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All Journal Jurnal Teknologi Perikanan dan Kelautan Geoplanning : Journal of Geomatics and Planning Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse)
Abrar, Camelia Batun
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering

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Mapping Landslide Vulnerability using Machine Learning Approach along the Taba Penanjung-Kepahiang Road, Bengkulu Province Abrar, Camelia Batun; Lubis, Ashar Muda; Fadli, Darmawan Ikhlas; Akbar, Arya J; Samdara, Rida
Geoplanning: Journal of Geomatics and Planning Vol 11, No 1 (2024)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.11.1.43-56

Abstract

Landslides occur when masses of rock, debris or soil move due to various factors and processes that cause land movement. The Taba Penanjung-Kepahiang route is one of the areas in Bengkulu Province that is highly prone to landslides. This causeway is the only fastest land route connecting the Bengkulu-Kepahiang area. In recent years, the road area has often been cut off due to landslides and fallen trees, which have caused road access to be cut off and obstructed and claimed lives. This study uses a Machine Learning (ML) and GIS approach with Variable Frequency Ratio using 16 independent factors obtained from the spatial database and DEM, which correlate with landslide events. This research aims to gain an in-depth understanding of the factors that cause landslides. In addition, the research focus is the development of a Disaster Mitigation Model to design and implement effective strategies to reduce the risk and impact of landslide disasters through in-depth analysis The dependent factor is the location of the landslide from the historical landslide area for the last five years, with a distribution of 70/30%. Furthermore, frequency ratio is used to analyze the correlation between conditioning factors and historical landslides. Then, the independent and dependent factors were normalized to create a landslide susceptibility map. Frequency Ratio (FR) indicates the likelihood of an event occurring, with drainage density (FR= 0.69), shear wave velocity (Vs30) (FR= 0.66), slope (FR= 0.60), and rainfall (FR= 0.55).  The output of the processed data is in the table below.
Climate Change Impact on Temperature, Rainfall, and Humidity in Batang Toru, South Tapanuli Siregar, Anjeli Agustina; Berliani, Riska; Abrar, Camelia Batun; Suhendra, Suhendra; Lizalidiawati, Lizalidiawati
Journal of Ocean, Mechanical and Aerospace -science and engineering- Vol 69 No 1 (2025): Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse)
Publisher : International Society of Ocean, Mechanical and Aerospace -scientists and engineers- (ISOMAse)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36842/jomase.v69i1.526

Abstract

Batang Toru is a sub-district in South Tapanuli Regency that is vulnerable to climate change due to forest conversion to gold mining. This is thought to be the cause of climate change in Batang Toru. This study aims to determine climate variability due to the influence of gold mining in Batang Toru. This research can provide useful information for designing policies, reducing risks, and improving operational sustainability at the Batang Toru mine. The data used are monthly mean temperature, rainfall, and humidity data for 5 years before and after mining operations (1992-1996 and 2018-2022) obtained from BMKG FL Tobing Meteorological Station and NASA. The methods used are descriptive, quantitative, and correlation analysis of temperature, rainfall, and humidity data. Data processing uses Panoply software to create 2D distribution maps and Microsoft Excel to see the time series of each data. The results showed that temperature variability increased by 0.53°C. Batang Toru's rainfall variability is of the equatorial type, with peaks occurring in October and April. The average humidity value for the last 5 years was 84.88% and previously it was 82.88%. Based on the results of the study, it is known that the impact of gold mining operations has greatly affected climate variability in Batang Toru.
ACCUMULATION OF LEAD AND COPPER IN THE SEDIMENTS IN SOUTH KALIH AND PANJANG ISLAND, BANTEN: AKUMULASI TIMBAL DAN TEMBAGA PADA SEDIMEN DI PERAIRAN PULAU KALIH SELATAN DAN PULAU PANJANG, BANTEN Nazwasyawinka, Keyla; Nurjanah, Siti; Abrar, Camelia Batun; Amalia Nasution, Isra; Dida, Eki Naidania; Sasongko, Agung Setyo; Cahyadi, Ferry Dwi; Cahyarini, Sri Yudawati
Jurnal Teknologi Perikanan dan Kelautan Vol 16 No 4 (2025): NOVEMBER 2025
Publisher : Fakultas Perikanan dan Ilmu Kelautan, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24319/jtpk.16.395-405

Abstract

South Kalih and Panjang Islands are located in Banten Bay, small island with environmental conditions adjacent to the center of industrial activities. Industrial activities near the waters can increase the risk of heavy metal pollution, thereby affecting the quality of the aquatic environment. This study aims to evaluate the condition of aquatic environmental quality based on heavy metal content in sediments. Sediment sampling was conducted at ten observation stations using a purposive random sampling method. Heavy metal analysis was performed using the Flame Atomic Absorption Spectrometry (FAAS). The results indicate that South Kalih Island accumulated more Pb heavy metals with an average of 2.7922 mg kg⁻¹, while the highest accumulation of Cu heavy metals was on Panjang Island with an average of 5.7188 mg kg⁻¹. The accumulation of heavy metals Pb and Cu in the sediments in South Kalih and Panjang Island was below the standard threshold, except at PPS5P1 of Panjang Island, where Cu concentrations exceeded the CCME (2002) quality guideline. Areas with dense anthropogenic activities are more likely to increase the accumulation of heavy metals in the waters.
Co-Authors Agung Setyo Sasongko Akbar, Arya J Amalia Nasution, Isra Ashar Muda Lubis Berliani, Riska Dida, Eki Naidania Fadli, Darmawan Ikhlas Ferry Dwi Cahyadi Lizalidiawati Lizalidiawati Nazwasyawinka, Keyla Rida Samdara Siregar, Anjeli Agustina Siti Nurjanah Sri Yudawati Cahyarini Suhendra Suhendra