Judul: Identifiaction of Changes in Land Cover and Rainfall in Bogor in 1991-2020 using Cloud Computing Technology
Abstrak: Perubahan tutupan lahan bervegetasi menjadi lahan terbangun berdampak pada cuaca disekitarnya, salah satunya adalah curah hujan. Penelitian ini mengidenfikasi perubahan tutupan lahan dan curah hujan di Bogor pada rentang tahun 1991-2020. Identifikasi perubahan tutupan lahan menggunakan data satelit Landsat 5, 7, dan 8 yang diolah dengan Google Earth Engine (GEE). Data hujan yang digunakan merupakan data hasil pengamatan di stasiun BMKG Citeko dan Dramaga. Analisis perubahan tutupan lahan menggunakan statistik deskriptif dan uji akurasi kappa. Hasil penelitian menunjukkan perubahan tutupan lahan terbangun memiliki tingkat akurasi sebesar 86,79% dan indeks kappa 0,8. Tren lahan terbangun bernilai positif, sedangkan tutupan vegetasi negatif. Tren curah hujan pada kedua stasiun bernilai negatif. Tutupan lahan terbangun mengalami peningkatan seluas 845 km2 dari tahun 1991-2020 dan tutupan vegetasi berkurang seluas 838 km2 . Perubahan tutupan lahan berhubungan dengan perubahan curah hujan melalui faktor-faktor meteorologis yang berperan dalam proses fisis kejadian hujan. Faktor meteorologis tersebut antara lain adalah suhu udara, radiasi, kecepatan dan arah angin. Hasil ini dapat memberikan informasi dan meningkatkan wawasan kepada para pihak terkait tentang dampak dari perubahan lahan terhadap kondisi iklim. Penelitian lebih lanjut perlu melakukan analisis kuantitatif hubungan antara unsur-unsur cuaca dengan tutupan lahan., Changes in vegetated land cover to built-up land have an impact on the surrounding weather, one of which is rainfall. This study identified changes in land cover and rainfall in Bogor in the 1991-2020 range. Identification of land cover changes using Landsat 5, 7 and 8 satellite data processed with the Google Earth Engine (GEE). The rain data used is observational data at the BMKG Citeko and Dramaga stations. Analysis of land cover change using descriptive statistics and kappa accuracy test. The results showed that changes in built-up land cover had an accuracy rate of 86.79% and a kappa index of 0.8. The trend of built-up land is positive, while the vegetation cover is negative. Rainfall trends at both stations are negative. The built-up land cover increased by 845 km2 from 1991-2020 and the vegetation cover decreased by 838 km2 . Changes in land cover are related to changes in rainfall through meteorological factors that play a role in the physical processes of rain events. These meteorological factors include air temperature, radiation, wind speed and direction. These results can provide information and increase insight to related parties about the impact of land use change on climate conditions. Further research needs to carry out a quantitative analysis of the relationship between weather elements and land cover.
Keyword: Google Earth Engine, land cover, Landsat, rainfall, supervised  classification

Judul: Detection of Land Use and Land Cover Changes in Sukajaya District Using Machine Learning on Google Earth Engine
Abstrak: Perubahan penggunaan/penutupan lahan merupakan fenomena yang terjadi hampir di seluruh bagian dunia. Beberapa wilayah telah terjadi perubahan penggunaan/penutupan lahan yang intens, terutama di Kecamatan Sukajaya, Kabupaten Bogor. Tujuan penelitian ini adalah menelaah algoritma indeks, membandingkan machine learning dalam mengklasifikasi penggunaan/penutupan lahan di Kecamatan Sukajaya, Kabupaten Bogor, serta analisis perubahannya dari tahun 2013-2022. Kelas penggunaan/penutupan lahan dibagi menjadi tujuh kelas. Algoritma indeks yang digunakan sebanyak 12 indeks. Machine learning yang digunakan adalah CART, Random Forest dan SVM. Enhanced Water Index adalah indeks yang paling dapat membedakan pengunaan/penutupan lahan di Kecamatan Sukajaya. SVM performa terbaik dengan nilai OA 90,46 dan Kappa 88,80 di tahun 2013 dan nilai OA 91,08 dan Kappa 89,52 di tahun 2022. Sifat irreversible perluasan lahan terbangun di Kecamatan Sukajaya tidak mutlak karena telah terjadi longsor yang menyebabkan perubahan klasifikasi lahan terbangun menjadi lahan terbuka., Land use/cover change is a phenomenon that occurs in almost every part of the world. Some regions have experienced intense changes in land use/cover, especially in Sukajaya District, Bogor Regency. The purpose of this study is to examine index algorithms, compare machine learning methods in classifying land use/cover in Sukajaya District, Bogor Regency, and analyze the land use/land cover changes from 2013 to 2022. Land use/cover classes are divided into seven categories. A total of 12 index algorithms are used. The machine learning methods used are CART, Random Forest, and SVM. The Enhanced Water Index is the best index in differentiating land use/cover in Sukajaya District. SVM show the best performance with an Overall Accuracy (OA) of 90.46% and Kappa value of 88.80% in 2013, and an OA of 91.08% and Kappa value of 89.52% in 2022. The irreversible characteristic of built-up area expansion in Sukajaya District is not absolute due to a landslide that led to a change in the classification of built-up area to bare land.
Keyword: supervised learning, index algorithm, cloud computing, land use/cover classification changes, supervised learning

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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