Judul: Pemodelan Dampak Madden Julian Osillation terhadap Kebakaran Hutan dan Lahan di Riau
Abstrak: Madden Julian Oscillation (MJO) merupakan fenomena yang berpengaruh terhadap kondisi musim hujan dan kemarau. MJO memiliki efek yang kuat di wilayah Riau. Riau merupakan salah satu daerah rawan kebakaran di Indonesia, seperti peristiwa ekstrem yang terjadi pada tahun 2013 dan 2014. Tujuan penelitian ini yaitu memodelkan dan menganalisis dampak fenomena MJO terhadap kebakaran hutan dan lahan di Riau. Koefisien model ditentukan menggunakan optimasi tanpa kendala dengan memaksimalkan korelasi antara data iklim dan hotspot. Ketika indeks MJO digunakan sebagai fungsi bobot, model yang dibangun berhasil meningkatkan korelasi indikator iklim (hari tanpa hujan dan anomali curah hujan) dengan hotspot. Analisis Heterogenous Correlation Map (HCM) menunjukkan bahwa model 1 (hari tanpa hujan terboboti) lebih berasosiasi dengan hotspot dibandingkan dengan model 2 (anomali curah hujan terboboti). Pada analisis regresi terboboti, performa model 1 cukup baik dalam memprediksi tahun ekstrem (2005, 2013, atau 2014). Namun model 2 gagal dalam memprediksi tahun 2013., Madden Julian Oscillation (MJO) is a phenomenon that affects the condition of the rainy and dry seasons. MJO has a strong effect in Riau. Riau is one of the fire prone areas in Indonesia, as seen in 2013 and 2014. In that year there were quite a high number of forest and land fires in Riau. This study aims to model and analyze the impact of the MJO phenomenon on forest and land fires in Riau. The model coefficients are determined using an unconstrained optimization by maximizing the correlation between climate data and hotspots. When the MJO index is used as a weight function, the built model is successful in increasing the correlation of climate indicators (dry spell and anomaly precipitation) with hotspots. Heterogenous Correlation Map analysis shows that model 1 (weighted dry spell) is more associated with hotspots than model 2 (weighted anomaly precipitation). In the weighted regression analysis, the performance of model 1 is quite good in predicting extreme years (2005, 2013, or 2014). However, model 2 is failed to predict 2013.
Keyword: HCM, hotspot, land and forest fire, MJO, PLS

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: Trichomonas Gallinae Penyebab Trichomonosis Pada Unggas
Abstrak: Trichomonas gallinae adalah protozoa yang bergerak aktof dengan keempat flagella yang mempunyai layar dan pada salah satu sisinya terdapat membran seperti sirip ikan yang berombak. Spesies dari genus Trichomonas ini mempunyai arti penting pada unggas, karena dapat menyebabkan infeksi pada alat pencernaan bagian atas.
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