoagow Fajar Yulianto Prabowo Farid, Fajri Filipus Alfriyadi Junaidi firhad firmansyah Hasan Said Tortop Hendro Purnomo Herman, Sofiana Hidayatullah Shidiq hidayatullah sidiq Hikmahtiar, Syouma Hurien Helmi Ichwan Noor Ardiyat Ikah N. P. Permanasari Ilham Mopio Iman Pradana A. Assagaf Iqbal, Mochamad Iwan Tri Riyadi Yanto, Iwan Tri Riyadi Jemssy Ronald Rohi Jermsittiparsert, Kittisak Junior, Prince Robert Kapugu, Excellentia Riane Kittisak Jermsittiparsert Manmeet Kaur Melfa Utari Misdiyanta, Partama Mitsui, Yoshitaka Muhamad Syazali Muhammad Hafizh Hibullah Murkute, Yogesh Novandri Kusuma Wardana Oggi Heical Ardian Oggi Heicqal Ardian Oky Sugarbo Ozyurt, Basak Panse, Vishal R. Paramitha Tedja Trisnaning Puspasari, Fitri Radhitya, Berwyn Dzaky Rahmad Junaidi, Rahmad Randy Galaxy Rita Desiasni Rizal Maulana Rizal Maulana, Rizal Rofiqul Umam Sabrina Putri Puspitasari Sely Novita Sari Setiahadiwibowo, Ajimas Pascaning Setiawan, Nanda Juli Setyo Pambudi Setyo Pambudi Setyo Pambudi Shilvyanora Aprilia Rande, Shilvyanora Syamsul Huda Syamsul Huda Tarumasely, Nofry Hence Tedy Kurniawan Topac, Tuna Tortop, Hasan Said Tri Nugroho Suwarno Urip Nurwijayanto Prabowo Urip Nurwijayanto Prabowo Urip Nurwijayanto Prabowo, Urip Nurwijayanto Veronica Diana Anis Anggorowati Vico Luthfi Ipmawan Wijaya, Andy Erwin Yonathan Ito Yongthong, Keodouangdy