Judul: Prediksi Curah Hujan Deras Berpotensi Banjir berdasarkan Model Indeks MJO di Wilayah Jawa Barat
Abstrak: Madden Julian Oscillation (MJO) merupakan variabilitas iklim intraseasonal yang ditandai oleh perpindahan gerombol awan konvektif seperti Cumulonimbus yang membawa banyak uap air dan dapat meningkatkan curah hujan deras berpotensi banjir pada beberapa wilayah. Membangun model prediksi indeks MJO dan curah hujan deras berpotensi banjir merupakan salah satu hal yang penting dilakukan sebagai sistem peringatan dini untuk mengantisipasi kejadian banjir yang seringkali terjadi di wilayah Jawa Barat. Hal ini terjadi terutama saat MJO memasuki fase 3, 4 dan 5 yang merupakan fase MJO aktif yang melintasi wilayah Samudera Hindia dan Indonesia, sehingga apabila indeksnya mengalami penguatan maka dampak yang ditimbulkannya seperti curah hujan deras berpotensi banjir juga meningkat. Model ARIMA digunakan untuk memprediksi indeks MJO, sedangkan model curah hujan deras berpotensi banjir dibangun melalui metode proyeksi trend dengan regresi dan menggunakan nilai RMM1, RMM2, dan indeks MJO sebagai prediktornya. ARIMA(1,1,1)(1,1,1)42 memiliki nilai koefisien determinasi (R2) sebesar 0.85 sedangkan model prediksi curah hujan deras berpotensi banjir memiliki nilai koefisien determinasi (R2) sebesar 0.99. Peristiwa MJO pada fase 3, 4 dan 5 memiliki pengaruh yang paling kuat terhadap nilai curah hujan deras berpotensi banjir, OLR, dan suhu virtual di wilayah Jawa Barat. ABSTRACT CINDY LIA LISTIANI. Prediction of The Potentially Flooding Rainfall based on MJO Index’s Model in West Java. Supervised by HIDAYAT PAWITAN. Madden Julian Oscillation (MJO) is an intraseasonal climate variability characterized by movement of the convective cloud clusters such as Cumulonimbus that carries a lot of water vapor and can increase the rainfall that caused flooding in some areas. Forecast model of MJO Index and the potentially flooding rainfall is important to be built. This forecast model can be used as an early warning system to anticipate the flood events that often occur in the region of West Java, especially when the 3rd, 4th, 5th phase of MJO. In this phases, the MJO is active and passing through the Indian ocean and also territories of Indonesia. If the index of MJO is stronger, it will impacts such as increased the heavy rainfall and it can potentially flooding. ARIMA model is used to predict the MJO Index, while the potentially flooding rainfall’s forecast model is built by the trend projection method with regression and it use the value of RMM1, RMM2, and MJO Index as a predictor. The coefficient of determination (R2) of ARIMA(1,1,1)(1,1,1)42 is 0.85 and the coefficient of determination (R2) of the potentially flooding rainfall’s forecast model is 0.99. The 3rd , 4th and 5th phase of MJO events have a strong influence on the potentially flooding rainfall, OLR, and virtual temperature in West Java.
Keyword: Model ARIMA indeks MJO, Madden Julian Oscillation, curah hujan deras berpotens banjir

Judul: Prediction Model Development Madden Julian Oscillation (MJO) based on the results of data analysis Real Time Multivariate MJO (RMM1 and RMM2).
Abstrak: Background of this research is the importance of study on the Madden Julian Oscillation, the dominant oscillation in the equator area. MJO cycle showed by cloud cluster growing in the Indian Ocean then moved to the east and form a cycle with a range of 40-50 days and the coverage area from 10N-10S. Method that used to predict RMM is Box-Jenkins based on ARIMA (Autoregressive Integrated Moving Average) statistical analysis. The data used RMM daily data period 1 March 1979 –1 March 2009 (30 years). RMM1 and RMM2 is an index for monitoring MJO. This is based on two empirical orthogonal functions (EOFs) from the combined average zonal 850hPa wind, 200hPa zonal wind, and satellite-observed Outgoing Longwave Radiation (OLR) data. The results in form of the Power Spectral Density (PSD) graph Real Time Multivariate MJO (RMM) and long wave radiation (OLR = Outgoing Longwave Radiation) at the position 100°BT, 120°BT, and 140°BT that show the wave pattern (spectrum pattern) and clearly shows the oscillation periods. There is a close relation between RMM1 with OLR at the position 100oBT that characterized the PSD value about 45 day. Through Box-Jenkins method, the prediction model that close to time series data of RMM1 and RMM2 is ARIMA (2,1,2), that mean the forecasts of RMM data for the future depending on one time previously and the error one time before. Prediction model for RMM1 is Zt = 1.681 Z t-1 – 0.722 Z t-2 + 0.041 Zt-3 - 0.02 at-1 - 0.05 at-2.. Prediction model for RMM2 is Zt = 1.714 Zt-1 – 0.764 Zt-2 - 2 + 0.05 Zt-3 - 0.109 at-1 - 0.05 at- 2.. The flood case in Jakarta January-February 1996 and 2002 are one of real evidence that made the MJO prediction important. MJO with active phase dominant cover almost the entire Indonesia west area at that moment. Keywords: MJO, RMM1 and RMM2, OLR, Power Spectral Density, ARIMA, Rainfall
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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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