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All Journal Jurnal Medika Malahayati Socius (Jurnal Pendidikan dan Pembelajaran Ilmu Pengetahuan Sosial) (Edisi Elektronik)
Wicaksana, Muhammad Akbar
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Biochemistry, Genetics & Molecular Biology Education Environmental Science Health Professions Immunology & microbiology Medicine & Pharmacology Public Health Social Sciences

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Ocular Manifestation In Marfan Syndrome: A Case Report Wicaksana, Muhammad Akbar; Sugiarti, Emmy Dwi
Jurnal Medika Malahayati Vol 8, No 3 (2024): Volume 8 Nomor 3
Publisher : Universitas Malahayati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/jmm.v8i3.14525

Abstract

Sindrom Marfan adalah gangguan kongenital autosomal dominan yang memengaruhi jaringan ikat dalam beberapa sistem. Kelainan pada protein fibrilin-1 dapat menyebabkan kelainan dalam beberapa sistem. Tujuan laporan ini adalah untuk mendokumentasikan manifestasi klinis pada pasien sistem okular dan tatalaksana pasien dengan sindroma marfan. Seorang pria berusia 26 tahun datang ke Rumah Sakit Mata Cicendo, dirujuk dari Unit Kardiologi di Rumah Sakit Hasan Sadikin, dengan keluhan utama penglihatan kabur sejak sekolah dasar. Saat pemeriksaan fisik, subluksasi lensa teramati di kedua mata terutama saat dilatasi pupil. Evaluasi biometrik mengungkapkan kornea yang relatif datar dengan panjang aksial yang panjang. Tajam penglihatan pasien membaik dengan kacamata. Pasien diberikan kacamata dan diberi edukasi tentang sifat progresif penyakit dan risiko pewarisan penyakit. Tidak semua pasien dengan sindrom Marfan yang mengalami gejala okular memerlukan intervensi bedah. Terapi non-bedah dapat membantu pasien mencapai ketajaman visual yang layak. Evaluasi sistemik dapat membantu pasien memahami dan mitigasi penyakit.
MODELING FOREST AND LAND FIRE VULNERABILITY IN BANJAR DISTRICT USING RANDOM FOREST CLASSIFICATION METHOD IN 2023 Wicaksana, Muhammad Akbar; Widayani, Prima; Windartono, Barandi Sapta
JURNAL SOCIUS Vol 14, No 2 (2025): JURNAL SOCIUS
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/js.v14i2.22935

Abstract

Forest and land fires are a major environmental concern in Banjar Regency, South Kalimantan, with a burned area of 1,812.80 ha recorded in 2023. This study aims to model fire susceptibility levels using the Random Forest algorithm based on remote sensing data. The data utilized include Landsat 8 imagery from 2023 with extracted spectral indices such as NDVI, NBR, NDWI, MSI, and BAI, along with fire hotspot data from the Banjar Regency Disaster Management Agency. The model was trained using data from June to mid-September and validated with data from mid-September to November 2023. Results indi-cate that the northern and central areas of Banjar Regency exhibit the highest fire susceptibility. The susceptibility map was categorized into five zones based on fire probability. Accuracy assessment using a confusion matrix yielded an overall accuracy of 71.64% and a Kappa coefficient of 40.81%. These findings demonstrate that the Random Forest method is effective in iden-tifying fire-prone areas with high efficiency and minimal input data. This model provides a valuable tool for spatially targeted fire prevention and mitigation planning.
Co-Authors Prima Widayani Sugiarti, Emmy Dwi Windartono, Barandi Sapta