Judul: Analysis of Determinants of Poverty in Underdeveloped Regions in Sumatra Island
Abstrak: Pulau Sumatra memiliki kinerja ekonomi yang baik bila mengacu pada kontribusi terhadap PDB Nasional. Namun Pulau Sumatra masih memiliki tujuh daerah tertinggal. Kondisi ini diperparah dengan persentase penduduk miskin yang sangat tinggi di tiap daerah tertinggal. Penelitian ini dilakukan untuk memetakan perkembangan kemiskinan daerah tertinggal di Pulau Sumatra dengan menggunakan tipologi Klassen, serta menganalisis faktor-faktor yang mempengaruhi kemiskinan di Daerah Tertinggal di Pulau Sumatra dengan metode analisis regresi data panel. Hasil analisis pemetaan yang dilakukan dengan tipologi klassen menunjukkan Kabupaten Nias Utara konsisten berada di kuadran dengan persentase kemiskinan tinggi dan PDRB per kapita rendah selama periode penelitian. Sedangkan mayoritas kabupaten lainnya berpindah posisi kuadran. Hasil analisis regresi data panel menunjukkan bahwa faktor yang berpengaruh signifikan menurunkan kemiskinan adalah Panjang jalan dengan kondisi baik, IPM, Belanja modal dan PDRB per kapita. Sementara tingkat pengangguran terbuka (TPT) berpengaruh signifikan meningkatkan kemiskinan. Sedangkan belanja bantuan sosial tidak berpengaruh terhadap kemiskinan daerah tertinggal di Pulau Sumatra., Sumatra Island has shown a strong economic performance in terms of its contribution to the national GDP. However, the island still has seven underdeveloped regions. This situation is further exacerbated by a high percentage of poverty in each of these underdeveloped areas. This research aims to map the progress of poverty in these underdeveloped regions of Sumatra Island using the Klassen typology, and to analyze the faktors influencing poverty in these regions through panel data regression analysis. The mapping analysis conducted using the Klassen typology consistently places North Nias Regency in the quadrant with a high poverty percentage and low per capita gross regional domestic product (PDRB) throughout the study period. Meanwhile, most other regencies have shifted their quadrant positions. The panel data regression analysis results indicate that significant faktors reducing poverty include the length of well-maintained roads, the Human Development Index (HDI), capital expenditure, and per capita PDRB. On the other hand, the open unemployment rate (TPT) significantly increases poverty. Social assistance spending does not have an effect on poverty in the underdeveloped regions of Sumatra Island
Keyword: Determinants of poverty, panel data regression, Sumatra Island, Underdeveloped Regions

Judul: Implementation of Spatial Durbin Model in Determining the Factor that Affect Poverty in North Sumatra Province
Abstrak: Kemiskinan merupakan masalah ekonomi yang menjadi salah satu masalah utama di Indonesia. Provinsi Sumatra Utara menduduki peringkat kedelapan berdasarkan jumlah penduduk miskin terbanyak di Indonesia dan peringkat ke-13 berdasarkan persentase penduduk miskin terbanyak di Indonesia. Berbagai upaya yang telah dilakukan pemerintah Provinsi Sumatra Utara untuk membantu penduduk miskin, seperti pemberian Bantuan Langsung Tunai (BLT). Namun demikian, faktor-faktor yang memengaruhi kemiskinan perlu diidentifikasi sehingga dapat digunakan untuk membantu pemegang kebijakan dalam membuat strategi untuk menurunkan angka kemiskinan. Oleh karena itu, penelitian ini bertujuan mengidentifikasi faktor-faktor yang memengaruhi kemiskinan di Provinsi Sumatra Utara dengan menggunakan regresi spasial. Penelitian ini menggunakan data sekunder dari Badan Pusat Statistik (BPS) Provinsi Sumatra Utara pada tahun 2021. Hasil penelitian menunjukkan bahwa data memiliki keragaman antar lokasi sama namun terdapat autokorelasi spasial. Model regresi spasial terbaik yang diperoleh adalah Spatial Durbin Model (SDM) dengan nilai AIC sebesar 178,6529 dan nilai R^2 sebesar 0,8340. Model ini lebih baik dibandingkan dengan Spatial Autoregressive Model (SAR) karena memiliki nilai AIC yang lebih kecil dan R^2 yang lebih besar. Peubah persentase rumah tangga yang memiliki akses terhadap air minum layak mengindikasikan adanya asosiasi positif terhadap persentase penduduk miskin di Provinsi Sumatra Utara. Adapun, peubah pengeluaran per kapita disesuaikan, umur harapan hidup, dan tingkat partisipasi angkatan kerja mengindikasikan adanya asosiasi negatif terhadap persentase penduduk miskin di Provinsi Sumatra Utara., Poverty is an economic problem, which is one of the main problems in Indonesia. North Sumatra province is ranked eighth based on the highest number of poor people in Indonesia and ranked 13th based on the highest percentage of poor people in Indonesia. Various of efforts have been made by the government of North Sumatra to reduce poverty, such as the provision of direct cash assistance (BLT). However, it is worth looking at the factors that significantly affect poverty. Therefore, this study will identify the factors that affect poverty in the Province of North Sumatra by using spatial regression. This study uses secondary data from the Central Statistics Agency (BPS) North Sumatra in 2021. The results show that the data has the same variation between locations but there is spatial autocorrelation. The spatial Regression Model that is suitable for use is the Spatial Durbin Model (SDM) with an AIC value of 178,6529 and an R^2 value of 0,8340. This Model compares favorably with the Spatial Autoregressive Model (SAR) due to it’s lower AIC value and a higher R^2. The percentage of households that have access to decent drinking water indicate a positive association on the percentage of poor people in North Sumatra. However, the adjusted expenditure per capita, life expectancy, and labor force participation rates indicate a negative association on the percentage of poor people in North Sumatran Province.
Keyword: kemiskinan, regresi spasial, Spatial Autoregressive Model, Spatial Durbin Model, poverty, spatial regression

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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