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ABSTRAK
Karakteristik debit sangat penting dalam pengelolaan manajemen Daerah Aliran Sungai (DAS). Karakteristik debit adalah ciri atau sifat debit aliran sungai (Q). Penelitian ini bertujuan mengetahui pengaruh Karakteristik debit terhadap penggunaan tanah dan pola curah hujan secara spasial terhadap pola aliran atau debit. Metoda yang digunakan dalam penelitian ini adalah metoda survey dan analisa kuantitatif. Berdasarkan perhitungan Karakteristik debit aliran (Q) Daerah Aliran Ci Meta pada tahun 1991 ? 2006. Parameter debit rata-rata (MQ), debit tertinggi (MHQ), debit terendah (MNQ), dan koefisien runoff mengalami penurunan setelah 1998, sedangkan Qmin/Qmax mengalami kenaikan setelah 1998. Pengaruh penggunaan tanah digambarkan pada kejadian tahun 1994 dan 2002, dimana pada tahun 1994 koefisien runoff berada diatas nilai ratarata. Sedangkan pada tahun 2002 koefisien runoff berada di bawah nilai debit rata-rata dan mengalami penurunan Variabel curah hujan hulu dan curah hujan tengah berkorelasi dengan variable volume debit (Qvol) dan variabel debit maksimum (Qmax).

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ABSTRAK
Kabupaten Bantul merupakan salah satu daerah yang termasuk kategori rawan bencana gempa bumi di Propinsi Daerah Istimewa Yogyakarta. Kejadian gempa bumi terakhir tahun 2006 di daerah ini menimbulkan dampak yang luar biasa, yaitu korban jiwa, maupun kerusakan besar baik infrastruktur maupun bangunannya. Namun demikian, terdapat juga beberapa daerah yang mengalami kerusakan ringan akibat bencana gempa bumi tersebut. Tesis ini membahas mengenai analisis risiko gempa bumi dan variasi spasialnya di Kabupaten Bantul. Perhitungan risiko didasarkan pada fungsi perkalian antara bahaya (H) dan kerentanan (V) dibagi dengan ketahanan/kapasitas (C). Parameter bahaya yang dianalisis meliputi: nilai PGA (Peak Ground Acceleration), dan Struktur Sesar. Parameter kerentanan yang dianalisis meliputi: luas permukiman, panjang jaringan jalan, jenis batuan, jumlah penduduk, jumlah kepadatan penduduk, jumlah penduduk usia rentan, jumlah penduduk wanita, jumlah keluarga miskin, jumlah industri kecil/menengah, jumlah pasar dan jumlah pendapatan asli daerah (PAD). Parameter ketahanan/kapasitas yang dianalisis meliputi: jumlah fasilitas kesehatan, fasilitas umum berupa sekolah dan keberadaan sistem peringatan dini bencana. Hasil penelitian menunjukkan bahwa wilayah Kabupaten Bantul mempunyai variasi spasial tingkat risiko bencana gempa bumi dengan 3 kategori yaitu: risiko rendah, sedang dan tinggi. Secara umum Kabupaten Bantul didominasi oleh wilayah dengan tingkat risiko sedang/menengah. Wilayah dengan risiko tinggi terdapat dua variasi spasial yaitu di sepanjang sesar Opak dan sebagian mengelompok di bagian utara dekat dengan Kota Yogyakarta dan Bantul. Wilayah risiko tinggi tersebut umumnya dikarenakan memiliki tingkat kerentanan wilayahnya tinggi hingga sedang baik kerentanan fisik maupun sosial ekonominya, akan tetapi kapasitasnya rendah. Wilayah yang memiliki risiko paling tinggi meliputi desa Trimulyo, kemudian Sumberagung, dan Tamantirto. Wilayah yang mempunyai risiko paling rendah meliputi desa Jatimulyo, kemudian Terong dan Dlingo. Wilayah risiko rendah tersebut umumnya mempunyai tingkat kerentanan rendah baik fisik maupun sosial ekonominya, tetapi mempunyai kapasitas daerahnya tinggi.

