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All Journal Jurnal Syntax Imperatif : Jurnal Ilmu Sosial dan Pendidikan Indonesian Journal of Earth Sciences Jurnal Mandiri IT Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia
Waluyo, Dangan
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Earth & Planetary Sciences Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences

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Peran Industri Pertahanan Dalam Meningkatkan Kemanan Maritim Guna Mendorong Visi Indonesia Sebagai Poros Maritim Dunia Sholihah, Tyan Hidayatus; Waluyo, Dangan; Jupriyanto, Jupriyanto; Putro, Tri Guntoro Sukarno
AURELIA: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Vol 4, No 2 (2025): July 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/aurelia.v4i2.5115

Abstract

Indonesia merupakan negara maritim terbesar di dunia dengan potensi ekonomi maritim mencapai 1.338 miliar dollar AS per tahun. Hal ini membuat Indonesia tidak lepas dari berbagai ancaman militer maupun non militer. Beberapa ancaman ini membuat kondisi keamanan Indonesia yang menjadi tidak stabil dan mengganggu upaya Indonesia dalam mewujudkan misi sebagai ”poros maritim dunia”. Potensi ancaman tersebut membutuhkan pertahanan negara yang kuat yang dapat mencakup seluruh wilayah secara maksimal. Sehingga diperlukan lembaga atau instansi yang bertujuan menjaga keamanan dan pertahanan maritim negara. Badan Keamanan Laut (Bakamla) RI merupakan lembaga yang bertugas melakukan patroli keamanan dan keselamatan diwilayah yurisdriksi Indonesia. Namun saat ini kebutuhan kapal patroli Bakamla masih jauh dari ideal. Oleh karena itu dalam paper ini akan dibahas penyebab dari potensi ancaman keamanan maritim Indonesia dilihat dengan perspektif sytem thinking, serta bagaimana pengadaan alutsiskamla mempengaruhi keamanan maritim Indonesia. Penelitian ini menggunakan metode penelitian deskriptif dan kuantitatif untuk memahami ancaman keamanan maritim Indonesia dampak dari pengadaan alutsiskamla berupa kapal patroli. Hasil penelitian menunjukkan bahwa penyebab potensi ancaman keamanan maritim Indonesia adalah kurang optimlanya kapal patroli Bakamla yang hanya memenuhi 53% kebutuhan kapal ideal, yang berdampak pada cakupan patroli area yaitu 51% dari total luas perairan dan yurisdiksi Indonesia. Langkah solutif untuk meningkatkan infrastruktur Bakamla adalah pengadaan kapal patroli baru. Solusi ini terbukti efektik karena berdasarkan perhitungan Internal Strategic Factor Analysis Summary (IFAS) dan Enternal Strategic Factor Analysis Summary (EFAS) setelah dilakukan SWOT, edua faktor strategis, baik internal maupun eksternal, memiliki nilai solusi yang lebih tinggi secara total daripada ancaman keamanan maritim, yaitu faktor internal 4.1818 dibanding 4.52173 dan faktor internal yaitu 3.975 dibanding 4.225.
Bangka strait salinity prediction using landsat 9 oli image data Khoirun Nisa; Harsono, Gentio; Martha, Sukendra; Waluyo, Dangan
Jurnal Mandiri IT Vol. 14 No. 1 (2025): July: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i1.447

