Judul: Factors Influencing Stunting Cases in West Java in 2021  Using Negative Binomial Spatial Regression
Abstrak: Stunting merupakan gangguan pertumbuhan dan perkembangan pada anak yang ditandai dengan tinggi badan anak berada di bawah standar. Provinsi Jawa Barat dengan angka prevalensi stunting 24,5 persen merupakan salah satu provinsi yang termasuk dalam 12 provinsi prioritas untuk menjalankan rencana aksi nasional percepatan penurunan stunting. Kasus stunting merupakan data cacah dan kejadiannya jarang terjadi. Analisis yang dapat digunakan adalah regresi Poisson. Asumsi yang harus dipenuhi pada regresi Poisson adalah equidispersi namun sulit dipenuhi karena kondisi overdispersi. Salah satu cara mengatasi overdispersi adalah menggunakan analisis regresi binomial negatif. Kasus stunting di Provinsi Jawa Barat terindikasi adanya efek spasial sehingga perlu digunakan pemodelan spasial. Penelitian ini bertujuan menentukan peubah yang memengaruhi kasus stunting di Provinsi Jawa Barat tahun 2021 dengan menggunakan regresi spasial binomial negatif. Hasil penelitian menunjukkan terdapat overdispersi. Uji efek spasial menunjukkan tidak terdapat heterogenitas pada data, terdapat dependensi spasial pada robust lag, dan terdapat dependensi spasial pada beberapa peubah penjelas. Hasil penelitian menunjukkan model terbaik dengan nilai AIC terkecil adalah spatial autoregressive binomial negatif. Peubah yang berpengaruh signifikan terhadap banyaknya stunting adalah persentase bayi berusia kurang dari enam bulan mendapat ASI, persentase tempat pengelolaan makanan memenuhi syarat, dan persentase bayi berat badan lahir rendah., Stunting is a growth and development disorder in children characterized by the child's height being below standard. With a stunting prevalence rate of 24.5 percent, West Java province is one of the provinces included in the 12 priority provinces for carrying out the national action plan to accelerate stunting reduction. Stunting cases are count data, and their occurrence is rare. The analysis that can be used is Poisson regression. The assumption that must be fulfilled in Poisson regression is equidispersion, but it isn't easy to fulfill because of the overdispersion condition. One way to overcome overdispersion is to use negative binomial regression analysis. The case of stunting in West Java Province indicated a spatial effect, so it was necessary to use spatial modeling. This study aims to determine the variables that affect stunting cases in West Java Province in 2021 using negative binomial spatial regression. The results showed that there was overdispersion. The spatial effect test indicated that there is no heterogeneity in the data, there is a spatial dependency on RLM lag, and there are spatial dependencies on several variables. The results showed that the best model with the smallest AIC value was a spatial autoregressive negative binomial. Variables that have a significant effected on the number of stunting are the percentage of infants aged less than six months who are breastfed, the rate of places where food management meets the requirements, and the percentage of babies with low birth weight.
Keyword: binomial negatif, overdispersi, spasial, stunting

Judul: Studi Faktor Determinan Stunting pada Anak Usia di Bawah 5 Tahun di Indonesia 2016 - 2022: Analisis Regresi Panel Spasial
Abstrak: Child stunting remains a critical issue for human resource development in Indonesia, despite a 10% reduction in prevalence to 21.6% in 2022. This study employs spatial panel regression to assess and understand the spatial distribution of stunting rates across Indonesian provinces, identify the determinant factors of stunting among children under five, and determine the most effective approach for reducing stunting prevalence as the recommendations. This method is underutilized in supporting policy-making and program development at both national and regional levels. Given significant socio-economic disparities and infrastructural limitations across the archipelago, prioritizing effective interventions is crucial. The findings reveal that the Spatial Autoregressive Model (SAR) with Fixed Effect Model (FEM) with time effects is the best model for analysing stunting prevalence from 2016 to 2022 in Indonesia. The analysis results indicate that high school graduation rates, gender inequality, and unmet health service needs are significant predictors. The selected SAR-FE model demonstrates a coefficient of determination of 67.84% and an AIC of -860.36 using a k-nearest neighbour weighting matrix. This research provides critical insights into the determinants and spatial distribution of stunting in Indonesia, offering policymakers tailored evidence to design effective interventions., Masalah stunting pada anak tetap menjadi isu penting untuk pengembangan sumber daya manusia di Indonesia, meskipun prevalensinya mengalami penurunan sebesar 10% menjadi 21.6% pada tahun 2022. Penelitian ini menggunakan regresi panel spasial untuk mengidentifikasi determinan stunting serta memahami disparitas regional yang terjadi di Indonesia. Tujuan penelitian ini yakni untuk mengidentifikasi distribusi spasial tingkat stunting di seluruh provinsi Indonesia, mengkaji faktor-faktor penentu stunting pada anak di bawah lima tahun, serta menentukan pendekatan paling efektif untuk mengurangi prevalensi stunting dalam bentuk rekomendasi. Hasil di lapangan menyatakan bahwa metode ini masih kurang dimanfaatkan dalam mendukung pembuatan kebijakan dan pengembangan program di tingkat nasional dan regional. Dengan disparitas sosial-ekonomi yang signifikan dan keterbatasan infrastruktur di seluruh kepulauan, prioritas intervensi yang efektif menjadi poin yang sangat krusial. Temuan studi ini mengungkapkan bahwa Spatial Autoregressive Model (SAR) dengan Fixed Effect Model (FEM) atau model pengaruh tetap dengan efek waktu adalah model terbaik untuk menganalisis prevalensi stunting dari tahun 2016 hingga 2022 di Indonesia. Hasil analisis menunjukkan bahwa tingkat kelulusan sekolah menengah atas, ketidaksetaraan gender, dan kebutuhan pelayanan kesehatan yang tidak terpenuhi adalah prediktor signifikan. Model SAR-FE terpilih menunjukkan nilai koefisien determinasi sebesar 67.84% dan AIC sebesar -860.36 dengan menggunakan matriks pembobot k-nearest neighbour.
Keyword: Stunting, disparity, socio-economic, spatial panel, weighting matrices

Judul: Elektrodeposisi Film Tipis Semikonduktor Cu2ZnSnS4 (CZTS) pada Substrat Kaca ITO
Abstrak: Semiconductor Cu2ZnSnS4 (CZTS) thin film that can be used as absorber layers on solar cell module was made via electrodeposition method. CZTS thin film was electrodeposited on the surface of a silicate glass coated with a thin layer of indium tin oxide (ITO). Deposition process was done using potentiostatic mode at room temperature with a potential of 1.05 V for 30, 45, and 60 minutes, followed with annealing the film at 2 different temperatures, 500 ºC using furnace and 180 ºC using hot plate, both treatments for 45 minutes in N2/H2S atmosphere. The X-ray difractograms were analyzed using Match 2 program and showed that the CZTS thin films had kesterit crystalline structure, with a low percentage of CZTS phase. The thin film also contained secondary phases such as Cu2S, ZnS, and SnS. The obtained CZTS thin films had a thickness between 1.039 and 1.676 μm. Absorption study showed that the band gap energy of CZTS thin films which was annealed using furnace ranged from 1.50 to 1.52 eV, whereas that annealed using the hot plate was not observed. The band gap energy value showed that CZTS thin films can be used as sunlight absorber layers on solar cell. The formation of CZTS crystal film on this investigation was effectively performed using furnace annealing process at a temperature of 500 ºC with deposition time of 45 minutes.
Keyword: Thin film, Electrodeposition, Cu2ZnSnS4