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ABSTRACT
Bantul District is one of earthquake prone area in Yogyakarta Province. Last genesis earthquake on 2006 in this area past a tremendous impact, the loss of lives, substantial damage of infrastructures dan buildings. However, there are also some areas that suffered minor damage due to the earthquake disaster. This research is analyse the earthquake risk and its spatial variation in Bantul District. Risk calculation is based on multiplication function between Hazard (H) and Vulnerability (V) divided by the Capacity (C). Hazard parameters include in these analyzed: Peak Ground Acceleration (PGA) and Fault Structure. Vulnerability parameters include in these analyzed: the percentage of the settlement area, the length of road network, the lithology, number of population, number of density, the number of vulnerable population, number of females, the number of poor families, number of market, number of industrial, and number of economic income (PAD).Capacity parameters include in these analyzed: the number of health facilities, public facilities such as schools and early warning system of disaster in villages. The final result showed that The Bantul District has spatial variaton of earthquake risk in 3 categories: low risk, medium and high risk. The Bantul District is dominated by areas with medium risk. They have two spatial pattern of high risk, the areas were in line with Opak Fault and other area was near the city of Yogyakarta and Bantul. High risk area have three characteristics, high vulnerability of pyhsics and social economics, medium hazard, and low capacity. The areas of high risk are Trimulyo Village, Sumberagung and Tamantirto. The areas of low risk have three characteristic, low hazard, low vulnerability and high capacity. The low areas are Jatimulyo, Terong and Dlingo.

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Faktor hidrogeologi mempunyai tingkat perlindungan tertentu terhadap pencemaran airtanah, yang digunakan untuk menentukan masuknya pencemaran ke dalam airtanah. Tujuan penelitian adalah untuk mengetahui pola wilayah kerentanan airtanah dangkal statis dan dinamis terhadap pencemaran dengan menggunakan metode DRASTIC yang berbasis Sistem Informasi Geografis, dan mengetahui hubungan antara wilayah kerentanan airtanah dangkal dengan konsentrasi nitrat. Penentuan wilayah kerentanan airtanah dangkal dilakukan melalui analisis tumpang susun antara tujuh variabel DRASTIC dan penggunaan tanah. Sebagian besar wilayah kerentanan airtanah dangkal statis dan dinamis di Kecamatan Citeureup didominasi oleh wilayah dengan kerentanan sedang. Pola wilayah kerentanan airtanah dangkal baik statis maupun dinamis mengelompok di bagian selatan dan menyebar di bagian utara, serta cenderung semakin bertambah kelas kerentanannya di bagian tengah daerah penelitian. Konsentrasi nitrat sebagai salah satu pencemar airtanah tidak berasosiasi dengan wilayah kerentanan airtanah dangkal statis, tetapi berasosiasi dengan wilayah kerentanan airtanah dangkal dinamis di Kecamatan Citeureup.

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Penelitian ini dilakukan di Kota Administrasi Jakarta Selatan. bertujuan untuk mengetahui pola sebaran wilayah potensial resapan air tanah, serta mengetahui faktor-faktor yang dominan terhadap wilayah potensial resapan air tanah di Kota Administrasi Jakarta Selatan. Metodelogi penelitian ini dengan Grid System, diperoleh dari overlay yang akan menghasilkan Potensi Resapan Air Tanah. Sebaran keruangan Resapan Air Tanah di Jakarta Selatan di kategorikan menjadi tiga yaitu: a) sebaran wilayah potensi resapan rendah di Jakarta Selatan dominan terdapat di bagian utara atau mendekati pusat kota. kelurahan yang paling besar memiliki luasan tersebut adalah Kelurahan Tebet Barat dalam Kecamatan Tebet dengan luas 110,42 ha atau 0,75 %. b) Sebaran wilayah potensi resapan sedang di Jakarta Selatan dominan terdapat di bagian utara atau mendekati pusat kota. kelurahan yang paling besar memiliki luasan tersebut adalah Kelurahan Pondok Pinang dalam Kecamatan Kebayoran Lama dengan luas 660,22 ha atau 4,53 %. Sedangkan, c) sebaran wilayah potensi resapan tinggi di Jakarta Selatan dominan terdapat di bagian utara atau mendekati pusat kota. kelurahan yang paling besar memiliki luasan tersebut adalah Kelurahan Ragunan dalam Kecamatan Pasar Minggu dengan luas 50,63 ha atau 0,34 %. ...... The research was conducted at the South Jakarta Administration. aims to determine the distribution patterns of potential groundwater recharge areas, and determine the dominant factors of the potential groundwater recharge areas in South Jakarta Administration. This research methodology with Grid System, derived from the overlay that will generate Potential Groundwater Infiltration. Spatial Distribution of Soil Water Infiltration in South Jakarta categorized into three, namely: a) the distribution of low recharge potential areas in South Jakarta are dominant in the northern part of or close to the city center. The biggest urban area is the Village has the Western District of Tevet Tevet with area 110.42 ha or 0.75%. b) The distribution of the potential catchment area in South Jakarta was predominantly located in the northern part of or close to the city center. The biggest urban area is the Village has Pondok Pinang in Kebayoran Lama district with an area of 660.22 hectares or 4.53%. Meanwhile, c) distribution of high recharge potential areas in South Jakarta predominantly located in the northern part of or close to the city center. The biggest urban area is the Village has Ragunan the Sunday Market District with an area of 50.63 ha, or 0.34%.

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Keterbatasan tanah dengan semakin bertambahnya jumlah penduduk yang menghuninya harus ditangani dengan optimal agar fungsi tanah tetap dapat memakmurkan. Namun, dalam perkembangannya jumlah tanah terlantar semakin meningkat setiap tahunnya. Penelitian Persebaran Tanah Terlantar dilaksanakan di Kabupaten Sukabumi Provinsi Jawa Barat. Tujuan dalam penelitian ini adalah mengetahui pola persebaran tanah terlantar di Kabupaten Sukabumi dan menganalisis faktor-faktor yang berpengaruh terhadap terjadinya pola persebaran tanah terlantar di Kabupaten Sukabumi. Batasan konsep tanah terlantar berupa sebidang fisik tanah yang tidak digunakan sesuai dengan peruntukan tanahnya. Analisa keruangan dilaksanakan dengan menggabungkan Peta Peruntukan Tanah dengan Peta Penggunaan Tanah untuk mendapatkan ketidaksesuaian antara kawasan peruntukan dengan penggunaan tanah atau tanah terlantar. Setelah didapatkan pola persebaran tanah terlantar, selanjutnya dilakukan analisa spasial dan statistik mengenai faktor-faktor yang mempengaruhi pola persebaran tanah terlantar dilihat dari faktor kependudukan, aksesibilitas dan penguasaan tanah. Hasil penelitian menyimpulkan tanah terlantar di Kabupaten Sukabumi mempunyai pola mengelompok, mengarah ke wilayah tenggara mendekati perbatasan dengan Kabupaten Cianjur, yakni pada bentuk wilayah bergunung atau kemiringan lereng curam, jenis tanah yang peka terhadap erosi, dan curah hujan yang tinggi. Variabel yang paling besar hingga yang yang paling kecil pengaruhnya terhadap pola persebaran tanah terlantar secara berurutan adalah jarak ke ibukota kabupaten, pertumbuhan penduduk, profesi konstruksi, profesi pertanian, kepadatan penduduk, dan penguasaan tanah Negara dikuasai. ...... The people growth makes the limitation of the availability of lands. Thus, lands have to be managed optimally so the function of land to give the prosperity of people could be achieved. This research about the distribution of idle land was held in Kabupaten Sukabumi, West Java Province. The aim of the research is to know the distribution pattern of idle lands and analyze factors that effect to create distribution pattern of idle land. The limitation concept of idle land was a parcel of land that was not utilized according to its allocation. Spatial analyzation was used to integrate land allocation map with land use map to get incompability between the use and the allocation of land or idle land. After we got the pettern of idle land distribution, it was analyzed by using spatial analyzation and statistic to get factors that influenced the creation of idle lands from demography, accessibility and land tenure. The result of research showed that idle land in Sukabumi had an agglomerate pattern, approaching to southeastern area to boundary of Kabupaten Cianjur wich was mountainous area or steep slopes, lands on those areas were sensitive to erosion, and high rainfall. The most influenced variables to the less ones for the distribution pattern of idle lands sequentially were the distance to the capital of kabupaten, population growth, constructions occupation, agriculture occupation, population density and state land tenurship.

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Penelitian ini bertujuan untuk mengetahui pengaruh distribusi curah hujan dan karakteristik fisik setiap sub-DAS Ci Liwung Hulu yang terdiri dari topografi, jenis tanah dan penggunaan tanah terhadap debit aliran Daerah Aliran Ci Liwung Hulu. Metode yang digunakan adalah Soil Conservation Service (SCS) yang disimulasikan menggunakan model hujan-debit HEC-HMS yang di validasi menggunakan metode RMSE dan Nash. Hasil pengolahan data menunjukan bahwa karakteristik dan distribusi hujan setiap sub-DAS mempengaruhi besar kecilnya debit yang dihasilkan. Sub-DAS Ci Liwung (Tugu) merupakan sub-DAS yang menghasilkan sumbangan debit terbesar pada DA Ci Liwung Hulu pada kejadian banjir Tahun 2002 dan 2007. Berdasarkan hasil validasi, simulasi, data curah hujan radar cuaca memiliki nilai simpangan yang lebih kecil dibandingkan data curah hujan observasi. Penggunaan data radar cuaca memberikan gambaran distribusi hujan spasial dengan resolusi tinggi dan dapat digunakan untuk memprediksi debit aliran yang dihasilkan oleh suatu Daerah Aliran Sungai (DAS).

