Judul: Estimating the Severinity Forest and Land Fire Using a Geographic Information System in Meranti Island, Riau Province
Abstrak: Kebakaran hutan dan lahan merupakan bencana alam yang sering terjadi di wilayah Indonesia khususnya di Pulau Sumatera. Selain menjadi penyumbang lahan gambut terluas, Kabupaten Kepulauan Meranti Provinsi Riau menjadi salah satu tempat kebakaran terburuk, sehingga perlu diketahui tingkat keparahan kebakaran, persebaran, maupun luasannya sehingga apabila terjadi kebakaran, penanggulangannya dapat dilakukan secara efektif. Salah satu teknik yang dapat digunakan untuk mendapatkan data-data tersebut, yaitu melalui Sistem Informasi Geografis dan penginderaan jauh. Penelitian ini bertujuan untuk mengidentifikasi tingkat keparahan dan pertumbuhan indeks spektral vegetasi pasca kebakaran hutan dan lahan. Berdasarkan analisis data diketahui bahwa sebaran hotspot/titik panas terbanyak di Kabupaten Kepulauan Meranti terjadi pada tahun 2014. Keparahan kebakaran tahun 2014 di Kabupaten Kepulauan Meranti di dominasi oleh tingkat keparahan kelas tinggi pada indeks NBR. Luas tingkat keparahan kelas tinggi dengan indeks NBR adalah 52,1%. Nilai uji akurasi indeks NBR memiliki nilai 90,334%. Frekuensi kebakaran pada area yang berulang menyebabkan laju pertumbuhan nilai indeks vegetasi lebih terhambat dibandingkan dengan pengaruh tingkat keparahan kebakaran., Forest and land fires are natural disasters that often occur in Indonesia, especially on Sumatra. In addition to being the largest peatlands, the Meranti Islands Regency Riau is one of the worst fire sites. It is necessary to know the severity of the fire, its distribution, and its extent so that if a fire occurs can be managed effectively. Technique that can be used to obtain these data is through Geographic Information Systems and remote sensing. This study aims to identify the severity and the growth of the spectral index of vegetation after forest and land fires. Based on the data analysis, the distribution of hotspots in the Meranti Islands Regency occurred in 2014. The severity of the 2014 fires in the Meranti Islands Regency was dominated by the high severity grade on the NBR index. The area of high-grade severity with NBR index is 52.1%. The NBR index accuracy test value has a value of 90.334%. The frequency of fires in repeated areas causes the growth rate of the vegetation index value more inhibited compared to the effect of fire severity.
Keyword: Indeks vegetasi, Kebakaran, SIG, Tingkat keparahan

Judul: Estimasi Tingkat Keparahan Kebakaran Hutan dan lahan Menggunakan Citra Sentinel-2 di Kabupaten Siak, Riau
Abstrak: Kebakaran hutan dan lahan menjadi masalah tahunan yang sering terjadi di Provinsi Riau. Salah satu daerah dengan luasan kebakaran terluas di Provinsi Riau adalah Kabupaten Siak. Kegiatan analisis kebakaran hutan dan lahan perlu dilakukan untuk membantu proses rehabilitasi dan pencegahan kebakaran hutan dan lahan pada tahun-tahun selanjutnya. Tingkat keparahan kebakaran hutan dan lahan dianalisis melalui penginderaan jauh meggunakan Citra Sentinel-2 dengan metode NBR (Normalized Burn Ratio). Tingkat keparahan kebakaran hutan dan lahan diklasifikasikan menjadi tiga kelas yaitu, rendah, sedang dan tinggi. Tingkat keparahan kebakaran rendah tahun 2019 adalah 81939,50 Ha dengan persentase luasan kebakaran 50,40%. Tingkat keparahan kebakaran sedang tahun 2019 adalah 42326,77 Ha dengan persentase luasan kebakaran 26,04% dan tingkat keparahan kebakaran tinggi tahun 2019 adalah 38303,76 Ha dengan persentase luasan kebakaran adalah 23,56%. Sedangkan Tingkat keparahan kebakaran rendah tahun 2020 adalah 34243,76 Ha dengan persentase luasan kebakaran adalah 39,42%. Tingkat keparahan kebakaran sedang adalah 13596,92 Ha dengan persentase luasan kebakaran 15,65% dan tingkat keparahan tinggi adalah 39032,25 Ha dengan persentase luasan kebakaran adalah 44,93%., Forest and land fires becomes an annual problem which often happens in Riau Province. One of the areas with the largest fire area in Riau Province is Siak Regency.The analysis activity of Forest and land fire need to be done in order to assist the process of rehabilitation and prevention of forest and land fires in the following years. The severity of forest and land fires was analyzed through remote sensing using Sentinel-2 Imagery with the NBR (Normalized Burn Ratio) method. The severity of forest and land fires was classified into three classes, namel; low, medium and high. The low fire severity in 2019 was 81939.50 Ha with severity percentage of 50.40%. The medium fire severity level was 42326.77 Ha with severity persentage of 26.04% and the high fire severity level in 2019 was 38303.76 Ha with severity percentage of 23.56%. While the low fire severity in 2020 was 34243.76 Ha with the severity percentage of 39.42%, the medium fire severity was 13596.92 Ha with severity percentage of 15.65% and the high severity level was 39032.25 Ha with the severity percentage of 44.93%.
Keyword: Forest, Land, Fire, NBR, Sentinel-2 Image, Severity level

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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