Judul: Pemodelan Kemiskinan di Pulau Jawa Tahun 2012 sampai 2018 dengan Panel Spasial Dinamis
Abstrak: Tiga provinsi di Pulau Jawa memiliki persentase kemiskinan di atas rata-rata nasional sebesar 10.19% pada 2020. Salah satu metode untuk mengidentifikasi faktor-faktor yang memengaruhi persentase kemiskinan adalah panel spasial dinamis. Penelitian ini bertujuan untuk menentukan model panel spasial dinamis terbaik berdasarkan matriks pembobot spasial dan menentukan peubah-peubah yang memengaruhi persentase kemiskinan di Pulau Jawa. Matriks pembobot yang dibandingkan adalah ketetanggaan langkah ratu, dua tetangga terdekat, invers jarak, dan eksponensial jarak. Data yang digunakan di penelitian ini antara lain persentase kemiskinan sebagai peubah respon, sedangkan pendapatan domestik regional bruto, persentase pendidikan yang ditamatkan SD ke bawah, angka melek huruf, persentase pengeluaran per kapita, persentase penduduk usia produktif, harapan lama sekolah, rata-rata lama sekolah, dan persentase banyaknya puskesmas sebagai peubah penjelas yang diamati tahun 2012-2018 di Pulau Jawa. Metode yang digunakan meliputi eksplorasi data, uji dependensi, dan analisis panel spasial dinamis. Hasil penelitian menunjukkan bahwa terdapat dependensi spasial pada peubah respon dan penjelas sehingga digunakan adalah model spasial Durbin. Model terbaik adalah model panel spasial Durbin dinamis dengan pengaruh tetap dan matriks pembobot dua tetangga terdekat. Peubah yang berpengaruh signifikan terhadap persentase kemiskinan adalah angka melek huruf, persentase penduduk umur produktif, dan persentase puskesmas. Efek marginal menunjukkan peningkatan pendapatan domestik regional bruto, persentase pendidikan yang ditamatkan SD kebawah, angka melek huruf, dan pengeluaran per kapita dapat menurunkan persentase kemiskinan bagi suatu kabupaten/kota di Pulau Jawa., Three provinces in Java had poverty percentages above the national average at 10.19% in 2020. One of the methods to identify the factors that affect poverty is the dynamic spatial panel model. This research aims to determine the best dynamic spatial panel model based on several spatial weighting matrices and identify the variables that affect the percentage of poverty in Java Island. The weighted matrices compared in this research were queen contiguity, two nearest neighbors, inverse distance, and exponential distance. The data used in this research were the percentage of poverty as response variable, meanwhile the gross domestic product, the percentage of education completed by elementary school, the literacy rate, expenditure per capita, percentage of the productive age population, expected of length school, the average of length school, and percentage of health centers as predictor variables observed in 2012-2018 on Java Island. The methods used were data exploration, dependency test, and dynamic spatial panel analysis. The results of the spatial autocorrelation test show that there was a spatial dependency on the dependent variable and predictors, so the model used was the Durbin spatial model. The best model was a dynamic spatial Durbin panel with a fixed effect and two nearest neighbor weighting matrices. Predictors that significantly affect poverty were the literacy rate, percentage of the productive age population, and the percentage of health centers. The marginal effect shows that an increase of gross domestic product, the percentage of education completed by elementary school, the literacy rate, and expenditure per capita could reduce the percentage of the city in Java.
Keyword: efek marginal, kemiskinan, panel spasial dinamis, dynamic spatial panel model, marginal effect, poverty

Judul: Pemodelan Autoregresif Spasial pada Data Panel (Studi Kasus Kemiskinan di Jawa Timur)
Abstrak: Penelitian ini bertujuan mengidentifikasi peubah-peubah yang berpengaruh terhadap persentase kemiskinan di Jawa Timur pada tahun 2017-2020. Metode yang digunakan untuk menjawab tujuan tersebut adalah analisis spasial data panel. Matriks pembobot yang digunakan adalah matriks jarak invers, matriks jarak eksponensial, dan matriks jarak k-tetangga terdekat. Data yang digunakan dalam penelitian ini adalah persentase kemiskinan sebagai peubah respon, sedangkan peubah penjelasnya adalah Indeks Pembangunan Manusia (IPM), Tingkat Pengangguran Terbuka (TPT), angka harapan hidup, rata-rata lama sekolah, rumah tangga yang memiliki akses terhadap sanitasi layak, rumah tangga dengan sumber air minum yang layak, dan pengeluaran rata-rata per kapita sebulan. Hasil analisis menunjukkan bahwa terdapat ketergantungan spasial pada peubah respon dan pengaruh waktu di dalam model data panel sangat kecil sehingga dapat diabaikan. Oleh karena itu, model yang digunakan adalah model panel spatial autoregressive (SAR) dengan pengaruh tetap efek individu dan matriks pembobot jarak 2-tetangga terdekat. Hasil penelitian menunjukkan bahwa peubah-peubah yang berpengaruh signifikan terhadap persentase kemiskinan di Jawa Timur pada tahun 2017-2020 adalah tingkat pengangguran terbuka, angka harapan hidup, dan rata-rata pengeluaran per kapita sebulan., The objective of this reserch is to identify the variables that affect the percentage of poverty in East Java from 2017 to 2020. The method used to answer this objective is spatial analysis of panel data. The weighting matrix used is the inverse distance, exponential distance, and k-nearest neighbor. The data used in this research were the percentage of poverty as response variable, meanwhile the predictor variables include the human development index, open unemployment rate, life expectancy rate, average of length school, households that have access to decent sanitation, households with decent drinking water sources, and average expenditure per capita a month. The result of the analysis show that there is a spatial dependence on the response variable and the effect of time in the panel data model is so small that it can be ignored. Therefore, the model used is spatial autoregressive (SAR) panel model with a fixed effect and an 2-nearest neighbor distance weighting matrix. The result of this study show that the variables that have a significant effect on poverty in East Java from 2017 to 2020 are life expectancy rate, open unemployment rate, and average expenditure per capita a month.
Keyword: poverty, spatial panel model, spatial weighting matrix

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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