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This study aims to determine impact of rainfall distribution and physical characteristics in each sub-watershed towards run-off in the Upper Ci Liwung Watershed. It consist of topography , soil type and land use. The method utilizing Soil Conservation Service (SCS ) applied on HEC - HMS rainfallrunoff model and was validated using the RMSE and Nash. The results show that the physical characteristics and rainfall distribution of each sub-watershed has significant impact on the run-off in Upper Ci Liwung Watershed especially sub-watershed Ci Liwung ( Tugu) on the flood events of 2002 and 2007. Based on the simulation validation result, weather radar rainfall data has a deviation value smaller than rainfall data of observation . Weather radar data provide accurate rainfall measurements at high resolution and can be applied to predict run-off in watershed.

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[ABSTRAK
Pemanasan global telah mengakibatkan peningkatan air laut dan banjir rob yang melanda daerah dataran pantai termasuk Kota Jakarta yang merupakan pusat perekonomian Indonesia. Jakarta merupakan wilayah yang mengalami perkembangan pembangunan yang pesat. Model spasial banjir rob DKI Jakarta yang didasarkan pada fluktuasi gelombang pasang, penurunan muka tanah dan ketinggian tempat merupakan kajian utama dalam penelitian ini. Melalui grid 2x2 meter penurunan muka tanah diektraksi menjadi informasi spasial sebagai basis data pemodelan. Berdasarkan hasil regresi linear multivariate. Melalui hasil verifikasi lapangan di tiga puluh dua lokasi untuk memperkuat model regresi model linear multivariate. Hasil analisis menunjukan wilayah yang akan tergenang pada tahun 2030, 2050, 2080, dan 2100 cenderung bertambah dari sekarang, 25% sampai 36% dari luas wilayah DKI Jakarta.

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ABSTRACT
Plain area, including the city of Jakarta which is the center of the Indonesian economy. Jakarta is a region that is experienced a rapid development progress. Spatial models of tidal flood Jakarta based on fluctuations in the tidal wave, land subsidence and elevation are the main study in this research. Through the grid of 2x2 meters of land subsidence was extracted into spatial information as database modeling. Based on the results of multivariate linear regression. Through the results of field verification of the thirtytwo locations to strengthen the multivariate linear regression model models. Results of the analysis showed that the area would be inundated in 2030, 2050, 2080, and 2100 tended to increase from now, 25% to 36% of the total area of Jakarta., plain area, including the city of Jakarta which is the center of the Indonesian economy. Jakarta is a region that is experienced a rapid development progress. Spatial models of tidal flood Jakarta based on fluctuations in the tidal wave, land subsidence and elevation are the main study in this research. Through the grid of 2x2 meters of land subsidence was extracted into spatial information as database modeling. Based on the results of multivariate linear regression. Through the results of field verification of the thirtytwo locations to strengthen the multivariate linear regression model models. Results of the analysis showed that the area would be inundated in 2030, 2050, 2080, and 2100 tended to increase from now, 25% to 36% of the total area of Jakarta.]

