Judul: Prediksi Awal Musim di Kabupaten Kapuas Menggunakan Data Curah Hujan Musiman Hasil Prediksi Model Iklim Global
Abstrak: Predictions of the rainy and dry season onsets are very important in climate risk management processes, especially for the development of early warning system of land and forest fires in Kalimantan. This research aimed to predict the rainy and dry season onsets in Kapuas District, Central Kalimantan. The prediction models used to predict the onsets were developed by using seasonal rainfall data on September-October-November (SON) periods as predicted by five Global Climate Models (GCMs). The models developed in this study relied on Canonical Correlation Analysis (CCA) prediction methods available in the Climate Predictability Tool (CPT) software developed by the International Research Institute for Climate and Society (IRI), Columbia University. This research showed that HMC and POAMA models produce better canonical correlations (r = 0.72 and 0.89, respectively) in creating the models for predicting the wet onsets compared to BCC (r=0.46), CWB (r=0.62), and GDAPS_F (r=0.67) models. In the development of models for predicting the dry season onsets, CWB and POAMA models indicated better canonical correlation results (r = 0.73 and 0.76, respectively) compared to BCC (r=0.53), GDAPS_F (r=0.64), and HMC (r=0.46) models. In general, the model validations showed that CWB, GDAPS_F, and POAMA models have better predictive skills than BCC and HMC models in predicting onsets of the rainy and dry seasons (with Pearson correlations (r) ranging between 0.30 and 0.75). Experiments on those five models for the predictions of wet season onset in 2013 showed that the predicted onsets occurred on the range of 8 September to 22 October in Cluster 1 and on 3 to 7 October in Cluster 2. For the predictions of the dry season onsets in 2014, the models predicted the occurrences from 6 to 25 May in Cluster 1 and from 21 to 25 March in Cluster 2.
Keyword: onset prediction, GCM, CPT, CCA

Judul: Prediksi Awal Musim Hujan di Provinsi Sulawesi Selatan Menggunakan Data Anomali Suhu Muka Laut
Abstrak: The Province of South Sulawesi is one of the centers for national paddy production with 7% contribution from total paddy production in national level. The increasing of paddy production depends on the water availability. Moreover, the water availability is always associated with the onset of rainy seasons, because if an area has the forward or backward of onset of rainy season, it will influence the water availability and crop calendar. In order to onset of rainy seasons, to reduce the farmer’s loss and to protect the food stability level in Indonesia, it needs to identified the areas which have the sensitivity for the onset of rainy season’s variability to climate control factors like ENSO and IOD. This research has been conducted to study the correlation between onset of rainy seasons (AMH) in South Sulawesi and sea surface temperature anomaly (AnoSML) in Pacific Ocean and Sulawesi Sea, to determine the domain of sea surface temperature predictor which has influence the onset of rainy seasons in South Sulawesi and to develop the onset of rainy season model prediction in South Sulawesi based on the sea surface temperature anomaly in Pacific Ocean and Sulawesi Sea. This research has been conducted using daily rainfall data during 30 years (1980-2010) from rainfall stations in South Sulawesi, sea surface temperature anomaly data for 4 domains i.e. Nino 3 region, Nino 3.4, Nino 4 and Sulawesi Sea on June, July, August and September (JJAS) during 30 years. The first analysis of data was conducted with the examination of observation daily rainfall data and selection of rainfall stations which are used for the development of the rainy season onset prediction model. Further analysis was conducted to determine the onset of rainy seasons using Moron’s method (five days of daily rainfall data/pentad analysis). The result of pentad analysis was used to calculate Principle Component Analysis (PCA) which was used to determine the cluster of rainfall stations. The correlation analysis was then calculated between the onset rainy seasons on each cluster and AnoSML data on JJAS. The last analysis was conducted for development of onset rainfall season model prediction and verification of the model. Based on the checking of observation daily rainfall data with the data availability >70%, there were 45 chosen stations for onset of the rainy season analysis. The result of AMH analysis showed that the average of AMH for whole stations was on the 348th Julian Date (JD) or on 14th December. The highest AMH was obtained at Stasiun BPP. Panincong (PNCG) in Soppeng District with 473th Julian Date or on 18th April. Otherwise, the lowest AMH was obtained at Stasiun BPP. Keera (KERA) in Wajo District with 278th Julian date or on 5th October. The result of PCA analysis showed that there were six PCs which were explained variability of data ± 80%. Based on the PC clustering, there were 3 clusters of rainfall stations. Cluster 1 has 13 rainfall stations which are spread in 9 districts i.e. Bantaeng District, Bulukumba, Enrekang, Gowa, Luwu, Maros, Pinrang, Soppeng and Wajo District. On Cluster 2, there are 10 rainfall stations
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Judul: Perancangan Proses Produksi Telur Asin Rendah Kolesterol
Abstrak: Telur asin merupakan produk olahan telur yang digemari masyarakat, tetapi mengandung kolesterol yang melebihi batasan konsumsi harian manusia. Tahap pengolahan, telur asin direndam dalam larutan khusus guna menurunkan kandungan kolesterol di dalam telur. Proses ini melibatkan pengaturan waktu pemeraman, konsentrasi larutan, dan bahan-bahan lainnya untuk mencapai hasil yang diinginkan. Formulasi telur asin yang terpilih yaitu pemeraman selama 12 hari dalam larutan garam 32,5% yang dicampur bawang putih, sereh, dan daun jeruk cincang, perendaman dalam larutan soda 20% selama 4 jam, dan dikukus selama satu jam. Kadar kolesterol sebesar 233,39 mg/100 g pada hari pertama dan mengalami penurunan menjadi 131,61 mg/100 g pada hari kesepuluh., Salted eggs are a popular egg product among the community, but they contain cholesterol that exceeds the daily human consumption limit. In the processing stage, the salted eggs are immersed in a special solution to reduce the cholesterol content inside the eggs. This process involves adjusting the soaking time, solution concentration, and other ingredients to achieve the desired results. The selected salted egg formulation is marinating for 12 days in 32.5% salt solution mixed with garlic, lemongrass, and chopped lime leaves, marinating in 20% soda solution for 4 hours, and steaming for one hour. The cholesterol level was measured at 233.39 mg/100g on the first day and decreased to 131.61 mg/100g on the tenth day.
Keyword: Soda solution, Low Cholesterol Salted Eggs, Process Design, Standardized Salted Eggs