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: A Comparative Study of Beta-Binomial Regression and Williams Methods and their Application to Infant Mortality Data in West Java
Abstrak: Regresi logistik Binom dapat digunakan untuk mengetahui faktor-faktor yang mampu menjelaskan tingkat kematian bayi. Namun, jika data mengandung overdispersi, regresi logistik Binom sudah tidak relevan lagi untuk digunakan. Overdispersi seringkali terjadi pada data biner, seperti pada data kematian bayi. Untuk menangani masalah overdispersi, regresi Beta-Binom dan metode Williams akan dibahas pada penelitian ini. Nilai dugaan parameter yang dihasilkan dengan menggunakan ketiga metode ini tidak berbeda secara signifikan, tetapi nilai galat baku dugaan parameter yang dihasilkan oleh metode regresi logistik Binom cenderung berbias kebawah (underestimate). Hasil simulasi menunjukkan bahwa metode Williams menghasilkan penduga yang lebih baik, ditinjau dari nilai bias dan ragam penduga parameternya dibandingkan dengan regresi Beta-Binom. Selanjutnya, untuk mengindetifikasi faktor-faktor yang mampu menjelaskan tingkat kematian bayi di Jawa Barat perlu diterapkan metode Williams dan regresi Beta-Binom terhadap data kematian bayi di Jawa Barat tahun 2012. Faktor-faktor yang mampu menjelaskan kematian bayi di Jawa Barat yaitu kekayaan rumah tangga, usia ibu, pendidikan ibu dan tempat tinggal.
Keyword: Institut Pertanian Bogor, IPB, Bogor Agricultural University, Beta-Binom regression, Binomial logistic regression, Infant mortality, Overdispersion, Williams methods, Analisis regresi liestik, Overdispersi, Simulasi

Judul: Sintesis Flavonol melalui 2’-Hidroksikalkon
Abstrak: Flavonol is a class of flavonoids commonly found in fruits and vegetables. Flavonol is very useful, especially in food sector and health. In this study, flavonol unsubstituted was successfully synthesized from an intermediate material 2’-hydroxychalcone. The 2’-hydroxychalcone was synthesized by Claisen-Schmidt condensation method between o-hydroxyacetophenone and benzaldehyde using 4 different catalysts, namely KOH 60%, solid pellet of KOH-grinding technique, BF3-Et2O, and NaH in DMF. The KOH 60% was the best catalyst, giving the highest yield (57%). Afterward, the flavonol was synthesized in 1-stage oxidation cyclization of o-hydroxyacetophenone using Algar-Flynn-Oyamada (AFO) reaction, giving 76%. The flavonol total yield from 2’-hydroxychalcone was 43%. All synthesized products were characterized by their melting points and their spectra. The success of the synthesis flavonol opens the way to synthesis of useful flavonol derivatives such as quercetin and kaempferol
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