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[ABSTRAK
Kebakaran hutan dan lahan merupakan permasalahan kompleks yang terjadi di Provinsi Riau setiap tahun. Pemicunya berasal dari faktor alami dan akibat aktivitas manusia. Penelitian ini menggunakan variabel hotspots (titik panas) sebagai indikasi adanya kebakaran hutan dan lahan yang dihasilkan oleh sensor satelit NOAA (National Oceanic and Atmospheric Administration) akibat kenaikan suhu di atas 315° K atau 42°C pada luasan 1 km2. Hotspots yang tersebar diseluruh Provinsi Riau dianalisis kepadatannya sepanjang tahun 2005 hingga 2014 menggunakan perhitungan Kernel Density. Hasilnya pola spasial kepadatan hotspots terkonsentrasi di Kota Dumai, Kabupaten Rokan Hilir, Bengkalis dan Pelalawan. Sedangkan pola temporal menunjukkan jumlah hotspots terbanyak selama 10 tahun terjadi pada bulan Juni hingga Agustus. Kemudian sebaran kepadatan hotspots dihubungan dengan faktor-faktor pemicu terjadinya kebakaran yakni curah hujan bulanan, sebaran dan kedalaman gambut serta jenis penggunaan lahan. Hasil analisis menunjukkan jumlah hotspots terbanyak tersebar pada wilayah dengan curah hujan bulanan rendah yaitu 50 - 150 mm/bulan dan pada lahan gambut dengan kedalaman lebih dari 4 meter (sangat dalam) serta pada jenis penggunaan lahan perkebunan, hutan lahan basah sekunder dan semak belukar. Selanjutnya penentuan ambang batas hari tanpa hujan sehubungan kemunculan hotspots diperoleh melalui teknik buffering sejauh 10 km dari stasiun-stasiun pengamatan hujan setiap hari selama bulan Juni hingga Agustus. Analisis pada setiap kemunculan hotspots juga dikaitkan dengan kedalaman gambut dan jenis penggunaan lahan untuk mengetahui karakteristik setiap area buffer, hasilnya ambang batas hari tanpa hujan dalam kaitan kemunculan hotspots di Provinsi Riau adalah 3 hari.

