Judul: Application of Geographic Information System for Determining Priority Areas for Flood Handling and Evacuation Paths for Flood Victims (Case Study: Alalak District, Barito Kuala Regency, South Kalimantan Province)
Abstrak: Akibat dari bencana banjir pada Januari 2021 banyak penduduk Kecamatan Alalak yang perlu dievakuasi dengan cepat dan aman menuju tempat pengungsian. Tujuan dari penelitian ini adalah mengetahui daerah rawan banjir, menentukan daerah prioritas banjir, mengidentifikasi sebaran lokasi evakuasi banjir, dan memberi rekomendasi jalur evakuasi. Metode penelitian menggunakan pendekatan deskriptif kuantitatif. Pengolahan data berbasiskan data spasial dengan menggunakan komponen Sistem Informasi Geospasial (SIG). Analisis daerah rawan banjir mengacu pada SNI 8197:2015. Penentuan daerah prioritas banjir dilakukan dengan meng-overlay hasil analisis rawan banjir dengan data kependudukan. Perencanaan jalur evakuasi menggunakan network analyst dengan memanfaatkan hasil analisis daerah rawan banjir untuk menentukan sebaran lokasi evakuasi. Hasil penelitian ini menunjukkan Kelurahan Handil Bakti dan Desa Semangat Dalam menjadi daerah prioritas banjir karena masuk prioritas 1. Berdasarkan pemerosesan network analyst, dihasilkan 20 jalur evakuasi di Kelurahan Handil Bakti yang menghubungkan 20 jalur evakuasi dengan dua titik pengungsian dan dihasilkan lima jalur evakuasi di Desa Semangat Dalam yang menghubungkan lima titik kumpul dengan satu titik pengungsian., As a result of the flood disaster in January 2021, many residents of the Alalak sub-district need to be evacuated quickly and safely to a refugee camp. This study aims to identify flood-prone areas, determine priority areas for flooding, identify the distribution of flood evacuation locations, and provide recommendations for evacuation routes. The research method uses a quantitative descriptive approach. Data processing is based on spatial data using the Geospatial Information System (GIS) components. Analysis of flood-prone areas refers to SNI 8197:2015. Determination of flood priority areas is done by overlaying the results of the flood-prone study with population data. Evacuation route planning uses a network analyst by utilizing the results of an analysis of flood-prone areas to determine the distribution of evacuation locations. The results of this study indicate that Handil Bakti Village and Semangat Dalam Village are priority flood areas because they are prioritized 1. Based on network analyst processing, 20 evacuation routes are generated in Handil Bakti Village, which connects 20 evacuation routes with two evacuation points, and five evacuations route in Semangat Dalam Village, which combines five assembly points with one evacuation point.
Keyword: Banjir, Daerah prioritas, Jalur Evakuasi

Judul: Analysis of Flood Prone Areas in the Krukut Watershed Based on Geographical Information Systems
Abstrak: Indonesia merupakan negara yang sering mengalami bencana alam seperti banjir. Banjir dapat berdampak pada kehidupan sosial, ekonomi, kerusakan material, kerusakan lingkungan dan kerusakan warisan budaya. Penanggulangan banjir perlu dilakukan untuk mengurangi dampak banjir yang begitu merugikan. Penanggulangan banjir dapat dilakukan dengan memetakan daerah rawan banjir dengan kajian Sistem Informasi Geografis (SIG) menggunakan perangkat lunak ArcGIS. Metode penelitian berupa metode deskriptif yang terdiri dari pengumpulan data, pengolahan data awal dan data lanjutan. Proses identifikasi wilayah rawan banjir menggunakan metode skor (scoring). Faktor yang mempengaruhi kerawanan adalah faktor curah hujan, kemiringan lereng, sungai dan tutupan lahan, jenis tanah dan ketinggian lahan. Berdasarkan hasil skor, Jakarta Pusat memiliki kelas kerawanan banjir kategori rendah seluas 846.03 ha (17.89%), kelas kerawanan banjir sedang seluas 3886.17 ha (82.11%). Jakarta Selatan memiliki kelas kerawanan banjir rendah seluas 4920.99 ha (35.67%) dan kelas kerawanan banjir sedang seluas 8874.90 ha (64.33%)., Indonesia is a country that often experiences natural disasters such as floods. Floods can have an impact on social, economic life, material damage, environmental damage, and damage to cultural heritage. Flood countermeasures need to be done to reduce the adverse effects of flooding. Flood countermeasures can be done by mapping flood-prone areas using Geographic Information System (GIS) of ArcGIS software. The research method is a descriptive method consisting of data collection, initial data processing, and advanced data. The process of identifying flood-prone areas uses the scoring method. Factors that influence vulnerability are rainfall, slope, river and land cover, soil type, and land elevation. From scoring result, Central Jakarta has a moderate category of flood hazard category was 846.03 ha (17.89%), and a high flood hazard class was 3886.17 ha (82.11%) . South Jakart has a low flood hazard class in South Jakarta is 4920.99 ha (35.67%), and the moderate flood hazard class is 8874.90 ha (64.33%).
Keyword: Arcgis, food prone, GIS, overlay

Judul: Characterizations of low alloy steel sae 4422  plated with chromic acid (Cro3)
Abstrak: Characterizations of low alloy steel SAE 4422 plated with chromic acid (CrOrO3) was use Optical Microscopy (OM), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), RD),Energy Dispersive Analysis of X-Ray (EDAX), Hardness Test and Roughness Test. Microstructures analysis exhibits cracks and grain boundaries microcracks as a characteristics of chrome metal found at plating metal. Perlite and Ferrite as grains of steel found at base metal with grain boundaries around it. Phase analysis of plating metal appropriate to chrome metal with lattice constant (a) is 2.559 Å and phase analysis of base metal appropriate to iron ferrite with lattice constant (a) is 3.318 Å. Both plating and base metal have cubic system. Chemical analysis of plating metal at surface section exhibits that cracks area have highest value of carbon element compare with grains and grains boundaries area. While chemical analysis of base metal at cross section exhibits that perlite have highest value of carbon element compare with ferrite and grain boundaries. The hardness value of plating metal at surface section and cross section are 753 and 637 VHN. While, the hardness value of base metal and interface area at cross section are 205 and 373 VHN. The roughness value at measurement points of chrome surface for as received sample are 0.445 μm. Observation used Optical Microscopy and Scanning Electron Microscopy exhibits surface irregularities combine to form surface texture of plating metal at surface section.
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