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All Journal Jurnal Ilmu dan Teknologi Kelautan Tropis JURNAL PENDIDIKAN, SAINS DAN TEKNOLOGI Maritime Park: Journal Of Maritime Technology and Socienty
Al Hakim, Muhammad Abdul Ghofur
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Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Environmental Science Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

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DETEKSI TURBIDITY FRONT MENGGUNAKAN CITRA SATELIT SENTINEL-2 HUBUNGANNYA DENGAN OSEANOGRAFI DI ESTUARI BENGAWAN SOLO Susilo, Setyo Budi; Gaol, Jonson Lumban; Al Hakim, Muhammad Abdul Ghofur
Jurnal Ilmu dan Teknologi Kelautan Tropis Vol. 14 No. 3 (2022): Jurnal Ilmu dan Teknologi Kelautan Tropis
Publisher : Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jitkt.v14i3.40172

Abstract

Estuari merupakan daerah percampuran antara massa air tawar dan air laut yang menyebabkan zat-zat di dasar perairan naik ke permukaan sehingga konsentrasi unsur hara menjadi tinggi. Penelitian mengenai pertemuan massa air estuari masih perlu dilakukan terutama terkait turbidity front estuary karena untuk mengetahui kemampuan citra Setinel-2 dalam mendeteksi turbidity front. Selama ini penelitian ini terbatas dari data in situ, oleh karena itu teknologi penginderaan jauh coba diterapkan untuk mendeteksi turbidity front estuary. Penelitian ini bertujuan untuk mengembangkan algoritma TSS lokal dan mendeteksi turbidity front berdasarkan citra satelit Sentinel-2. Metode penelitian ini menggunakan citra Sentinel-2 untuk mengetahui batas turbidity front berdasarkan TSS yang dibandingan dengan data in situ salinitas dan TSS sebagai validasi data. Hasil penelitian ini diketahui algoritma empiris yang diperoleh dari band ratio (merah/(biru+hijau+merah)) pada Sentinel-2 memiliki hasil yang terbaik dengan koefisien determinasi (R2) = 0,7409. Hasil citra satelit menunjukkan bahwa turbidity front estuary terjadi pada jarak 1,4 – 3 km, sedangkan pada data in situ terjadi pada jarak 2 – 4 km di muara Bengawan Solo. Terdapat perbedaan nilai TSS sebesar 1,9182 mg/L antara data in situ dengan citra satelit di daerah turbidity front estuary. Kondisi musim, curah hujan dan pasang surut memengaruhi konsentrasi dan jarak turbidity front dari muara sungai.
Machine Learning-Based Mapping of Mangrove Forest Changes from Sentinel-2 in Balikpapan Bay, East Kalimantan Al Hakim, Muhammad Abdul Ghofur; Sinurat, Maya Eria Br; Zulkifle, Nurul Ain Najwa; Nurmawati; Mas’ud M, Ahmad Azwar
Jurnal Ilmu dan Teknologi Kelautan Tropis Vol. 17 No. 3 (2025): Jurnal Ilmu dan Teknologi Kelautan Tropis
Publisher : Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jitkt.17.3.67707

Abstract

Balikpapan Bay contains extensive mangrove forests which play an important role as habitat for a range of species and in providing a range of ecosystem services. In recent years, the mangrove forests around Balikpapan Bay are increasingly being lost and degraded due to development pressures. Thus, change detection in mangrove ecosystem has become highly relevant, as it can provide essential information to support the conservation practices and coastal management. This study aims to map mangrove forest change in Balikpapan Bay, East Kalimantan over a five-year period from Sentinel-2 using machine learning. Five machine learning algorithms (Random Forest (RF), Support Vector Machine (SVM), Classification and Regression Tree (CART), K-Nearest Neighbors (KNN), and Minimum Distance), implemented on the Google Earth Engine platform, were evaluated to determine the most suitable method. The evaluation results indicate that RF, SVM, and CART yielded mangrove mapping accuracies of 80% or higher. Notably, the CART algorithm surpassed the other tested models, demonstrating the highest overall accuracy of 84% and a Kappa coefficient of 0.78. Mapping using the selected CART model shows that, between 2020 and 2025, mangrove areas in Balikpapan Bay decreased by 21% (2,906.17 ha). Approximately 97% (2,834.49 ha) of this loss is concentrated in the North Penajam Paser, which has a high rate of land conversion to built-up areas.
Probabilistic Evaluation of Seawall Performance Against Wave Run-Up and Overtopping Under Variable Water Levels at Serui Fuel Terminal Mas'ud M, Ahmad Azwar; Paotonan, Chairul; Sitorus, Chris Jeremy Verian; Al Hakim, Muhammad Abdul Ghofur
Maritime Park: Journal of Maritime Technology and Society Volume 5, Issue 1, 2026
Publisher : Department of Ocean Engineering, Faculty of Engineering, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62012/mp.vi.48184

