Judul: The Global Climate Prediction Data Association Analysis for Hotspots Using the Combined Empirical Orthogonal Function (CEOF)
Abstrak: Iklim global yang terdiri dari El Nino-Southern Oscillation (ENSO) dan Indian Ocean Dipole (IOD) memiliki dampak pada penurunan curah hujan di wilayah Indonesia. Penelitian sebelumnya menemukan bahwa ENSO dan IOD yang berasal dari dataset OISST memiliki keterkaitan dengan hotspot di Indonesia, khususnya di Sumatera bagian selatan dan Kalimantan. Namun hasil korelasinya terlalu kecil sehingga penelitian sebelumnya tidak difokuskan pada menganalisis kekuatan korelasi antar wilayah. Oleh karena itu, studi ini menghitung asosiasi estimasi ENSO dan IOD yang berasal dari dataset ERA5 pada hotspot di Indonesia berdasarkan Heterogeneous Correlation Map (HCM) dan menganalisis kekuatan korelasi antar wilayah di Indonesia. ERA5 merupakan data estimasi yang sering digunakan untuk analisis prakiraan cuaca. Hasil penelitian menunjukkan bahwa ENSO lebih berasosiasi dengan titik api di Papua dan Kalimantan. Sebaliknya, IOD lebih dikaitkan dengan titik api di Sumatera bagian selatan. Selain itu, berdasarkan varians yang dijelaskan dan kekuatan korelasinya, hotspot di Indonesia lebih sensitif terhadap ENSO dan IOD yang berasal dari ERA5 daripada OISST., The global climate consisting of the El Nino-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) has an impact on reducing rainfall in Indonesia. Previous researches have found that ENSO and IOD derived from the OISST dataset are correlated to hotspots in Indonesia, particularly in southern Sumatra and Kalimantan. However, their correlation is too small so that previous research was not focused on analyzing the strength of the correlation between regions. Therefore, this study calculates the association of ENSO and IOD estimation derived from the ERA5 dataset of hotspots in Indonesia based on the Heterogeneous Correlation Map (HCM) and analyzes the strength of the correlation among regions in Indonesia. Apart from OISST, ERA5 is an estimated data which is often used for weather forecast analysis. The result of the study shows that ENSO is more associated with hotspots in Papua and Kalimantan. In contrast, IOD is more associated with hotspots in southern Sumatra. In addition, based on the variance described and the strength of the correlation, hotspots in Indonesia are more sensitive to ENSO and IOD originating from ERA5 than OISST’s.
Keyword: ENSO, Heterogeneous correlation map, Hotspot, IOD, SVD

Judul: Heterogeneous Correlation Map between Regional and Local Climate Estimation Data on the Burned Areas in Indonesia
Abstrak: Indonesia merupakan negara dengan hutan hujan tropis terbesar ketiga di dunia, namun setengahnya sudah terdegradasi. Salah satu penyebabnya yaitu kebakaran hutan. Kebakaran hutan bisa disebabkan oleh dua faktor, yaitu faktor manusia dan alam. Faktor alam salah satunya menurunnya curah hujan. Fenomena iklim regional (ENSO dan IOD) dan lokal (selat Karimata, selat Makassar, dan laut Arafura) merupakan salah satu penyebab menurunnya curah hujan di Indonesia. Penelitian ini bertujuan melihat keterkaitan data estimasi iklim regional terhadap data luas area terbakar di Indonesia dan melihat keterkaitan data estimasi iklim lokal terhadap luas area terbakar di wilayah sekitarnya. Penelitian ini menggunakan metode Combined Empirical Orthogonal Function (CEOF) berbasis Singular Value Decomposition (SVD). Hasil penelitian menunjukkan bahwa ENSO lebih memiliki korelasi terhadap luas area terbakar di Merauke, Sulawesi dan Kalimantan. Sementara itu, IOD lebih memiliki korelasi terhadap luas area terbakar di Sumatra bagian Selatan. Luas area terbakar di Riau berkorelasi sangat rendah terhadap iklim regional, baik ENSO maupun IOD. Luas area terbakar di Sumatra selain dipengaruhi oleh ENSO dan IOD, ternyata juga dipengaruhi oleh iklim lokal di selat Karimata. Sama halnya dengan luas area terbakar di Kalimantan dipengaruhi oleh iklim lokal di selat Makassar dan luas area terbakar di Merauke dipengaruhi oleh iklim lokal di laut Arafura., Indonesia is a country with the third largest tropical rainforest in the world, but half of the forest has already been degraded, one of the causes is forest fires. Forest fires can be caused by two factors, namely human and natural factors. One of the natural factors is the lack of rainfall. Regional (ENSO and IOD) and local climate phenomena (Karimata straits, Makassar straits, and Arafura seas) are some of the causes of the lack of rainfall in Indonesia. This study aims to analyze the correlation of regional climate estimation data with data of burned areas in Indonesia and to analyze the correlation of local climate estimation data with data of burned areas in the surrounding area. This study uses the Combined Empirical Orthogonal Function (CEOF) method based on Singular Value Decomposition (SVD). The result shows that ENSO has a better correlation with the burned area in Merauke, Sulawesi and Kalimantan. Meanwhile, IOD has a better correlation with the burned area in southern Sumatra. The burned area in Riau has a very low correlation with the regional climate, both ENSO and IOD. The burned area in Sumatra is not only influenced by ENSO and IOD, but it is also influenced by the local climate in the Karimata strait. Similarly, the burned area in Kalimantan is influenced by the local climate in the Makassar Strait and the burned area in Merauke is influenced by the local climate in the Arafura Sea.
Keyword: ENSO, IOD, burned area, CEOF, SVD

Judul: Studies of  microbial cellulose production through two stage cultivation
Abstrak: Acetobacter xylinum is a bacteria that can synthesize cellulose when grown in culture both static and agitated culture. In this study, cultivation is done through two stages, first stage of cultivation (agitated culture system) for 24 hours with a shaker speed of 150 rpm and cultivation of the second stage (static culture system) for 14 days. The addition of sucrose content sucrose 0%, 5%, and 7.5%. The shaker speed at 100 rpm , 150 rpm, 200 rpm, and 0 rpm as a control treatment. Additional media used is (NH4) 2SO4 0.6 g/l, K2HPO4/KH2PO4 5.0 g/l, yeast extract 2.5 g/l, and 2% glacial acetic acid. Production of microbial cellulose occurs fastest in the sample with the addition of sucrose 0% with a shaker speed of 100 rpm which began on day 5 and reached a maximum on day 10. Bacterial cellulose wet weights of 454.89 g/l, dry weight of 11.09 g/l, and the value Y(p/s) at 0.43.
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