Judul: The application of flexible scan statistics in detecting poverty hotspots in Java Island
Abstrak: Poverty hotspot detection is one of the study to know the set of area which has a high number of poverty. Previous study using Circular Spatial Scan Statistics found a problem which is low power to reject null hypothesis since it use circle window as the basis of scan. Flexible scan statistics provide better aproach by using a set of connected regions as window scan. Java Islands is the highest in number of people, with almost 60% of Indonesia people living in Java. By Using SUSENAS 2005 data, we conducted study about poverty hotspot detection using flexible scan statistics in FlexScan 3.05 as the alternatives to handle arbitrary shape of cluster and low power of test in circular spatial scan statistics. The result of the study has showed that flexible scan statistics showed good performance in detecting poverty hotspot, either first, second or third priority area. The average of reliabilty score is 91.15%. Among seven maximum cluster size used in this study, maximum cluster size 10% showed lowest average reliability and the highest average of reliability was shown when maximum cluster size were 20% and 30%.
Keyword: Poverty hotspots, Flexible scan statistics, Java Island

Judul: A modified test in flexibly shaped spatial scan statistic for detecting poverty hotspots.
Abstrak: A flexibly spatial scan statistic was proposed by Tango and Takahashi (2005) that can detect arbitrary shaped clusters (hotspots). In this research, a flexibly shaped spatial scan statistic will be applied to perform poverty hotspots detection in Bogor. Overall population of family in Bogor is 1,094,480 families and 29.44% of families who live in Bogor are categorized as poor family. The problem was flexibly spatial scan statistic use Poisson distribution in their calculation but the poverty rate was too high to be approached by Poisson distribution. In fact that Poisson must be constructed from the number of trials is large and the probability of success is small. We proposed Bernoulli distribution instead of Poisson. This distribution was more suitable to the faced case. That have to be noticed is sampling unit from both the distribution. At Poisson, what becoming sampling unit is village while at Bernoulli the sampling unit is family. Each family has only two possibility status, that are poor and not poor. It was meets the characteristic of Bernoulli distribution. In this proposed method, the events of being poor are independents distributed, so we could find the likelihood function as multiplication of each individual mass function. In this research, the proposed test tends to be more sensitive compared to Septiani (2006), we obtained more significant hotspot. The order of log likelihood ratio statistic was slightly different, there were only minor changes. Septiani’s result using Poisson distribution still relevant to detect poverty hotspots in Bogor.
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Judul: Sintesis 1-Kloro-2-metoksi-6-propilnaftalena-1,3-dioksolana (1:1) sebagai Prekursor Asam (S)-(+)-(6-Metoksi-2-naftil)propanoat
Abstrak: Senyawa 1-kloro-2-metoksi-6-propilnaftalena-1,3-dioksolana (1:1) sebagai prekursor asam (S)-(+)-(6-metoksi-2-naftil)propanoat disintesis dari bahan awal 2-metoksinaftalena. Tahapan sintesis diawali dengan klorinasi menggunakan 2 jenis pereaksi klorinasi, yakni isosianurat terklorinasi dan NaOCl. Klorinasi dengan isosianurat terklorinasi berhasil menyintesis 1-kloro-2-metoksinaftalena sebagai produk monoklorinasi melalui pencirian dengan kromatograf gas-spektrometer massa (GC-MS). Nisbah konversi produk paling efisien diperoleh pada laju penambahan 2.5 mmol/jam. Sebaliknya, klorinasi dengan NaOCl menghasilkan produk triklorinasi. 1-Kloro-2-metoksinaftalena selanjutnya diasilasi dengan propanoil klorida, tetapi analisis dengan GC menunjukkan bahwa produk asilasi tidak terbentuk. Sistem bebas-air diperlukan untuk keberhasilan proses asilasi tersebut.
Keyword: isosianurat terklorinasi, NaOCl, nisbah konversi