Judul: Analisis Gerombol Dampak Bencana Banjir di Indonesia Menggunakan Metode Self Organizing Maps
Abstrak: Terdapat fenomena kecenderungan meningkatnya bencana alam dalam tiga dekade terakhir di Indonesia. Lebih dari 4 miliar orang terkena dampak peristiwa alam yang ekstrem pada tahun 1980-2010. Sebagai negara yang luas, penting untuk membuat pemetaan wilayah sehingga dapat meminimalisir kerugian yang ditimbulkan oleh bencana salah satunya banjir. Data dampak bencana banjir yang bersumber dari BNPB dengan 514 kabupaten/kota di Indonesia digunakan pada penelitian ini. Metode yang dapat digunakan untuk mencapai tujuan ini adalah dengan analisis gerombol, salah satunya dengan metode Self Organizing Maps (SOM). Metode SOM memiliki kelebihan yaitu merupakan perangkat visualisasi dan analisis untuk data berdimensi tinggi dan dapat menangani pencilan peubah ganda. Penggerombolan 514 kabupaten/kota di Indonesia tahun 2021 berdasarkan 10 peubah menghasilkan 7 gerombol. Gerombol 1,4 dan 5 dikategorikan sebagai gerombol yang memiliki dampak bencana banjir terbesar. Dampak bencana pada Gerombol 1 (Banjar) didominasi oleh banyaknya korban dan kerusakan fasilitas. Gerombol 1 (Banjar) didominasi oleh banyaknya korban dan kerusakan infrastruktur dampak bencana banjir. Gerombol 4 (Bandung, Indramayu, Bekasi, Cilacap, Wonogiri, Pekalongan, Kota Pekalongan, Alor, Lembata, Flores Timur) didominasi oleh banyaknya korban dan kerusakan rumah dampak bencana banjir. Gerombol 5 (Bima, Sumba Timur, Kupang, Rote Ndao, Sabu Raijua, Malaka, Kota Kupang) didominasi oleh banyaknya korban dan kerusakan infrastruktur dampak bencana banjir., There has been a trend of increasing natural disasters in Indonesia over the past three decades. More than 4 billion people were affected by extreme natural events from 1980 to 2010. As a large country, it is important to map out regions to minimize the losses caused by disasters, one of which is flooding. Data on the impact of flood disasters sourced from BNPB, covering 514 regencies/cities in Indonesia, was used in this study. A method that can be used to achieve this goal is cluster analysis, one of which is the Self-Organizing Maps (SOM) method. The SOM method has the advantage of being a visualization and analysis tool for high- dimensional data and can handle multiple variable outliers. The clustering of 514 regencies/cities in Indonesia in 2021 based on 10 variables resulted in 7 clusters. Clusters 1, 4, and 5 are categorized as clusters with the greatest impact of flood disasters. The disaster impact in Cluster 1 (Banjar) is dominated by the number of victims and damage to facilities. Cluster 1 (Banjar) is dominated by the number of victims and infrastructure damage due to flood disasters. Cluster 4 (Bandung, Indramayu, Bekasi, Cilacap, Wonogiri, Pekalongan, Pekalongan City, Alor, Lembata, East Flores) is dominated by the number of victims and house damage due to flood disasters. Cluster 5 (Bima, East Sumba, Kupang, Rote Ndao, Sabu Raijua, Malaka, Kupang City) is dominated by the number of victims and infrastructure damage due to flood disasters.
Keyword: cluster,disaster, district/city, floods, SOM

Judul: Analisis Potensi Rawan (Hazard) dan Resiko (Risk) Bencana Banjir dan Longsor (Studi Kasus Provinsi Jawa Barat)
Abstrak: Trend disaster in Indonesia has increased from year to year. Hydro-meteorological disasters such as floods, droughts, landslides, cyclones and tidal waves are the dominant type of disaster in Indonesia. Hydrometeorological disasters occurred on average almost 70% of total disaster in Indonesia. West Java Province is one of the areas that have a high potential for the occurrence of landslides. This is due to the topography of the hilly and mountainous regions, as well high population density which puts pressure on the ecosystem. The purpose of this study is to establish the methodology in determining the criteria forming floods and landslides, determine the distribution of the occurrence of potentially vulnerable hazard areas and risk of floods and landslides, as well as determine the suitability of spatial pattern in the spatial plan of West Java Province Year 2010-2030 against potential floods and landslides hazard in the province of West Java. Floods and landslides potential hazard models were constructed through spatial analysis (overlay) with scoring and weighting system of the 7 parameters used, namely: land use, rainfall, slope, elevation, landform, soil type and geology. The model risk of floods and landslides were constructed by integrating the hazard map with the analysis of vulnerability, which consists of the parameters road/ accessibility, infrastructure and land use, as well as the analysis of the element of risk, which consists of a number of density parameters population (people/km2), GDP, land use, and emergency preparedness or response. The results showed that the area of West Java which has the potential flood-prone high is 460.204 ha (12,5%) and very high is 507.274 ha (13,8%), with distribution locations in Bekasi, Cirebon, Indramayu, Karawang, Majalengka, Subang, Bandung City, Banjar City, Bekasi City, Bogor City, Cirebon City and Depok City. The area with the potential of landslide-prone high is 141.855 ha (3,9%) and very high is 14.895 ha (0,4%), with distribution locations in Bandung dan Garut. The results of field validation and data recapitulation incidence of floods and landslides in the field with BNPB data (2010-2012), show that the accuracy of a map resulting from the analysis of potential hazard and risk of flooding and landslides are quite high. The frequency of floods in the field occurs 88 times as much as the class of potential flood hazard areas of moderate to very high with a total of 115 times the incidence of flooding, or by 76.5% of the total flood. While the frequency of landslides in the field occurs 86 times in the classes as potential landslide hazard moderate to very high with a total of 113 times the incidence of landslides, or 76.1% of the total landslide. There are only 5 spatial pattern with the high suitability of the potential flood-prone high: LNH-Tsunami Hazard (97,6 %), KB-Forest (77,7 %), Municipality (90,3 %), Paddy Field (96,5 %), and KB-Water Body (76,7 %). And only 2 spatial pattern with the high suitability of the potential landslide-prone high: Conservation Forest (86,8 %) and Primary Forest (80,2 %).
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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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