Abstract

Salinity is an important parameter because it affects the environment, such as water quality, growth, and development of aquatic vegetation and various animal species. Conventional water quality monitoring is still ineffective, so it is necessary to utilize technology in monitoring water quality, including water Salinity is an important parameter because it affects the environment, such as water quality, growth, and development of aquatic vegetation and various animal species. Conventional water quality monitoring is still ineffective, so it is necessary to utilize technology in monitoring water quality, including water salinity. Utilization of remote sensing is often used to study salinity both on a small scale and a global scale. Therefore, the author conducted a study to predict salinity in the Bangka Strait using the RRS (Remote Sensing Reflectance) method. The data used are Landsat 9 OLI image data downloaded from the USGS website and in situ salinity data in the Bangka Strait sea. The Landsat 9 OLI image data used is level 2 Surface Reflectance (SR), which is ready for analysis without additional processing by the user. The data obtained were processed using multiple linear regression analysis with Rrs as the independent variable and in situ salinity as the dependent variable. Salinity prediction models are divided into three groups based on the image recording date, namely Rrs 1 for the Landsat 9 OLI image recording on May 9, 2024, Rrs 2 for July 28, 2024, and Rrs 3 for the image recording on September 28, 2023. Multiple linear regression analysis produces R² values for each model of 0.81662874, 0.8170285, and 0.8136894. These R² results indicate that the three models, Rrs 1, Rrs 2, and Rrs 3, are included in the very good criteria in predicting salinity. To choose the best of the three models, by considering the results of the validity test. The NMAE validity test for Rrs 1, Rrs 2, and Rrs 3 is 10.10152, 10.37618, and 8.88680. Meanwhile, the RMSE values are 2.41327, 2.41064, and 2.43253. Therefore, it can be determined that the Rrs 2 model is the best in predicting salinity because it has the highest R² value, namely 0.8170285, and the smallest RMSE, namely 2.41064.
Peran Industri Pertahanan Dalam Meningkatkan Kemanan Maritim Guna Mendorong Visi Indonesia Sebagai Poros Maritim Dunia Sholihah, Tyan Hidayatus; Waluyo, Dangan; Jupriyanto, Jupriyanto; Putro, Tri Guntoro Sukarno
AURELIA: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Vol 4, No 2 (2025): July 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/aurelia.v4i2.5115

Abstract

Indonesia merupakan negara maritim terbesar di dunia dengan potensi ekonomi maritim mencapai 1.338 miliar dollar AS per tahun. Hal ini membuat Indonesia tidak lepas dari berbagai ancaman militer maupun non militer. Beberapa ancaman ini membuat kondisi keamanan Indonesia yang menjadi tidak stabil dan mengganggu upaya Indonesia dalam mewujudkan misi sebagai ”poros maritim dunia”. Potensi ancaman tersebut membutuhkan pertahanan negara yang kuat yang dapat mencakup seluruh wilayah secara maksimal. Sehingga diperlukan lembaga atau instansi yang bertujuan menjaga keamanan dan pertahanan maritim negara. Badan Keamanan Laut (Bakamla) RI merupakan lembaga yang bertugas melakukan patroli keamanan dan keselamatan diwilayah yurisdriksi Indonesia. Namun saat ini kebutuhan kapal patroli Bakamla masih jauh dari ideal. Oleh karena itu dalam paper ini akan dibahas penyebab dari potensi ancaman keamanan maritim Indonesia dilihat dengan perspektif sytem thinking, serta bagaimana pengadaan alutsiskamla mempengaruhi keamanan maritim Indonesia. Penelitian ini menggunakan metode penelitian deskriptif dan kuantitatif untuk memahami ancaman keamanan maritim Indonesia dampak dari pengadaan alutsiskamla berupa kapal patroli. Hasil penelitian menunjukkan bahwa penyebab potensi ancaman keamanan maritim Indonesia adalah kurang optimlanya kapal patroli Bakamla yang hanya memenuhi 53% kebutuhan kapal ideal, yang berdampak pada cakupan patroli area yaitu 51% dari total luas perairan dan yurisdiksi Indonesia. Langkah solutif untuk meningkatkan infrastruktur Bakamla adalah pengadaan kapal patroli baru. Solusi ini terbukti efektik karena berdasarkan perhitungan Internal Strategic Factor Analysis Summary (IFAS) dan Enternal Strategic Factor Analysis Summary (EFAS) setelah dilakukan SWOT, edua faktor strategis, baik internal maupun eksternal, memiliki nilai solusi yang lebih tinggi secara total daripada ancaman keamanan maritim, yaitu faktor internal 4.1818 dibanding 4.52173 dan faktor internal yaitu 3.975 dibanding 4.225.
Sea Surface Salinity (SSS) Prediction Using Landsat 8 OLI Image Data in The Bangka Strait Waters with Five Prediction Model Combinations Nisa, Khoirun; Harsono, Gentio; Martha, Sukendra; Waluyo, Dangan
Indonesian Journal of Earth Sciences Vol. 5 No. 2 (2025): July-December
Publisher : MO.RI Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52562/injoes.2025.1738

