Judul: Modeling Spasial Kerentanan Longsor. (Studi Kasus Di Propinsi Jawa Barat, Indonesia).
Abstrak: Indonesia sering terkena tanah longsor yang disebabkan oleh hujan dan gempa bumi. Selama periode tahun 1981-2007, frekuensi kejadian longsor tahunan bervariasi dengan rata-rata 49 kejadian per tahun. Ini dilaporkan oleh (Chrisanto et al., 2008). Ada juga informasi berdasarkan katalog global yang telah disajikan oleh (Kirschbaum et al., 2009) di mana pada tahun 2003 dan 2007-2009 ada laporan kejadian 97 tanah longsor di Indonesia yang mengakibatkan 872 kerusakan. Juga dalam periode 2011-2012, di mana pada tahun 2011 ada sekitar 29 kejadian yang terjadi di Jawa Barat. Dan pada tahun 2012, hampir seluruh daerah di Indonesia mengalami longsor tanah akibat intensitas curah hujan yang tinggi dan sistem tektonik yang aktif pada saat itu (Badan Geologi, 2011, 2012). Jumlah kematian di Indonesia yang disebabkan oleh tanah longsor juga tinggi. Penelitian yang dilakukan oleh (Petley, 2007) menunjukan bahwa pada tahun 2007, jumlah total korban jiwa yang disebabkan oleh tanah longsor di Indonesia sendiri adalah 465 jiwa ini angka merupakan tertinggi kedua disamping China. Karena tingginya kejadian tanah longsor dan jumlah korban jiwa akibat longsor, ada kebutuhan dari strategi mitigasi di Indonesia untuk mencegah bencana longsor di masa depan. Salah satu strategi mitigasi adalah pemetaan kerentanan longsor. Penelitian ini bertujuan untuk mengembangkan metode permodelan spasial dalam kerentanan longsor yang dapat menemukan area kerentanan longsor berdasarkan analisis data. Hasil penelitian dapat menunjukan faktor-faktor utama penentu kejadian longsor di wilayah penelitian, memprediksi area yang rawan longsor, dan menghasilkan peta kerentanan area yang rawan longsor dalam daerah penelitian. Penelitian ini dilakukan di wilayah dengan batas administrasi meliputi 4 kabupaten di Jawa Barat, yaitu Kabupaten Cianjur, Kabupaten Bandung Barat, Kabupaten Bandung, dan Kabupaten Garut. Wilayah penelitian ini dipilih karena wilayah dengan karakteristik pegunungan di Propinsi Jawa Barat merupakan daerah yang paling besar dengan kemungkinan terjadinya longsor. Bahan yang digunakan dalam penelitian ini adalah peta digital dalam format vektor meliputi peta penggunaan lahan/ tutupan lahan, peta jenis tanah, peta geologi, peta jenis iklim, peta curah hujan tahunan, peta landsystem, peta sungai, dan data longsor. Alat yang digunakan dalam penelitian ini adalah komputer, software GIS, software statistik SPSS, Microsoft office (MS Word, dan MS Excel), dan GPS. Setiap faktor-faktor tanah longsor diberi skor berskala berdasarkan korelasi masing-masing faktor dengan kepadatan longsor. Metode yang digunakan dalam analisis ini adalah analisis regresi dan analisis korelasi dalam menentukan faktor yang harus di analisis, dan Principal Component Analysis (PCA) dalam menentukan bobot masing-masing faktor. Dari 9 faktor tanah longsor yang dipilih untuk analisis, berdasarkan hasil penentuan bobot, komponen utama 1 sampai komponen utama 8 dapat menjelaskan 96% dari total varian data. Komponen ini juga memberikan hasil akurasi keseluruhan terbaik untuk kelas kerentanan yang dibagi dalam 3 kelas sebesar 68.20%. Persamaan matematika yang diperoleh dalam penelitian ini adalah: Landslide Susceptibility Index (LSI) = 0.231 * Penggunaan/Tutupan Lahan + 0.188 * Kemiringan Lereng + 0.112 * Jarak Terhadap Sungai + 0.107 * Tipe Jenis Tanah + 0.100 * Curah Hujan Tahunan + 0.073 * Kepadatan Penduduk + 0.068 * Umur Geologi + 0.066 * Tipe Iklim + 0.054 * Geomorfologi. Hasil penentuan bobot menyimpulkan pangkat setiap faktor dalam kontribusi terhadap kejadian longsor di wilayah penelitian. Berdasarkan penentuan bobot, faktor
Keyword: Kerentanan Longsor, Modeling Spasial, PCA, Propinsi Jawa Barat

Judul: Modeling Spasial Kerentanan Longsor. (Studi Kasus di Propinsi Jawa Barat, Indonesia).