Abstract

Seawalls are one of the coastal protection structures commonly used to reduce the risk of wave overtopping, especially in critical coastal infrastructure. At the Fuel Terminal in Serui, overtopping events have been recorded causing damage to several facilities, even under moderate wave conditions. This study evaluates the performance of the existing seawall under the combined influence of probabilistic waves (H2%, H10%, H33%) and sea level variations (MSL and HWL). A 20-year wave dataset (2002–2021) obtained from ECMWF was statistically analyzed, followed by theoretical wave transformation toward the shoreline. Wave run-up was calculated based on the Iribarren-type formulation and empirical equations, in which the 2% exceedance run-up (R2%) was estimated using the probabilistic extreme wave height (H2%) following established empirical correlations for smooth seawalls. Overtopping discharge was estimated using an exponential formula and compared with established overtopping impact classifications. Results indicate that under High Water Level (HWL) conditions, all run-up values exceeded the seawall crest elevation (+1.93 m relative to MSL), with R2% reaching 3.3 m and a maximum overtopping discharge of 92 l/s/m, corresponding to a high functional damage risk. Wave overtopping does not compromise the structural integrity of the seawall but can cause significant functional damage to facilities and operation behind the wall. Even under MSL conditions, overtopping still occurred for extreme wave conditions (H2%), These results are consistent with field observations in 2020, confirming that the existing seawall geometry and smooth surface contribute to limited wave energy dissipation. Unlike conventional deterministic assessments, this study introduces a probabilistic and field-validated evaluation framework that integrates run-up and overtopping analysis under varying water levels, providing a more realistic basis for assessing seawall performance for future adaptive redesign strategies.
ANALISIS PERUBAHAN LUAS HUTAN MANGROVE MENGGUNAKAN METODE NDVI (NORMALIZED DIFFERENCE INDEX) DI KECAMATAN BALIKPAPAN BARAT KOTA BALIKPAPAN Sahdian, Iitra Achbar; Keliwar, Khairi Ahza Hail; Luthfi Saud, Muhammad Nur Ibnu; Al Hakim, Muhammad Abdul Ghofur; Nugroho, Bayu Ashari; Kholifah, Puspa Indah Nur; Safitri, Rosita Dewi
PENDIDIKAN SAINS DAN TEKNOLOGI Vol 12 No 4 (2025)
Publisher : STKIP PGRI Situbondo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47668/edusaintek.v12i4.2130

Abstract

Mangrove ecosystems are a crucial component of coastal areas, serving both strategic ecological and economic functions; however, their existence is vulnerable to human activities and the dynamics of coastal environments. The Balikpapan Barat subdistrict is one of the areas in Balikpapan City that features various types of activities, including settlements, industrial activities, and port activities, which have the potential to impact the condition of the mangrove forests. This study aims to analyse changes in the area and density of mangrove forests in 2019 and 2025 using the Normalised Difference Vegetation Index (NDVI) method based on Sentinel-2A satellite imagery. The research method comprises three stages: image pre-processing, NDVI value calculation, and classification of mangrove density into three classes: low, medium, and high. The analysis results indicate a decline in the distribution area of mangroves in West Balikpapan District, primarily due to anthropogenic activities such as infrastructure development, settlement expansion, and coastal industrial activities. However, some areas still exhibit moderate to high vegetation density, indicating the presence of natural regeneration processes and the role of conservation areas in maintaining mangrove ecosystems. This study confirms that the use of remote sensing imagery and the NDVI method is effective in supporting spatial and sustainable mangrove monitoring, and can serve as a basis for planning the management and conservation of mangrove ecosystems in coastal areas.Keywords: mangrove, NDVI, Sentinel-2, Area, Density, West Balikpapan.
Co-Authors Chairul Paotonan Chris Jeremy Verian Sitorus Jonson Lumban Gaol Keliwar, Khairi Ahza Hail Kholifah, Puspa Indah Nur Luthfi Saud, Muhammad Nur Ibnu Mas'ud M, Ahmad Azwar Mas’ud M, Ahmad Azwar Maya Eria Br Sinurat, Maya Eria Br Nugroho, Bayu Ashari Nurmawati Safitri, Rosita Dewi Sahdian, Iitra Achbar Setyo Budi Susilo Zulkifle, Nurul Ain Najwa