Abstract

Salinity is the most important parameter for controlling the biological components of ecosystems, seas, and estuaries, which also control the components that make up an ecosystem. Conventional water quality monitoring is considered inaccurate and inefficient in terms of energy and time. Therefore, research is needed to predict sea surface salinity as a type of water quality monitoring using remote sensing reflectance or Remote Sensing Reflectance (RRS) from Landsat imagery. The Landsat image data used is level 2 Surface Reflectance (SR), which is ready to use without additional processing by the user, whereas previous research required corrections to the image data to obtain Surface Reflectance image data. This study aims to determine the performance of the prediction model produced by using five combinations of Landsat image bands. The data used are Landsat 8 OLI image data (recording date 05 August 2024) downloaded from the USGS website and in situ salinity data in the Bangka Strait sea (09 March 2025), as many as 5 samples that can be used. The obtained data were processed using multiple linear regression analysis with Rrs as the independent variable and in situ salinity as the dependent variable. The salinity prediction model consisted of five band combinations. The analysis produced R² values for each model combination of 0.8166287408, 0.935603228, 0.820745745, 0.869209652, and 0.574027060. The RMSE validity tests for combination 1, combination 2, combination 3, combination 4, and combination 5 were 2.41327, 1.43012, 2.38602, 2.03811, and 3.67817. Then for the NMAE value, namely 10.10152205%, 5.32713015%, 9.58011308%, 8.8868031%, and 14.51012574%. The combination rankings that have the best prediction performance are combination 2, combination 4, combination 3, combination 1, and combination 5. So the best model in predicting seawater salinity is the combination of the 2 prediction models, with its constituent band components being band 1, band 2, and band 4.
Hydrological Analysis of Mini Hydro Power Plants (PLTM) Using The Flow Duration Curve Approach Bennuwardana, Nengah; Martha, Sukendra; Prihanto, Yosef; Waluyo, Dangan; Firmansyah, Firmansyah; Rifai, Bachtiar
JURNAL SYNTAX IMPERATIF : Jurnal Ilmu Sosial dan Pendidikan Vol. 6 No. 4 (2025): Jurnal Syntax Imperatif: Jurnal Ilmu Sosial dan Pendidikan
Publisher : CV RIFAINSTITUT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54543/syntaximperatif.v6i4.792

Abstract

Hydrological analysis is crucial in the planning of a Mini-Hydro Power Plant (PLTM). This study aims to examine the hydrological aspects of the Way Besai PLTM, located in Bonglai Village, Way Kanan Regency, Lampung Province. The Way Besai Mini-Hydro Power Plant (PLTM) is a runoff-river PLTM scheme located approximately 242 km north of Bandar Lampung City, Lampung Province, Indonesia. The data used include daily rainfall data from six rainfall stations, climate element data from the Radin Inten II Meteorological Station, and outflow data from the Besai PLTA. The rainfall data were analyzed for consistency using the Mass Curve method, with only three stations deemed consistent. Potential evapotranspiration was calculated using the Modified Penman method. Furthermore, the rainfall data were converted into daily discharge data using the F.J. Mock Rainfall to Runoff hydrological method. The catchment area is 449.14 km2 at the intake site and the average annual rainfall reaches 2,366 mm/year. The analysis results are used to determine the mainstay discharge (plant discharge) and the planned flood discharge through the Flow Duration Curve (FDC). Based on these results, the Way Besai Hydroelectric Power Plant is projected to have a generated power of 9.2 MW and an annual energy of 67.513 GWh resulting from the utilization of an effective water head of 67.45 m and a maximum plant discharge of 16.5 m3/second.
Co-Authors Bachtiar Rifai Bennuwardana, Nengah Firmansyah Firmansyah Gentio Harsono Jupriyanto Jupriyanto, Jupriyanto Khoirun Nisa KHOIRUN NISA Putro, Tri Guntoro Sukarno SHOLIHAH, TYAN HIDAYATUS Sukendra Martha Yosef Prihanto, Yosef