Judul: Analysis Hotspot and Burned Areas in Alor District East Nusa Tenggara Province
Abstrak: Kabupaten Alor merupakan salah satu Provinsi di Nusa Tenggara Timur yang tergolong rawan kebakaran. Kabupaten Alor memiliki jumlah hotspot terbanyak ketiga setelah Sumbawa dan Kupang. Tujuan penelitian ini adalah menganalisis sebaran hotspot area bekas kebakaran hutan dan lahan di Kabupaten Alor Provinsi Nusa Tenggara Timur pada tahun 2015 dan 2019. Analisis hotspot dilakukan dengan menggunakan satelit Terra/Aqua-MODIS (Moderate Resolution Imaging Spectroradiometer) untuk mengetahui area permukaan bumi yang memancarkan suhu tinggi. Analisis data dilakukan melalui buffering hotspot dengan jarak 1 km x 1 km. Jumlah hotspot di Kabupaten Alor pada tahun 2015 sebesar 51 hotspot yang tersebar di lima jenis tutupan lahan. Jumlah hotspot tahun 2019 sebesar 64 hotspot yang tersebar di delapan jenis tutupan lahan. Luas area bekas terbakar di Kabupaten Alor pada tahun 2015 sebesar 16.021 hektar dan mengalami peningkatan luas area bekas terbakar sebanyak 25% pada tahun 2019 menjadi 20.106 hektar. Jenis tutupan lahan yang memiliki luas area bekas terbakar terbesar pada tahun 2015 dan tahun 2019 adalah hutan lahan kering sekunder. Jenis tutupan lahan yang memiliki luas area bekas terbakar terkecil pada tahun 2015 adalah pertanian lahan kering dan pada tahun 2019 adalah pemukiman atau lahan terbangun serta tanah terbuka. Kata kunci: area terbakar, hotspot, kebakaran, tutupan lahan, Alor District is one part of the East Nusa Tenggara Province that classified as prone to fire disaster. Alor District has the third highest number of hotspots after Sumbawa and Kupang. The purpose of this study is to analyze the distribution of hotspots in areas of former forest and land fires in Alor District, East Nusa Tenggara Province in 2015 and 2019. Hotspot analysis was performed using the Terra/Aqua MODIS (Moderate Resolution Imaging Spectroradiometer) satellite to find out the area of the earth's surface that emits high temperatures. Data analysis was carried out through hotspot buffering with a distance of 1 km x 1 km. The number of hotspots in Alor District in 2015 was 51 hotspots spread across five types of land cover. The number of hotspots in 2019 was 64 hotspots spread across eight types of land cover. The burned areas in Alor Regency in 2015 was 16,021 hectares and experienced an increase in the burned areas by 25% in 2019 to 20,106 hectares. The type of land cover that had the largest burned areas in 2015 and 2019 is secondary dryland forest. The type of land cover that had the smallest area of burned areas in 2015 was dryland farming and in 2019 it was residential or built-up land as well as open land. Keywords: burned area, hotspot, fire, land cover
Keyword: burned area, hotspot, fire, land cover

Judul: Analisis Kebakaran Hutan dan Lahan Berdasarkan Hotspot dan Area Terbakar di Kabupaten Pelalawan, Provinsi Riau
Abstrak: Provinsi Riau selalu mengalami kebakaran hutan dan lahan setiap tahunnya. Salah satu kabupaten yang sering terbakar adalah Kabupaten Pelalawan. Kabupaten Pelalawan memiliki jumlah hotspot tertinggi dalam kurun waktu 2015- 2019. Penelitian ini bertujuan untuk menganalisis sebaran hotspot dan areal terbakar pada tahun 2015 dan 2019 di Kabupaten Pelalawan, Riau. Data yang digunakan berupa hotspot dan informasi spasial daerah terbakar dari citra satelit MODIS Terra/Aqua. Hasil penelitian menunjukkan bahwa jumlah hotspot di Kabupaten Pelalawan adalah 2168 pada tahun 2015 dan 1503 pada tahun 2019. Tahun 2015 jumlah hotspot didominasi di lahan non gambut dan pada tahun 2019 didominasi di lahan gambut. Kecamatan Pangkalan Kuras memiliki jumlah hotspot tertinggi pada tahun 2015 dan Kecamatan Teluk Meranti memiliki jumlah hotspot tertinggi pada tahun 2019. Luas areal yang terbakar pada tahun 2015 sebesar di Kabupaten Pelalawan adalah sebesar 50.896,207 ha dan pada tahun 2019 adalah sebesar 8.078,358 ha., Riau Province always occurs forest and land fires every year. One of the districts that are often burned is Pelalawan District. Pelalawan District has the highest number of hotspots in the 2015-2019 period. This study aims to analyze the distribution of hotspots and burned areas in 2015 and 2019 in Pelalawan District Riau. Data used in this study comes from the MODIS Terra/Aqua satellite imagery. The results showed that the number of hotspots in Pelalawan Regency was 2168 in 2015 and 1503 in 2019. In 2015 the number of hotspots was dominated on non-peat land and in 2019 dominated on peatland. Pangkalan Kuras District had the highest number of hotspots in 2015 and Teluk Meranti District had the highest number of hotspots in 2019. The area burned in 2015 was 50,896,207 ha in Pelalawan Regency and 8,078,358 ha in 2019.
Keyword: burned area, forest and land fire, hotspot, pelalawan district

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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