Judul: Pemetaan Daerah Rawan Banjir Berbasis Sistem  Informasi Geografis pada Kecamatan Kalideres Kota Jakarta Barat
Abstrak: Kecamatan Kalideres di Jakarta Barat, DKI Jakarta, sering dilanda banjir akibat meluapnya Kali Semongol yang melewati tiga kelurahan rawan banjir, yaitu Kelurahan Kamal, Kelurahan Tegal Alur, dan Kelurahan Pegadungan. Tujuan dari penelitian ini adalah mengetahui pengaruh faktor curah hujan, jenis tanah, kemiringan lereng, ketinggian lahan, tutupan lahan serta sungai terhadap peluang kejadian banjir, memetakan kawasan yang berpotensi banjir, serta mengidentifikasi daerah risiko banjir di Kecamatan Kalideres. Sistem Informasi Geografis (SIG) memungkinkan identifikasi cepat daerah rawan banjir melalui pemetaan menggunakan metode Weighted Overlay. Kecamatan Kalideres memiliki total penduduk sebanyak 449.998 jiwa, terdiri dari lima kelurahan, yaitu Kelurahan Kamal, Tegal Alur, Pegadungan, Kalideres, dan Semanan. Kelurahan Kalideres memiliki tingkat kerawanan banjir yang tinggi dengan luas 18,32 ha (0,65%) karena termasuk dalam kategori kritis dengan durasi terjadinya banjir selama 2 – 15 hari dan kedalaman banjir 0.5 – 3 m. Kelurahan Pegadungan memiliki risiko tertinggi dengan 106.914 jiwa terpapar dan kerugian ekonomi sekitar 16,15 milyar rupiah., The sub-district of Kalideres in West Jakarta, DKI Jakarta, is often affected by floods due to the overflowing of Kali Semongol, which passes through three flood-prone neighborhoods, namely Kamal, Tegal Alur, and Pegadungan. The purpose of this study is to determine the influence of factors such as rainfall, soil type, slope gradient, land elevation, land cover, and proximity to rivers on the likelihood of flooding, to map flood-prone areas, and to identify flood risk areas in Kalideres sub-district. Geographic Information System (GIS) enables rapid identification of flood-prone areas through mapping using the Weighted Overlay method. Kalideres sub-district has a total population of 449,998 people, consisting of five neighborhoods, namely Kamal, Tegal Alur, Pegadungan, Kalideres, and Semanan. The Kalideres neighborhood has a high flood vulnerability level with an area of 18.32 ha (0.65%) as it falls under the critical category with a flood duration of 2 – 15 days and a flood depth of 0.5 – 3 m. The Pegadungan neighborhood has the highest risk, with 106,914 people exposed and an estimated economic loss of around 16.15 billion rupiahs.
Keyword: flood, flood risk, flood vulnerability, GIS, mapping

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: Synthesis of Apatite - Chitosan Composite Using Duck Eggshell and Chitosan with Temperature and pH Control
Abstrak: Composite of apatite-chitosan was prepared by using chitosan as polymer matrix. Calcium phosphate was prepared from CaO and (NH4)2HPO4, which the ratio Ca : P had to be 1.67. Chitosan is produced by deacetilase from biopolymer chitin. Duck eggshell (95% CaCO3) as starting material was converted to be calcium oxide (CaO) through calcinations with temperature 1000oC for 5 hours. In-situ and ex-situ methods were prepared from apatite and chitosan (dissolved with acetate acid 2%). Calcium phosphate prepared for bone implantation, but it is too fragile and brittle to be implant into the body. So addition of chitosan can decrease crystalinity and increase mechanic characteristic (tougher). Composite apatite-chitosan was resulted by fast precipitation. Fast precipitation was held in a breaker glass with nitrogen atmosphere, under controlled temperature at 37oC and pH 7, in order to increase amount of hydroxyapatite. Precipitation with CaO which was dropped by (NH4)2HPO4. Hydroxyapatite and chitosan were appearing at samples with in-situ and ex-situ methods which indicating by peak matching of XRD (closed lattice parameter, crystal size), overlapping at FTIR spectra and supporting by SEM picture (homogenous and agglomerated particle). However, it still needs further research to examine biocompatibility osteoconductive degree of sample by in-vivo and in-vitro test.
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