Judul: Regresi Komponen Utama dengan Pemodelan Sisaan ARCH/GARCH
Abstrak: Suhu merupakan salah satu unsur cuaca yang sangat penting karena dapat memberikan informasi mengenai pola curah hujan dan fenomena iklim ekstrim seperti El Nino dan La Nina. Badan Meteorologi Klimatologi dan Geofisika (BMKG) telah melakukan pemodelan suhu maksimum. Pemodelan yang dilakukan menggunakan Regresi Komponen Utama (RKU) menghasilkan koefisien korelasi (r) sebesar 0.243 dan Root Mean Square Error of Prediction (RMSEP) 1.385. Namun, model ini menghasilkan sisaan yang saling berkorelasi dan ragam sisaan yang tidak homogen. Model deret waktu ARMA dapat mengatasi korelasi antar sisaan, dan Autoregressive Conditional Heteroscedasticity (ARCH) atau Generalized Autoregressive Conditional Heteroscedasticity (GARCH) merupakan model yang dibentuk untuk menangani masalah ketidakhomogenan ragam. Pemodelan ARMA dan ARCH/GARCH digunakan untuk mengatasi kedua masalah tersebut. Tujuan penelititan ini adalah memodelkan suhu maksimum menggunakan regresi komponen utama dengan pemodelan sisaan ARCH/GARCH. Hasil menunjukkan bahwa model GARCH (2,1) merupakan model ragam terbaik dengan model rataan ARMA (1,1) yang memberikan nilai korelasi dan RMSEP yang sama dengan model RKU yang dilakukan oleh BMKG, tetapi model regresi komponen utama dengan pemodelan sisaan ARCH/GARCH terbukti mampu mengatasi masalah korelasi antar sisaan dan ketidakhomogenan ragam sisaan.
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Judul: Penggunaan ARCH/GARCH dalam Penanganan Heteroskedastisitas Ragam Sisaan (Studi Kasus: Curah Hujan Bulanan Stasiun Kalijati)
Abstrak: Rainfall data collected by BMKG are classified as time series data because the data is observed in the same time interval. Some problems such as serial correlation, nonstationarity in variance and mean of the data, and heteroscedasticity in the residual of the ARIMA model are frequently found particularly in the fluctuated rainfall data. The nonstationarity of variance can cause variance heteroscedasticity in ARIMA model, therefore a more sufficient ARCH/GARCH model is needed to overcome this problem. The variance of the monthly rainfall data in Kalijati Station from 1991 to 2012 was not stationary. Therefore this study used ARCH/GARCH method to handle heteroscedasticity problem which was found in ARIMA model of the rainfall data. Modeling the residual variance using ARCH/GARCH method obtained a smaller MAD value than ARIMA modeling. ARIMA (0,1,1) x (0,1,1)12 – GARCH (1,1) was the best simultaneous model which did not contain heteroscedasticity in the residual variance. The ARIMA (0,1,1) x (0,1,1)12 – GARCH (1,1) model forecasted that the monthly rainfall average in 2013 year was 279 mm with the highest monthly rainfall occuring on January 2013, which was 454 mm.
Keyword: GARCH, ARIMA, ARCH

Judul: Morfologi Organ Reproduksi Betina Walet Linchi (Collocalia linchi)
Abstrak: This research is aimed to describe the morphology of the female reproductive organs of the cave swiftlets (C. linchi ) macroscopic and microscopically. Four female reproduction organs were used in this study. Microscopic observation was done using Hematoxilin – eosin (HE), alcian blue (AB) pH 2.5 and periodic acid Schiff (PAS) staining methods. The reproductive organs were consisted of ovarium and oviduct. The oviduct has five parts: infundibulum, magnum, isthmus, uterus and vagina. The mucosa of oviduct has mucosal folds and lined with columnar ciliated epithelial cells. Glandular glands were found in the lamina propria of oviduct, except in the vagina. The thick muscle of sphincter uterovagina was found in the border between uterus and vagina. Using AB-PAS staining methods, it was detected that oviduct contained neutral and acid carbohydrate, especially in the secrete glands of oviduct.
Keyword: oviduct., ovarium, Collocalia linchi