Judul: Hubungan Kejadian Simultan El Niño Dan Indian Ocean Dipole (Iod) Terhadap Variasi Suhu Virtual Serta Estimasi Suhu Virtual Menggunakan Metode Arima Dan Holt-Winters
Abstrak: Kejadian El Niño dan IOD Indian Ocean Dipole (IOD) yang terjadi secara simultan pada tahun 1997 menyebabkan penurunan suhu virtual. Hasil rata-rata varians menunjukkan kenaikan index Niño 3.4 dan IOD diikuti oleh penurunan suhu virtual. Hasil Power Spektral Density (PSD) dan Wavelet menunjukkan bahwa osilasi dari kejadian El Niño dan IOD adalah 5 dan 3 tahunan, osilasi suhu virtual dianalisis berdasarkan Autocorrelation Function yaitu 1 tahunan. Besarnya suhu virtual dipengaruhi oleh indeks Niño 3.4, indeks IOD, serta Niño 3.4+IOD sehingga diperlukan analisis regresi multivariat sebelum dilakukan prediksi. Metode Box-Jenkins ARIMA (Autoregressive Integrated Moving Average) yang digunakan untuk prediksi data deret waktu suhu virtual. Model yang dipilih untuk Juanda ARIMA(0,2,2) Zt = 2Zt -1 - Zt -2 + (3.79E-6) + 1.051ɑt-1 – 0.054 ɑt-2 + ɑt, Perak ARIMA(0,2,2) Zt = 2Zt -1 - Zt -2 + (2.35E-6) + 1.057ɑt-1 – 0.059 ɑt-2 + ɑt, Ahmad Yani ARIMA(0,2,3) Zt = 2Zt -1 - Zt -2 + (5.51E-6) +1.267ɑt-1 – 0.126ɑt-2 – 0.143 ɑt-3 + ɑt, Polonia ARIMA(0,2,2) Zt = 2Zt -1 - Zt -2 - (6.55E-7) + 1.072ɑt-1 – 0.075 ɑt-2 + ɑt. Model Holt-Winters yang digunakan untuk prediksi data deret waktu suhu virtual untuk Juanda adalah F(t+m) = (14430.369+ 100.372m)( s(t-s+m)), Perak I adalah F(t+m) = (12987.58+ 82.507m)( s(t-s+m)), Ahmad Yani adalah F(t+m) = (6937.954+ 25.223m)( s(t-s+m)), Polonia adalah F(t+m) = (-3803.505+ 9.272m)( s(ts+ m)). Model prediksi ARIMA dan Holt-Winters dapat digunakan untuk peramalan suhu virtual di empat lokasi.
Keyword: El Niño, IOD, suhu virtual, multivariat, ARIMA, Holt-Winters

Judul: Penerapan Model ARIMA untuk Prediksi Anomali Curah Hujan Berdasarkan Indeks Monsun dan El Niño di Beberapa Kawasan di Indonesia.
Abstrak: This study based on atmosphere-ocean interaction that is very important to be investigated because of its influences to the rainfall variability over Indonesia. This study aims to investigate Monsoon and Niño 3.4 interaction in influencing rainfall fluctuation over Indonesia. The study areas cover Lampung, Sumbawa Besar, Indramayu, Banjarbaru, and Pandeglang from Januari 1976 - Desember 2000. The results of Power Spectral Density (PSD) and Wavelet analysis on rainfall anomaly and monsoon index data show strong at 12 months. Dominant oscillation pattern of Niño 3.4 is about 60 months. The result of regression analyses shows more significant relation between rainfall anomaly and AUSMI (Australian Monsoon Index) and WNPMI (Western North Pacific Monsoon Index). Therefore, it is suggested that the Monsoon (AUSMI and WNPMI) and El-Niño(Niño 3.4) can be used for further analysis. This study was undertaken with assumption that Monsoon oscillation and El-Niño are interacted and the model is developed by using multivariate regression method: Y = a + bAUSMI + cWNPMI + dNiño3.4. By using Box-Jenkins method based on ARIMA (Autoregressive Integrated Moving Average), the prediction model that is close to observed time series data of rainfall anomaly is ARIMA (1,0,1)12 with model equation Zt = 0.9989Zt-12 - 0.9338at-12 + at (AUSMI), ARIMA (1,1,1)12 with model equation Zt = -0.0674Zt-12 + Zt-12 - Zt-24 - 0.9347at-12 + at,(WNPMI), dan ARIMA (2,0,2) with model equation Zt = 3.594Zt-1 -0.8362Zt-2 – 1.634at-1 - 0.1053at-2 + at (NINO3.4). Model equation shows that time series data forecast of rainfall anomaly depend on previous “t” months data and previous ”t” months error.
Keyword: 

Judul: Hydroxyapatite-Chitosan Composite Coating on Stainless Steel 316 to Improve Corrosion Resistance
Abstrak: Metals that were used in bone implantation should have good corrosion resistance that were not easily corroded when implanted into the body. Metal corrosion resistance of stainless steel 316 can be enhanced through the metal coating by hydroxyapatite-chitosan composite with composition ratio of hydroxyapatite (gram) and chitosan 3% (mL) 0.2:0, 0.2:0.1, 0.2:0.5, 0.2:1.0, and 0.2:1.5. Besides improving the corrosion resistance of metal, the presence of chitosan also maintain the position of hydroxyapatite on metal surfaces. Corrosion resistance increases with increasing amount of chitosan added and the best composition of hydroxyapatite-chitosan composite was 0.2:1.0.
Keyword: