Judul: Peta Rawan Longsor di Wilayah Bogor
Abstrak: Longsor dapat menjadi bencana yang menimbulkan korban jiwa dan kerusakan harta benda, oleh karena itu dibutuhkan informasi sebaran area rawan longsor. Informasi sebaran areal rawan longsor umumnya disajikan dalam bentuk peta wilayah rawan longsor, dan terdapat metode-metode pemetaan wilayah rawan longsor yang menggunakan pendekatan pemetaan yang berbeda. Penelitian ini bertujuan untuk mengetahui keandalan hasil pemetaan area rawan longsor di wilayah Bogor dengan metode Paimin et al. (2006) yang dimodifikasi. Keandalan metode ini dievaluasi menggunakan data kejadian longsor selama tahun 2015 – 2019 di wilayah Bogor dan perbandingan dengan peta Zona Kerentanan Gerakan Tanah (ZKGT) (PVMBG 2016). Hasil penelitian ini menunjukkan bahwa metode pemetaan Paimin et al. (2006) menunjukkan sebagian besar wilayah Kabupaten Bogor dan Kota Bogor berada dalam kategori “Agak Rentan” masing-masing 71% dan 92% luas wilayah Kabupaten dan Kota Bogor. Selain itu, Peta Rawan Longsor metode Paimin et al. (2006) yang dimodifikasi dianggap lebih andal dibanding Peta ZKGT (PVMBG 2016) yang ditunjukkan dengan kesesuaiannya dengan jumlah kejadian longsor periode 2015 – 2019. Hal ini diduga akibat adanya perbedaan jumlah dan jenis parameter yang digunakan., Landslide can be a disaster that inflict casualties and property damage. Therefore, an information of landslide-prone areas is needed. Generally, informations about the landslide-prone areas is usually available in the form of Landslide-prone Area Map and there are some mapping methods that use different approach. This research aims to know the reliability of mapping landslide-prone areas in the Bogor region using modified method of Paimin et al. (2006). To evaluate the reliability of this method, landslide records from 2015 - 2019 in Bogor area as well as Peta Zona Kerentanan Gerakan Tanah (PVMBG 2016) were used as the comparative map. The results using method of modified Paimin et al. (2006) shows the majority of Bogor region is in “Agak Rentan” category, with 71% for Bogor Regency and 92% for Bogor City. Also, the map with modified method of Paimin et al. (2006) is considerd more reliable than Peta ZKGT (PVMBG 2016) which shown by its match with landslide records from year 2015 – 2019. This though to be the results of different numbers and types of parameters that employed between modified method of Paimin et al. (2006) and Peta ZKGT (PVMBG 2016).
Keyword: Bogor, Landslide Disaster, Landslide-prone Area, Mapping

Judul: Pemetaan Zona Rawan Longsor di Kabupaten Bogor Menggunakan Analisis Sistem Informasi Geografis
Abstrak: Tanah longsor merupakan salah satu kejadian alam yang terjadi di wilayah pegunungan, terutama di musim hujan. Kabupaten Bogor merupakan salah satu daerah dengan kondisi topogorafi dataran tinggi hingga pegunungan yang dapat menyebabkan terjadinya banyak bencana longsor sepanjang tahunnya. Peta daerah rawan bencana longsor merupakan salah satu cara dalam melaksanakan mitigasi bencana untuk mengurangi dan meminimalisir kejadian longsor dan akibat dari kejadian longsor. Penelitian ini bertujuan untuk memetakan daerah rawan longsor di Kabupaten Bogor menggunakan analisis sistem informasi geografis berdasarkan parameter dan faktor-faktor yang memengaruhi terjadinya longsor. Metode yang digunakan adalah analisis skoring dan pembobotan yang dilakukan menggunakan sistem informasi geografis. Adapun faktor-faktor yang berpengaruh dalam terjadinya longsor yang digunakan dalam penelitian ini yaitu kemiringan lereng, curah hujan, penggunaan lahan, dan jenis tanah. Hasil penelitian menunjukkan sebagian besar wilayah Kabupaten Bogor masuk dalam kelas klasifikasi kelas sedang dengan luas wilayah 140676,53 ha atau 47,63% dari total wilayah Kabupaten Bogor. Sedangkan kelas yang paling rendah adalah kelas sangat rendah dengan hanya 238,5 ha atau 0,08% dari wilayah Kabupaten Bogor., Landslide is one of the natural occurrences that happen in mountainous regions, especially during the rainy season. Bogor Regency is one of the areas with highland to mountainous topography, which can lead to numerous landslide disasters throughout the year. The landslide-prone area map is one of the ways to implement disaster mitigation to reduce and minimize the occurrence and impacts of landslides. This study aims to map the landslide-prone areas in Bogor Regency using geographic information system analysis based on parameters and factors influencing landslides. The method used is scoring and weighting analysis conducted through geographic information systems. The influencing factors in landslides used in this research are slope inclination, rainfall, land use, and soil type. The research results show that a significant portion of Bogor Regency falls into the moderate classification class, covering an area of 140,676.53 hectares or 47.63% of the total area of Bogor Regency. Meanwhile, the lowest class is the very low class, covering only 238.5 hectares or 0.08% of Bogor Regency's area.
Keyword: Disaster Mitigation, GIS, Landslide, Mapping

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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