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ABSTRACT
Land and forest fires are complex problems that occurred in the province of Riau every year. The trigger factors comes from natural and human activities. This research uses a variable hotspots as an indication of land and forest fires produced by the satellite sensors NOAA (National Oceanic and Atmospheric Administration) due to the temperature rise above 315 °K or 42° C on an area of 1 km2. The density of hotspots are scattered throughout the province of Riau 2005 to 2014 analyzed using Kernel Density calculations. The result patterns of spatial density of hotspots concentrated in Dumai, Rokan Hilir, Bengkalis and Pelalawan. While the time pattern showed the highest number of hotspots for 10 years occurred in June until August. Then the distribution of the density of hotspots related with the factors that trigger fires such as monthly rainfall, distribution and depth of the peatland and the type of land use. The analysis showed the highest number of hotspots spread out on an area with a low monthly precipitation is 50-150 mm / month and on peatlands with a depth of more than 4 meters (very deep) as well as on the type of plantation land use, wetlands secondary forest and shrubs. Furthermore, the determination of threshold no rain day due to the hotspots appearance obtained through buffering technique as far as 10 km from rain gauge stations every day during the month of June to August. Analysis on each occurrence of hotspots is also associated with the depth of peat and types of land use to determine the characteristics of each buffer area, the result of the threshold of no rainy days in relation to the hotspot appearance in Riau Province is 3 days.;Land and forest fires are complex problems that occurred in the province of Riau every year. The trigger factors comes from natural and human activities. This research uses a variable hotspots as an indication of land and forest fires produced by the satellite sensors NOAA (National Oceanic and Atmospheric Administration) due to the temperature rise above 315 °K or 42° C on an area of 1 km2. The density of hotspots are scattered throughout the province of Riau 2005 to 2014 analyzed using Kernel Density calculations. The result patterns of spatial density of hotspots concentrated in Dumai, Rokan Hilir, Bengkalis and Pelalawan. While the time pattern showed the highest number of hotspots for 10 years occurred in June until August. Then the distribution of the density of hotspots related with the factors that trigger fires such as monthly rainfall, distribution and depth of the peatland and the type of land use. The analysis showed the highest number of hotspots spread out on an area with a low monthly precipitation is 50-150 mm / month and on peatlands with a depth of more than 4 meters (very deep) as well as on the type of plantation land use, wetlands secondary forest and shrubs. Furthermore, the determination of threshold no rain day due to the hotspots appearance obtained through buffering technique as far as 10 km from rain gauge stations every day during the month of June to August. Analysis on each occurrence of hotspots is also associated with the depth of peat and types of land use to determine the characteristics of each buffer area, the result of the threshold of no rainy days in relation to the hotspot appearance in Riau Province is 3 days.;Land and forest fires are complex problems that occurred in the province of Riau every year. The trigger factors comes from natural and human activities. This research uses a variable hotspots as an indication of land and forest fires produced by the satellite sensors NOAA (National Oceanic and Atmospheric Administration) due to the temperature rise above 315 °K or 42° C on an area of 1 km2. The density of hotspots are scattered throughout the province of Riau 2005 to 2014 analyzed using Kernel Density calculations. The result patterns of spatial density of hotspots concentrated in Dumai, Rokan Hilir, Bengkalis and Pelalawan. While the time pattern showed the highest number of hotspots for 10 years occurred in June until August. Then the distribution of the density of hotspots related with the factors that trigger fires such as monthly rainfall, distribution and depth of the peatland and the type of land use. The analysis showed the highest number of hotspots spread out on an area with a low monthly precipitation is 50-150 mm / month and on peatlands with a depth of more than 4 meters (very deep) as well as on the type of plantation land use, wetlands secondary forest and shrubs. Furthermore, the determination of threshold no rain day due to the hotspots appearance obtained through buffering technique as far as 10 km from rain gauge stations every day during the month of June to August. Analysis on each occurrence of hotspots is also associated with the depth of peat and types of land use to determine the characteristics of each buffer area, the result of the threshold of no rainy days in relation to the hotspot appearance in Riau Province is 3 days.;Land and forest fires are complex problems that occurred in the province of Riau every year. The trigger factors comes from natural and human activities. This research uses a variable hotspots as an indication of land and forest fires produced by the satellite sensors NOAA (National Oceanic and Atmospheric Administration) due to the temperature rise above 315 °K or 42° C on an area of 1 km2. The density of hotspots are scattered throughout the province of Riau 2005 to 2014 analyzed using Kernel Density calculations. The result patterns of spatial density of hotspots concentrated in Dumai, Rokan Hilir, Bengkalis and Pelalawan. While the time pattern showed the highest number of hotspots for 10 years occurred in June until August. Then the distribution of the density of hotspots related with the factors that trigger fires such as monthly rainfall, distribution and depth of the peatland and the type of land use. The analysis showed the highest number of hotspots spread out on an area with a low monthly precipitation is 50-150 mm / month and on peatlands with a depth of more than 4 meters (very deep) as well as on the type of plantation land use, wetlands secondary forest and shrubs. Furthermore, the determination of threshold no rain day due to the hotspots appearance obtained through buffering technique as far as 10 km from rain gauge stations every day during the month of June to August. Analysis on each occurrence of hotspots is also associated with the depth of peat and types of land use to determine the characteristics of each buffer area, the result of the threshold of no rainy days in relation to the hotspot appearance in Riau Province is 3 days.;Land and forest fires are complex problems that occurred in the province of Riau every year. The trigger factors comes from natural and human activities. This research uses a variable hotspots as an indication of land and forest fires produced by the satellite sensors NOAA (National Oceanic and Atmospheric Administration) due to the temperature rise above 315 °K or 42° C on an area of 1 km2. The density of hotspots are scattered throughout the province of Riau 2005 to 2014 analyzed using Kernel Density calculations. The result patterns of spatial density of hotspots concentrated in Dumai, Rokan Hilir, Bengkalis and Pelalawan. While the time pattern showed the highest number of hotspots for 10 years occurred in June until August. Then the distribution of the density of hotspots related with the factors that trigger fires such as monthly rainfall, distribution and depth of the peatland and the type of land use. The analysis showed the highest number of hotspots spread out on an area with a low monthly precipitation is 50-150 mm / month and on peatlands with a depth of more than 4 meters (very deep) as well as on the type of plantation land use, wetlands secondary forest and shrubs. Furthermore, the determination of threshold no rain day due to the hotspots appearance obtained through buffering technique as far as 10 km from rain gauge stations every day during the month of June to August. Analysis on each occurrence of hotspots is also associated with the depth of peat and types of land use to determine the characteristics of each buffer area, the result of the threshold of no rainy days in relation to the hotspot appearance in Riau Province is 3 days.;Land and forest fires are complex problems that occurred in the province of Riau every year. The trigger factors comes from natural and human activities. This research uses a variable hotspots as an indication of land and forest fires produced by the satellite sensors NOAA (National Oceanic and Atmospheric Administration) due to the temperature rise above 315 °K or 42° C on an area of 1 km2. The density of hotspots are scattered throughout the province of Riau 2005 to 2014 analyzed using Kernel Density calculations. The result patterns of spatial density of hotspots concentrated in Dumai, Rokan Hilir, Bengkalis and Pelalawan. While the time pattern showed the highest number of hotspots for 10 years occurred in June until August. Then the distribution of the density of hotspots related with the factors that trigger fires such as monthly rainfall, distribution and depth of the peatland and the type of land use. The analysis showed the highest number of hotspots spread out on an area with a low monthly precipitation is 50-150 mm / month and on peatlands with a depth of more than 4 meters (very deep) as well as on the type of plantation land use, wetlands secondary forest and shrubs. Furthermore, the determination of threshold no rain day due to the hotspots appearance obtained through buffering technique as far as 10 km from rain gauge stations every day during the month of June to August. Analysis on each occurrence of hotspots is also associated with the depth of peat and types of land use to determine the characteristics of each buffer area, the result of the threshold of no rainy days in relation to the hotspot appearance in Riau Province is 3 days., Land and forest fires are complex problems that occurred in the province of Riau every year. The trigger factors comes from natural and human activities. This research uses a variable hotspots as an indication of land and forest fires produced by the satellite sensors NOAA (National Oceanic and Atmospheric Administration) due to the temperature rise above 315 °K or 42° C on an area of 1 km2. The density of hotspots are scattered throughout the province of Riau 2005 to 2014 analyzed using Kernel Density calculations. The result patterns of spatial density of hotspots concentrated in Dumai, Rokan Hilir, Bengkalis and Pelalawan. While the time pattern showed the highest number of hotspots for 10 years occurred in June until August. Then the distribution of the density of hotspots related with the factors that trigger fires such as monthly rainfall, distribution and depth of the peatland and the type of land use. The analysis showed the highest number of hotspots spread out on an area with a low monthly precipitation is 50-150 mm / month and on peatlands with a depth of more than 4 meters (very deep) as well as on the type of plantation land use, wetlands secondary forest and shrubs. Furthermore, the determination of threshold no rain day due to the hotspots appearance obtained through buffering technique as far as 10 km from rain gauge stations every day during the month of June to August. Analysis on each occurrence of hotspots is also associated with the depth of peat and types of land use to determine the characteristics of each buffer area, the result of the threshold of no rainy days in relation to the hotspot appearance in Riau Province is 3 days.]