Abstrak: Indonesia is frequently affected by landslides caused by both rainfall and earthquakes. During the period 1981-2007 the annual landslide frequency varies with an average of 49 events per year this was reported by (Chrisanto et al., 2008). There is also information from the global catalogue presented by (Kirschbaum et al., 2009) where in the years 2003 and from 2007 to 2009 there were reports 97 landslides in Indonesia, which produced 872 casualties. Also within the period of 2011-2012 where in 2011 there was about 29 events in West Java alone and in 2012 almost all of regions in Indonesia had a landslide event due to the high intensity of rainfall and active tectonic systems in that year. (Geological Agency, 2011 & 2012). Fatalities in Indonesia caused by landslides were also high. Study done by (Petley, 2007) showed that in 2007, total number of fatalities caused by landslides in Indonesia alone was 465 which was the second highest next to China. Due to the high occurrences of landslides and the number of fatalities, there is a need of mitigation strategies in Indonesia to prevent future landslide disasters. One of the mitigation strategy is to provide landslide susceptibility mapping. This research aims into developing a spatial modeling method in landslide susceptibility that can find landslide susceptibility area based on the data being analyzed. The result of the research can also observe the main factors that supports the events of landslides; predict the areas that are prone to landslides; and generate landslide susceptibility map of the areas that are prone to landslides. This research is done within 4 regencies in West Java Province which are Cianjur Regency, West Bandung regency, Bandung Regency, and Garut Regency. The area of this research is chosen because of the characteristic that is mountainous in the West Java Province which is the characteristic where landslides most likely occur in West Java. The materials used in this research is digital maps in vector format that is Landuse/Landcover Map, Soil Type Map, Geology Map, Climate Type Map, Annual Rainfall per Year Map, Landsystem Map, River Map, and Landslide Data. The tools used in this research are Personal Computer, GIS Software, Statistic Software (SPSS), Microsoft Office (MS Word, and MS Excel), and GPS. The factors were given rescaled scores based on the correlation between the landslide densities. The methods used in this analysis were regression analysis and correlation analysis in determining the factors to be analyzed and Principal Component Analysis (PCA) in determining the weight of each factors. From the 9 factors of landslide chosen for the analysis, based on the result of the weight determination, principal component 1 until principal component 8 which explained 96% of the total variance of the data gave the most accurate overall accuracy result for 3 susceptibility class at 68.20%. The mathematical equation obtained from this model: Landslide Susceptibility Index (LSI) = 0.231 * Landuse/Landcover + 0.188 * Slope + 0.112 * Distance to River + 0.107 * Soil Type + 0.100 * Annual Rainfall + 0.073 * Population Density + 0.068 * Geology Age + 0.066
Keyword: Landslide Susceptibility, PCA, Spatial Modeling, West Java, Rainfall, Geology Map, Scoring Development, Earth Qualies, Natural Resources

Judul: Synthesis of Molybdenum Trioxide (MoO3) by Electrochemical Method for Electrochromics Application
Abstrak: Molybdenum trioxide (MoO3) thin films have been deposited on glass substrates by electrochemical method using ammonium heptamolybdate tetrahydrate ((NH4)6Mo7O244H2O). The films were deposited onto glass substrates as the control temperature at 25○C and annealing treatment at 350○C for 30 mins. The MoO3 thin films were investigated by UV-Vis, X-ray diffraction techniques (XRD), Scanning Electron Microscopy (SEM). The JCPDS card show that orthorhombic MoO3 (α- phase) has been formed. Molybdenum trioxide MoO3 formation was also confirmed by JCPDS card no. 35-0609. The SEM photographs revealed that the spherical and rod-like morphology and their grains size increased with increasing of heating temperatures. The measurement results show that the MoO3 thin film prepared at 350°C transmited about 80% of the visible spectrum. The effect of different heat treatments on surface morphology, thickness and optical properties of the films are discussed in this thesis.
Keyword: Institut Pertanian Bogor, Bogor Agricultural University, IPB, Electrophoretics, electrodeposide, electrochromics, electrochromic materials, electrochromic mechanism