Judul: Assessing the Severity Level of Forest and Land Fires in Sungai Buluh Protected Peat Forest the Province of Jambi
Abstrak: Hutan Lindung Gambut (HLG) Sungai Buluh merupakan suatu kawasan gambut berstatus hutan lindung di Provinsi Jambi yang mengalami kejadian kebakaran hutan dan lahan tahun 2019. Penelitian ini bertujuan membandingkan indeks NDVI (Normalized Difference Vegetation Index) dan indeks NBR (Normalized Burn Ratio) dalam mengestimasi tingkat keparahan kebakaran hutan dan lahan di HLG Sungai Buluh pada tahun 2019. Tingkat keparahan kebakaran diukur menggunakan data citra Sentinel-2. Hasil dari penelitian ini menunjukkan tingkat keparahan kebakaran di HLG Sungai Buluh tahun 2019 didominasi oleh keparahan kebakaran kelas tinggi pada indeks NDVI seluas 208,808 ha dan pada indeks NBR seluas 207,900 ha. Indeks NBR dengan nilai D (Distance) sebesar 2,816 lebih baik daripada indeks NDVI dengan nilai D sebesar 2,114 dalam mengukur tingkat keparahan kebakaran. Selain itu, indeks NBR dengan tingkat akurasi 91,984% menghasilkan data yang lebih akurat dibandingkan indeks NDVI dengan tingkat akurasi 88,456%. Oleh karena itu, indeks terbaik untuk megestimasi tingkat keparahan kebakaran di HLG Sungai Buluh adalah indeks NBR., Sungai Buluh Peat Protection Forest is one of the protected peat forest areas in Jambi Province which experienced severe forest and land fires in 2019. This study aims to compare the NDVI (Normalized Difference Vegetation Index) index and the NBR (Normalized Burn Ratio) index in estimating the severity of forest and land fires at HLG Sungai Buluh in 2019. The severity of the fire was measured using the Sentinel-2 satellite image data. The fire severity in the HLG Sungai Buluh in 2019 was dominated by high class fire severity at the NDVI index covering an area of 208,808 ha and the NBR index covering an area of 207,900 ha. Basically, the NDVI index and the NBR index have a good ability to estimate the severity of forest and land fires. The NBR index with a D value of 2,816 is better than the NDVI index with a D value of 2,114 in measuring fire severity. In addition, the NBR index with an accuracy rate of 91,984% produces more accurate data than the NDVI index with an accuracy rate of 88,456%. Therefore, this study concluded that the best index to assess fire severity level in HLG Sungai Buluh is the NBR index.
Keyword: estimation, fire index, peat, severity level

Judul: Relationship Between  Vegetation Density Assessed Using NDVI with Carbon Reserves and Fire Hazard  Levels in HLG Sungai Buluh, Jambi
Abstrak: Hutan Lindung Gambut (HLG) Sungai Buluh merupakan kawasan lindung gambut di Jambi yang tergolong masih alami dan memiliki vegetasi yang sangat rapat. Penelitian ini bertujuan menduga kerapatan vegetasi mengunakan Normalized Difference Vegetation Index (NDVI), menduga biomassa dan cadangan karbon beserta tingkat bahaya kebakaran, serta menganalisis hubungan NDVI dengan keanekaragaman vegetasi dan cadangan karbon di HLG Sungai Buluh. Metode yang digunakan meliputi analisis vegetasi, pendugaan karbon menggunakan pendekatan alometrik dan destruktif untuk tingkat semai dan tumbuhan bawah, pendugaan tingkat bahaya kebakaran menggunakan skoring tutupan lahan dan nilai NDVI. Berdasarkan hasil analisis NDVI, kelas kerapatan terbagi menjadi kelas 1 (-0,015 – 0,369), kelas 2 (0,369 – 0,438), kelas 3 (0,438 – 0,633). Famili yang paling banyak ditemukan adalah Lauraceae, Dipterocarpaceae, dan Myrtaceae. Rata-rata biomassa dan kandungan karbon yang didapatkan masing-masing sebesar 191,26 ton/ha dan 89,90 ton C/ha. Tingkat bahaya kebakaran pada seluruh kelas menunjukkan kategori tinggi. Konsentrasi karbon berkorelasi paling tinggi dengan LBDS (r = 98,2%). Nilai NDVI memiliki korelasi tertinggi dengan jumlah jenis., Sungai Buluh Peat Protection Forest (HLG) is a peat protected area in Jambi that still natural and characterized by a high degree of vegetation density.This study aimed to estimate vegetation density using the Normalized Difference Vegetation Index (NDVI), estimate biomass and carbon stock along with fire hazard levels, and analyze the relationship between NDVI, vegetation diversity, and carbon reserves in HLG Sungai Buluh. The methods used include vegetation analysis, carbon estimation using allometric and destructive testing for seedlings and understory plants, fire hazard level estimation using land cover scoring and NDVI values. The result showed NDVI was categorized into three classes, nemely class 1 (-0,015 – 0,369), class 2 (0,369 – 0,438), class 3 (0,438 – 0,633). The most families found were Lauraceae, Dipterocarpaceae, and Myrtaceae. The average biomass and carbon stock obtained were 191,26 tons/ha and 89,90 tons C/ha, respectively. Fire hazard levels in all classes were found to be high. Carbon stock strongly correlated with LBDS (r = 98,2%). The NDVI value strongly correlated with the number of species.
Keyword: indeks vegetasi, karbon, tutupan lahan, tingkat bahaya kebakaran

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.
Keyword: