Judul: Pemodelan Indeks Pembangunan Manusia Kabupaten dan Kota di Pulau Jawa Tahun 2022 Menggunakan Geographically Weighted Regression
Abstrak: Indeks Pembangunan Manusia (IPM) sangat penting untuk melihat capaian pembangunan manusia di suatu wilayah. Pulau Jawa memiliki ketimpangan nilai IPM baik antarprovinsi maupun antarkabupaten/kota yang memungkinkan adanya heterogenitas spasial. Heterogenitas spasial dapat menimbulkan adanya hubungan yang berbeda antara peubah respons dengan peubah penjelas di setiap lokasinya yang disebut nonstasioneritas spasial. Oleh karena itu, metode yang dapat digunakan adalah Geographically Weighted Regression (GWR). Tujuan dari penelitian ini adalah menentukan fungsi pembobot kernel terbaik karena sangat memengaruhi model GWR dan menentukan peubah-peubah yang berpengaruh signifikan terhadap IPM kabupaten/kota di Pulau Jawa tahun 2022. Penelitian ini menggunakan data IPM yang disediakan oleh Badan Pusat Statistik dan Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi pada tahun 2022. Hasil penelitian menunjukkan bahwa fungsi pembobot kernel terbaik adalah adaptive Gaussian dengan AICc sebesar 601,422. Terdapat tiga kelompok kabupaten/kota berdasarkan peubah penjelas yang signifikan. Persentase penduduk miskin, persentase rumah tangga dengan akses terhadap sanitasi layak, produk domestik regional bruto per kapita, upah minimum, banyaknya rumah sakit umum, dan angka partisipasi kasar SMA/sederajat berpengaruh signifikan terhadap IPM pada semua kabupaten/kota di Pulau Jawa, sedangkan tingkat partisipasi angkatan kerja tidak berpengaruh signifikan. Peubah yang memiliki pengaruh paling besar pada setiap kabupaten/kota di Pulau Jawa adalah persentase penduduk miskin., Human Development Index (HDI) is very important to see the achievements of human development in a region. Java Island has inequality in HDI values both between provinces and districts/cities, which allows spatial heterogeneity. Spatial heterogeneity can have a different relationship between dependent variable and independent variables at each location, which is called spatial nonstationerity. Therefore, a method that can be used is Geographically Weighted regression (GWR). The purpose of this research is to determine the best kernel weighting function because it greatly affects the GWR model and determine the variables that have a significant effect on the HDI of districts/cities in Java Island in 2022. This research used HDI data provided by Statistics Indonesia and the Ministry of Education, Culture, Research, and Technology in 2022. The results showed that the best kernel weighting function was adaptive Gaussian with AICc of 601,422. There were three groups of districts/cities based on significant independent variables. The percentage of poor people, percentage of households with access to proper sanitation, gross regional domestic product per capita, minimum wage, number of public hospitals, and gross enrollment rate of senior high school/equivalent had a significant effect on HDI in all districts/ cities in Java Island, while the labor force participation rate had no significant effect. The variable that has the largest effect in each district/city in Java Island is the percentage of poor people.
Keyword: regresi, regression, spatial heterogeneity, geographically weighted regression, heterogenitas spasial, indeks pembangunan manusia, pulau jawa, human development index, java island

Judul: Spatial Analysis for the Distribution of Human Development Index and Regional Government Budget in Java Provinces
Abstrak: Indeks Pembangunan Manusia Tahun 2012 mengalami ketimpangan antara pedesaan dan perkotaan di Pulau Jawa. Hal ini disebabkan wilayah perkotaan yang memiliki perkembangan lebih baik dibandingkan wilayah pedesaan. Di sisi lain, perpindahan penduduk dari kabupaten ke kota merupakan salah satu faktor penyebab ketimpangan tersebut.Adapun dampak perpindahan penduduk dari kabupaten ke kota menyebabkan rendahnya kualitas sumber daya manusa di wilayah kabupaten. Angka IPM kabupaten dan kota di Pulau Jawa dihitung berdasarkan komponen-komponen penyusunnya yaitu angka harapan hidup, angka melek huruf, rata-rata lama sekolah, dan pengeluaran riil per kapita.Setiap komponen penyusun IPM diduga memilikikorelasi spasial. Analisis korelasi spasial yang digunakan untuk menghitung sebaran angka IPM dalam kajian ini adalah Local Indicator of Spatial Autocorrelation (LISA)., There is a gap ofHuman Development Index (HDI) between regency and city in Java. This is due to the faster development of urban areas be compared to rural areas. On the other hand, movement from the regency to city is one of the causes of these imbalances. The impact of migration from the regency to city is low quality of human resources in the regency. HDI figures of regencies and cities in Java are calculated from the components of life expectancy, literacy rate, average length of education, and income per capita. Each component of the HDI is expected to have spatial influence. Calculating of the HDI is usedLocal Indicator of Spatial Autocorrelation (LISA).
Keyword: Human Development Index, LISA, Regional Government Budget, General Spatial Model

Judul: Sintesis Flavon dari Fenol dan Benzoil Klorida
Abstrak: Flavone is a class of flavonoid, commonly found in plants with wide bioactivity spectrum. A widely used flavone synthesis route is through acidcatalyzed oxidative cyclization of β-diketone. In this study, unsubstituted flavone had been synthesized via 5-step from phenol, with 22% yield and successfully increased the yield of previous study on Fries rearrangement of phenyl acetate and benzoylation of o-HAP steps. Phenol was acetylated resulting 93% phenyl acetate. AlCl3-catalyzed Fries rearrangement in 1.5 hour and at 120 °C converted phenyl acetate into o-hydroxyacetophenone (o-HAP) with 40% yield. AlCl3 as catalyst produced o-HAP with higher and reproducible yield compared with BF3·Et2O and ZnCl2. Benzoylation of o-HAP followed by Baker-Venkataraman rearrangement of the ester product using KOH in dried pyridine produced β-diketone 1-(2- hydroxyphenyl)-3-phenylpropane-1,3-dione. The yield of ester and β-diketone were 71% and 85%, respectively. Finally, oxidative cyclization of β-diketone with sulphuric acid as catalyst produced 99% of flavone. The flavone product had been characterized spectroscopically and its melting point as well.
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