Judul: Distribusi Spasial Tanaman Padi Dan Estimasi Produksi Dengan Menggunakan Citra Modis Evi (Study Kasus Kabupaten Karawang, Subang, Dan Indramayu).
Abstrak: Indonesia is one of the rice producers in the world and most of the rice fields is located in Java Island which have the productivity of 60% of nearly 4 x 106 ton of rice (Amien et al., 1996). Rice in Indonesia generally is harvested twice a year (80-90 growing days) in well irrigated areas and harvested once a year (100-130 growing days) in non-irrigated areas (Indonesian Agency for Agricultural Research and Development, 2009). In Indonesia rice usually planted in the beginning of rainy season in October - December then to be harvested in February (Directorate General of Food Crops, 2009). Optical satellite remote sensing provides a viable means to meet the requirement of improved regional-scale detection and mapping of rice fields. Changes in plant phenology are considered to be a most sensitive indicator of plant responses to climate change observable on remotely sensed images (Linderholm, 2006). Vegetation Indices (VI) has proved particularly popular in the monitoring and characterization of plant cover. VI is used to diagnose and predict crop behavior over time and has been implemented by Potgieter et al. (2007) and Xiao et al. (2005) by using multi temporal Enhanced Vegetation Index (EVI) from MODIS imageries to estimate crop areas. The EVI will take full advantage of MODIS measurement capabilities to correct for various distortions in the reflected light caused by the particles in the air as well as the ground cover below the vegetation. The EVI data product also does not become saturated as easily as the NDVI when viewing rainforests and other areas of the Earth with large amounts of chlorophyll (Earth Observatory, 2009). It is becoming evident that studies of the growing season of land vegetation have become an important scientific issue for research into global climate change. The objectives of this research are to obtain the spatial distribution of rice fields in Karawang, Subang, and Indramayu Regency as national rice barn and to calculate estimation of rice production using medium resolution MODIS satellite imagery. The main data used for this research is MODIS EVI imagery with the resolution of 250m by 250m with the acquisition date ranging from 1 January 2008 to 31 December 2010. The landuse map and rice production statistic were acquired from Badan Informasi Geospasial (BIG/formerly known as BAKOSURTANAL) and Badan Pusat Statistik (BPS) that will be used to validate the spatial distribution and production estimation of rice field in the research area. The first technique to do is to change the 16-day of EVI MODIS image projection from sinusoidal projection into geographic projection, and the results were used to do next process. All of the 69 EVI MODIS satellite data ranging from January 2008 to December 2010 then were stacked to create an image with 69 bands that will make it able to be analyzed as multi temporal image of 16 days interval of EVI data. Next of the process is to subset to 69 bands EVI image with administrative boundary of Karawang, Subang, and Indramayu Regency and resulting EVI image of research area.
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Judul: Pengembangan Model Estimasi Produksi Padi Berbasis Data Sentinel-2A
Abstrak: Tanaman padi adalah salah satu jenis tanaman penghasil bahan pangan pokok masyarakat, bahkan menjadi komoditi pangan utama di Indonesia. Salah satu upaya agar tanaman padi menghasilkan beras dengan kualitas dan kuantitas yang baik dapat melalui cara pemupukan dan pemeliharaan yang baik. Dinamika pertumbuhan tanaman padi pada lahan yang luas, memerlukan metode pemantauan yang efisien terhadap waktu, melalui pendekatan penginderaan jauh dengan resolusi temporal menggunakan indeks vegetasi. Oleh karenanya penelitian ini bertujuan untuk (1) mengetahui respon nilai indeks vegetasi Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Optimization Soil-Adjusted Vegetation Index (OSAVI), Enhanced Vegetation Index-2 (EVI-2) dan Normalized Difference Red-Edge Index (NDRE) terhadap perlakuan pupuk dan jarak tanam dan (2) mengembangkan model estimasi produksi padi berdasarkan indeks vegetasi. Proses pengamatan lapang dan pengumpulan data dilakukan setiap 10 hari sekali selama satu siklus tanam di Desa Pasirkaliki, Karawang, Jawa Barat. Metode pengembangan model dilakukan berdasarkan analisis pada setiap akumulasi Thermal Heat Unit (THU) yang bersesuian dengan resolusi temporal Sentinel-2A, indeks vegetasi (NDVI, SAVI, OSAVI, EVI-2, dan NDRE) serta Random Forest Regression (RFR). Hasil penelitian menunjukkan bahwa pengaruh perlakuan dosis pupuk berpengaruh signifikan pada fase vegetatif dan fase generatif, ditandai dengan nilai R2 yang tinggi untuk nilai indeks vegetasi NDVI, SAVI, OSAVI, EVI-2, dan NDRE. Selain itu, hasil analisis RFR menunjukkan bahwa NDVI, OSAVI, dan NDRE memiliki performa yang baik untuk memprediksi berat kering gabah hasil panen. Performa model berbasis indeks NDRE menunjukkan akurasi yang lebih tinggi pada akumulasi THU 176°C hari (fase vegetatif) dengan angka persentase sebesar 94,58% dan RMSE 4,14. Performa model berbasis indeks OSAVI menunjukkan akurasi yang lebih tinggi pada akumulasi THU 481°C hari (fase genetatif) dengan angka persentase sebesar 95,05% dan RMSE 3,54. Saran untuk penelitian selanjutnya, menguji kehandalan model estimasi produksi gabah kering panen berbasis indeks NDRE digunakan pada fase vegetatif (akumulasi THU 176°C hari) dan indeks OSAVI digunakan pada fase generatif (akumulasi THU 481°C hari)., Rice plants are one type of plant that produces staple food for the community, even becoming the main food commodity in Indonesia. One of the efforts for rice plants to produce rice with good quality and quantity can be through fertilization and goog maintenance. The dynamics of rice plant growth on a large area of land requires a time-efficient monitoring method, through a remote sensing approach with temporal resolution using vegetation indices. Therefore, this research aims to (1) determine the response of Normalized Difference Vegetation Index (NDVI), Soil- Adjusted Vegetation Index (SAVI), Optimization Soil-Adjusted Vegetation Index (OSAVI), Enhanced Vegetation Index-2 (EVI-2) dan Normalized Difference Red- Edge Index (NDRE) to fertilizer dosage treatment and planting technique and (2) develop a rice production estimation model based on vegetation index. The field observation and data collection were carried out every 10 days during one cropping cycle in Pasirkaliki Village, Karawang, West Java. The model development method is based on the analysis of each Thermal Heat Unit (THU) accumulation that corresponds to the temporal resolution of Sentinel-2A, vegetation index (NDVI, SAVI, OSAVI, EVI-2, and NDRE) and Random Forest Regression (RFR). The results showed that the effect of fertilizer dosage treatment had a significant effect on the vegetative
Keyword: vegetation index, THU accumulation, RFR method, fertilizer dosage

Judul: Hydroxyapatite-Chitosan Composite Coating on Stainless Steel 316 to Improve Corrosion Resistance
Abstrak: Metals that were used in bone implantation should have good corrosion resistance that were not easily corroded when implanted into the body. Metal corrosion resistance of stainless steel 316 can be enhanced through the metal coating by hydroxyapatite-chitosan composite with composition ratio of hydroxyapatite (gram) and chitosan 3% (mL) 0.2:0, 0.2:0.1, 0.2:0.5, 0.2:1.0, and 0.2:1.5. Besides improving the corrosion resistance of metal, the presence of chitosan also maintain the position of hydroxyapatite on metal surfaces. Corrosion resistance increases with increasing amount of chitosan added and the best composition of hydroxyapatite-chitosan composite was 0.2:1.0.
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