Judul: Spatiotemporal Panel Regression Analysis Using Dynamic Spatial Durbin Model on Leprosy Prevalence in Island of Java
Abstrak: Kusta adalah penyakit menular kronis yang menyerang kulit dan sistem saraf. Indonesia menduduki peringkat ketiga sebagai negara dengan kasus kusta terbanyak pada tahun 2021, dengan Pulau Jawa berkontribusi hampir setengah dari kasus tersebut. Faktor sosial ekonomi dan sosial demografi merupakan beberapa faktor yang menyebabkan tingginya prevalensi penyakit ini di Pulau Jawa. Studi ini bertujuan untuk memperkirakan pengaruh peubah-peubah tersebut terhadap kejadian kusta di Pulau Jawa dari tahun 2017 hingga 2021 melalui analisis spasiotemporal. Model yang digunakan adalah model spasial dinamis Durbin, yaitu model yang menggabungkan dependensi spasial, temporal, dan spasiotemporal dari peubah dependen bersama dengan lag spasial dari peubah dependen. Hasil penelitian menunjukkan bahwa penggunaan matriks bobot spasial queen's contiguity menghasilkan model terbaik, dengan 86,46% keragaman dalam data dapat dijelaskan oleh model. Lag temporal dan spasiotemporal ditemukan signifikan, keduanya berdampak positif terhadap tingkat prevalensi kusta. Peubah penjelas yang ditemukan signifikan adalah harapan lama sekolah, kepadatan penduduk, dan persentase sanitasi yang baik. Harapan lama sekolah di wilayah tersebut ditemukan berdampak negatif terhadap tingkat prevalensi, kepadatan penduduk di wilayah yang berdekatan ditemukan mempengaruhi prevalensi kusta secara, dan persentase sanitasi layak di wilayah terdekat ditemukan berdampak negatif terhadap prevalensi kusta, namun kedua peubah tidak mempengaruhi tingkat prevalensi kusta pada daerah yang sama., Leprosy is a chronic infectious disease which affects the skin and nervous system. As of 2021, Indonesia ranks third as the country with highest amount of leprosy case, with the Island of Java contributing nearly half of those cases. Socioeconomic and sociodemographic factors are among the many aspects which caused the high of prevalence within the island. This study attempts to estimate the effects of those variables to leprosy incidence in Java Island from 2017 to 2021 through spatiotemporal analysis. Dynamic spatial Durbin model (DSDM), a model which incorporates both spatial, temporal, and spatiotemporal lag from the dependent variable together with spatial lag from the dependent variable is used. The results showed that the use queen’s contiguity spatial weighting matrix results in the best model, with 86.46% variance within the data is able to be explained by the model. Temporal and spatiotemporal lag was found to be significant, with both of them positively affecting leprosy prevalence levels. The regressors that was found to be significant was expected years of school, population density, and percentage of proper sanitation, with expected years of school within the region was found to negatively affect prevalence levels, population density in nearby regions found to positively affect leprosy prevalence, and percentage of proper sanitation in nearby regions was found to negatively affect leprosy prevalence. However, both variables does not affect leprosy prevalence within the same region.
Keyword: Leprosy, Dynamic Spatial Durbin Model, Spatiotemporal Analysis

Judul: Geographically Weighted Negative Binomial Regression Modeling (Case study: The Number of Leper in West Java)
Abstrak: Banyaknya penderita kusta merupakan contoh kejadian cacah. Analisis yang dapat digunakan untuk memodelkan data cacah adalah regresi Poisson. Penelitian ini bertujuan untuk menentukan peubah-peubah yang berpengaruh terhadap banyaknya penderita kusta di Jawa Barat tahun 2019. Data yang digunakan merupakan data banyaknya penderita kusta tahun 2019 di tiap kabupaten/kota di Jawa Barat. Data pada penelitian ini memiliki kondisi overdispersi dan heterogenitas spasial antar kabupaten/kota. Overdispersi perlu diatasi dengan pemodelan regresi binomial negatif. Sedangkan heterogenitas spasial diatasi dengan menambahkan pembobot adaptive bisquare kernel pada regresi binomial negatif. Penelitian ini menghasilkan sepuluh kelompok kabupaten/kota di Jawa Barat berdasarkan peubah-peubah yang berpengaruh signifikan terhadap banyaknya penderita kusta melalui model Geographically Weighted Negative Binomial Regression (GWNBR) dengan pembobot adaptive bisquare kernel. Secara umum peubah persentase rumah tangga ber-Perilaku Hidup Bersih dan Sehat (ber-PHBS) berpengaruh signifikan di seluruh kabupaten/kota di Jawa Barat. Khusus untuk Kabupaten Bogor, Kota Depok, Kota Bogor, dan Kabupaten Pangandaran peubah persentase penduduk miskin tidak berpengaruh signifikan terhadap banyaknya penderita kusta., The number of leper in West Java is an example of the count data case. The analyzes commonly used in count data is Poisson regression. This research will determine the variables that influence the number of leper in West Java. The data used is the number of leper in West Java in 2019. This data has an overdispersion condition and spatial heterogenity. To handle overdispersion, the negative binomial regression model can be employed. While spatial heterogenity is overcome by adding adaptive bisquare kernel weight. This research resulted Geographically Weighted Negative Binomial Regression (GWNBR) with a weighting adaptive bisquare kernel classifies regency/city in West Java into ten groups based on the variables that sigfinicantly influence the number of leper. In general, the variable in the percentage of households with Clean and Healthy Behavior (PHBS) has a significant effect in all regency/city in West Java. Especially for Bogor Regency, Depok City, Bogor City, and Pangandaran Regency, the variable of the percentage of people poverty does not have a significant effect on the number leper.
Keyword: Leper, negative binomial regression, Poisson regression, overdispersion, geographically weighted negative binomial regression

Judul: Sintesis dan Pencirian Natrium Titanat (Na2Ti2O4(OH)2) Berbahan Dasar Titanium Dioksida
Abstrak: TiO2 can be utilized as basic material for synthesis of sodium titanate (Na2Ti2O4(OH)2). This research was purposed to synthesize and characterize sodium titanate from TiO2 rutile powder as a basic material. Sodium titanate was synthesized by hydrothermal process at temperature 130 °C by mixing TiO2 rutile powder with 5 M and 10 M NaOH solution, then each was calcinated at temperature 700 °C. The energy dispersive X-ray analysis showed that sodium titanate has been successfully synthesized. This result was also supported by functional group analysis with Fourier transform infrared (FTIR) spectrofotometer showing the existence of Ti-O-Na vibration band at 989.42 cm-1. The formation of sodium titanate was depend on the reaction condition such as temperature, reaction time, and NaOH concentration. Scanning electron microscope image indicated that sodium titanate synthesized at 130 °C in 20 hours reaction time with 10 M NaOH had crystal size of 99.37 nm.
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