Judul: Land Cover Relationship to Surface Temperature with Landsat 8 OLI-TIRS Imagery in Pamijahan District, Bogor Regency
Abstrak: Suhu permukaan sebagai indikator perubahan iklim penting dilakukan pemantauan guna memberikan informasi kepada ilmuwan, pemerintah, dan lembaga swadaya masyarakat dalam mengambil keputusan terkait mitigasi perubahan iklim. Penelitian ini bertujuan melakukan analisis estimasi suhu permukaan dengan Citra Landsat 8 dan menganalisis hubungan tutupan lahan dengan suhu permukaan di Kecamatan Pamijahan, Kabupaten Bogor tahun 2023. Analisis suhu permukaan dengan metode split window algorithm (SWA) menghasilkan tujuh kelas suhu yaitu I: 17 °C – 20 °C, II: >20 °C – 23 °C, III: >23 °C – 26 °C, IV: >26 °C – 29 °C, V: >29 °C – 32 °C, VI: >32 °C – 35 °C, VII: >35 °C – 38,38 °C. Analisis klasifikasi tutupan lahan dengan metode maximum likelihood classification menghasilkan 9 kelas dengan akurasi 87%. Hasil penelitian menunjukkan tutupan lahan yang diwakili dengan indeks NDBI memiliki hubungan positif dengan nilai 0,61. Hubungan tutupan lahan yang diwakili dengan indeks NDVI memiliki hubungan negatif dengan nilai 0,44., Surface temperature as an indicator of climate change is important to monitor in order to provide information to scientists, government, and non governmental organizations in making decisions related to climate change mitigation. This study aims to analyze the estimation of surface temperature with Landsat 8 images and analyze the relationship between land cover and surface temperature in Pamijahan District, Bogor Regency in 2023. Analysis of surface temperature with the split window algorithm (SWA) method resulted in seven temperature classes I: 17 °C – 20 °C, II: >20 °C – 23 °C, III: >23 °C – 26 °C, IV: >26 °C – 29 °C, V: >29 °C – 32 °C, VI: >32 °C – 35 °C, VII: >35 °C – 38,38 °C. Land cover classification analysis using the maximum likelihood classification method resulted in 9 classes with 87% accuracy. The results showed that land cover represented by the NDBI index had a positive relationship with a value of 0,61. The land cover relationship represented by the NDVI index has a negative relationship with a value of 0,44.
Keyword: landsat 8 oli-tirs, maximum likelihood classification, remote sensing, split window algorithm

Judul: Land Cover Relationship to Surface Temperature with Landsat 8 OLI-TIRS Imagery in Pamijahan District, Bogor Regency
Abstrak: Suhu permukaan sebagai indikator perubahan iklim penting dilakukan pemantauan guna memberikan informasi kepada ilmuwan, pemerintah, dan lembaga swadaya masyarakat dalam mengambil keputusan terkait mitigasi perubahan iklim. Penelitian ini bertujuan melakukan analisis estimasi suhu permukaan dengan Citra Landsat 8 dan menganalisis hubungan tutupan lahan dengan suhu permukaan di Kecamatan Pamijahan, Kabupaten Bogor tahun 2023. Analisis suhu permukaan dengan metode split window algorithm (SWA) menghasilkan tujuh kelas suhu yaitu I: 17 °C – 20 °C, II: >20 °C – 23 °C, III: >23 °C – 26 °C, IV: >26 °C – 29 °C, V: >29 °C – 32 °C, VI: >32 °C – 35 °C, VII: >35 °C – 38,38 °C. Analisis klasifikasi tutupan lahan dengan metode maximum likelihood classification menghasilkan 9 kelas dengan akurasi 87%. Hasil penelitian menunjukkan tutupan lahan yang diwakili dengan indeks NDBI memiliki hubungan positif dengan nilai 0,61. Hubungan tutupan lahan yang diwakili dengan indeks NDVI memiliki hubungan negatif dengan nilai 0,44., Surface temperature as an indicator of climate change is important to monitor in order to provide information to scientists, government, and nongovernmental organizations in making decisions related to climate change mitigation. This study aims to analyze the estimation of surface temperature with Landsat 8 images and analyze the relationship between land cover and surface temperature in Pamijahan District, Bogor Regency in 2023. Analysis of surface temperature with the split window algorithm (SWA) method resulted in seven temperature classes I: 17 °C – 20 °C, II: >20 °C – 23 °C, III: >23 °C – 26 °C, IV: >26 °C – 29 °C, V: >29 °C – 32 °C, VI: >32 °C – 35 °C, VII: >35 °C – 38,38 °C. Land cover classification analysis using the maximum likelihood classification method resulted in 9 classes with 87% accuracy. The results showed that land cover represented by the NDBI index had a positive relationship with a value of 0,61. The land cover relationship represented by the NDVI index has a negative relationship with a value of 0,44.
Keyword: Landsat 8, Maximum likelihood classification, Remote sensing, Split window algorithm

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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