Judul: Study of Overdispersion Poisson Regression with Negative Binomial Regression then That Application on Amount of Infant Deaths in Indonesian at 2012.
Abstrak: Model regresi Poisson adalah model standar yang digunakan untuk memodelkan respons data cacahan. Pada penelitian ini model regresi Poisson digunakan untuk membangun model antara jumlah kematian bayi di Indonesia sebagai peubah respons (Y) dan beberapa faktor yang mempengaruhi jumlah kematian bayi sebagai peubah bebas (X). Salah satu asumsi yang harus dipenuhi dalam model regresi ini adalah asumsi equidispersi. Namun dalam penerapannya seringkali asumsi equidispersi tidak terpenuhi. Apabila nilai harapan peubah respons tersebut tidak sama dengan nilai ragam dari peubah respons tersebut, maka kejadian ini disebut Overdispersi. Overdispersi menyebabkan keterandalan dari hasil analisis regresi Poisson menjadi bias. Alternatifnya Regresi Binomial Negatif digunakan untuk mengatasi data yang mengandung overdispersi. Pada penelitian ini dilakukan simulasi dengan membangkitkan peubah respons (Y) dan 2 peubah penjelas (X1 dan X2). Hasil simulasi pada penelitian ini menunjukkan bahwa model regresi Binomial Negatif lebih baik digunakan daripada model regresi Poisson pada data yang mengalami fenomena overdispersi, terlihat dari nilai AIC yang lebih kecil. Pada model aplikasi data rill terindikasi adanya overdispersi, oleh karena itu fenomena overdispersi pada data kematian bayi ditangani dengan model regresi Binomial Negatif. Hasil analisis menunjukkan bahwa faktor-faktor yang mempengaruhi jumlah kematian bayi antara lain: persentase kemiskinan, rasio jumlah bidan terhadap seratus penduduk dan rata-rata umur ibu pada saat pertama kali melahirkan.
Keyword: Bogor Agricultural University, Institut Pertanian Bogor, IPB, AIC, Negative Binomial Regression, Overdispersion, Poisson regression, Angka kematian bayi, Model regresi binomial negatif, Metode simulasi, Kajian simulasi

Judul: Model Regresi Binomial Negatif Terboboti Geografis untuk Data Kematian Bayi (Studi Kasus 38 Kabupaten/Kota di Jawa Timur)
Abstrak: Negative binomial regression model is used to overcome the overdispersion in Poisson regression model. This model can be used to model the relationship of the infant mortality and the factors incidence. Geographical conditions, socio cultural and economic differ one of location another location causes the factors that influence infant mortality is different locally. Geographically Weighted Negative Binomial Regression (GWNBR) is one of methods for modeling that count data have spatial heterogeneity and overdispersion. The basic idea of this model considers of geography or location as the weight in parameter estimation. The parameter estimator is obtained from Iteratively Newton Raphson method. This research will determine the factors that influence infant mortality. GWNBR model with a weighting adaptive bi-square kernel function classifies regency/city in East Java into 16 groups based on the factors that significantly influence the number of infant mortality. This model is better used to analyze the number of infant mortality in East Java in 2008 due to a smallest deviance value.
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Judul: Characterizations of low alloy steel sae 4422  plated with chromic acid (Cro3)
Abstrak: Characterizations of low alloy steel SAE 4422 plated with chromic acid (CrOrO3) was use Optical Microscopy (OM), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), RD),Energy Dispersive Analysis of X-Ray (EDAX), Hardness Test and Roughness Test. Microstructures analysis exhibits cracks and grain boundaries microcracks as a characteristics of chrome metal found at plating metal. Perlite and Ferrite as grains of steel found at base metal with grain boundaries around it. Phase analysis of plating metal appropriate to chrome metal with lattice constant (a) is 2.559 Å and phase analysis of base metal appropriate to iron ferrite with lattice constant (a) is 3.318 Å. Both plating and base metal have cubic system. Chemical analysis of plating metal at surface section exhibits that cracks area have highest value of carbon element compare with grains and grains boundaries area. While chemical analysis of base metal at cross section exhibits that perlite have highest value of carbon element compare with ferrite and grain boundaries. The hardness value of plating metal at surface section and cross section are 753 and 637 VHN. While, the hardness value of base metal and interface area at cross section are 205 and 373 VHN. The roughness value at measurement points of chrome surface for as received sample are 0.445 μm. Observation used Optical Microscopy and Scanning Electron Microscopy exhibits surface irregularities combine to form surface texture of plating metal at surface section.
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