Abstrak :
Pemanasan global telah menganggu sistem iklim global dan menyebabkan meningkatnya frekuensi dan intensitas kejadian iklim ekstrim. Hujan ekstrim merupakan salah satu indikasi terjadinya kejadian iklim ekstrim. Dampak akibat terjadinya hujan ekstrim di sebagian wilayah Indonesia menimbulkan bencana alam, salah satunya bencana longsor. Indonesia yang sebagian wilayahnya berupa daerah perbukitan dan pegunungan, menyebabkan sebagian wilayah tersebut menjadi daerah yang rawan kejadian longsor. Kebumen merupakan salah satu wilayah yang dinyatakan termasuk wilayah dengan kejadian longsor tinggi. Berdasarkan banyaknya titik kejadian longsor membuktikan bahwa wilayah Kabupaten Kebumen merupakan salah satu wilayah yang tergolong rentan terhadap kejadian longsor. Melalui pendekatan Modeling GIS melalui Tools SINMAP diperoleh bahwa wilayah Kabupaten Kebumen yang berpotensi longsor terluas terdapat di Kecamatan Rowokele dengan luas 60% dari total wilayah yang berpotensi tinggi. Hasil pemodelan SINMAP kemudian dilakukan validasi berdasarkan titik kejadian longsor yang ada dan selanjutnya wilayah yang potensi dianalisis dengan Analytical Hierarchy Process (AHP), sehingga diperoleh bahwa wilayah yang dinyatakan rentan tersebar pada 149 desa, dengan desa yang memiliki rentan tinggi tersebar di 6 desa yaitu Desa Kebakalan, Desa Kajoran, Desa Kalirejo, Desa Clapar, Desa Logandu, dan Desa Wadasmalang atau 4,02% dari total wilayah yang dinyatakan rentan terhadap longsor. Terkait dengan perubahan iklim, maka kerentanan wilayah terhadap longsor sehubungan dengan perubahan Iklim terbagi atas sebaran kerentanan longsor berdasarkan rerata frekuensi hujan ekstrim yang terus meningkat sepanjang tahun dengan intensitas hujan ekstrim >20 kejadian tersebar di Desa Sawangan. Untuk sebaran kerentanan longsor berdasarkan tren hujan ekstrim dengan tingkat rentan tinggi dan nlai tren mengalami kenaikan dengan r > 0,4 terdapat di Kecamatan Sempor.

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Global warming disturbing the global climate system and causing increased frequency and intensity of extreme climate events. Extreme of rain is an indication the occurrence of extreme climate events. Impacts due to the occurrence extreme rainfall in some parts of Indonesia caused natural disasters, one of the landslides. Indonesia that partly in the form of hilly and mountainous regions, causing most of the territory into areas prone to landslide. Kebumen is one of the areas declared to including areas with a high incidence of landslides. Based on the number of points landslide prove that Kebumen district is one of the region that are vulnerable to landslide. Through the GIS Modeling approach of through Tools SINMAP obtained that the district of Kebumen potentially there are the largest landslide in the district with an area Rowokele 60% of the total area of high potential. The modeling results SINMAP then validated by a point landslide existing and further areas of potential analyzed with Analytical Hierarchy Process (AHP), to obtain that areas declared to vulnerable scattered in 149 villages, the village has a vulnerable high spread in 6 villages namely Kebakalan, Kajoran Village, Village Kalirejo, Clapar Village, Village Logandu and Wadasmalang village with a total area 5.71% of the total areas declared to vulnerable landslides. Related climate change, the vulnerability of the region to landslides in connection with climate change consists of the distribution of landslide vulnerability based on the average frequency of extreme rainfall that is continued to increase throughout the year with extreme rainfall intensity> 20 events spread in the District Sawangan. For the distribution of landslide vulnerability by extreme rainfall trends with high levels of vulnerable and value of trend has increased with r> 0.4 there are in the district Sempor.

Abstrak :
ABSTRAK Kota Padang diketahui rawan terhadap bencana alam banjir, berdasarkan kejadian banjir tahun 2012 yang berdampak luas di Kota Padang. Penelitian ini dimaksudkan untuk mengumpulkan respon masyarakat yang berkaitan dengan banjir dengan wilayah studi Tabing Banda Gadang Kota Padang. Tujuan utama dari penelitian ini adalah untuk menganalisis strategi adaptasi masyarakat terhadap dampak peristiwa alam ekstrim khususnya banjir, yang termasuk permasalahan serius di Kota Padang. Rumah tangga disurvei dengan teknik wawancara mendalam dan kuesioner yang dilakukan di wilayah terdampak banjir. Hasil penelitian menunjukkan masyarakat wilayah studi melakukan adaptasi terhadap banjir meliputi strategi adaptasi struktural dan non struktural yaitu penggunaan kembali barang yang tidak rusak, memindahkan barang ketempat yang lebih tinggi, gotong royong, pinjaman keuangan informal, meninggikan rumah. Selain itu terdapat kendala dalam adaptasi struktural dan non struktural untuk kemungkinan perulangan banjir masa depan, hal ini dipengaruhi berbagai hambatan untuk beradaptasi antara lain adalah keuangan, teknologi konstruksi untuk terhindar dari dampak banjir, oleh karena itu untuk adaptasi struktural dan non struktural di anggap masih rendah. Selanjutnya relokasi sebagai strategi menghindari banjir didukung oleh masyarakat terutama yang berada pada bekas aliran sungai yang dianggap zona bahaya tinggi. Pengalaman banjir, tingkat kerusakan, dan persepsi bahaya terhadap banjir juga memainkan peran penting dalam strategi adaptasi ini.

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ABSTRACT Padang city has long been known to be at risk from flood hazard, based on the 2012 flood events that have a wide impact in the Padang city. This study is intended to gather public response and local knowladge relating to flood the study area in Tabing Banda Gadang. The main objective of this thesis is to analyze the adaptation strategy of local community against extreme natural events, especially the impact of the floods, which belong amongst the most serious problem in Padang city, especially in Tabing Banda Gadang. A households were surveyed by using in-depth interviews and questionnaires carried out in the flood affected areas. The result of the study area various adaptation strategies have been adopted by the local community, structural and non structural adaptations include re-use material left undamaged, moving household equipment to higher place, mutual cooperation, informal financial loans and raise level of home. Meanwhile as for changes to the possibility future of flooding, the majority of respondents said their communities are unlikely to perform structural and non structural change to the possibility future of flooding, because it is influenced by a variety of barriers to change and adapt, among others, finance, construction technology to avoid the impact of flooding. Therefore, adaptation strategies to the structural and non-structural considered is remain low. On the other side of the relocation as a strategy to avoid flooding is supported by the communities, especially household those located are the former river channel that are considered high hazard zones. Flood experience, the level of damage, and individual flood danger perception also played an important role.