Judul: Menginvestigasi Kemiskinan Anak Multidimensi di Indonesia: Pendekatan Regresi Spasial
Abstrak: Child poverty is defined as poor children who experience poverty because of the lack of basic needs (nutrition, education, shelter, drinking water, or health services) that can affect their development or future opportunities (UNICEF 2019). The traditional approach to measure child poverty based on household income can not provide a comprehensive overview of children’s welfare. Therefore, multidimensional child poverty (MCP) that defines poor children by deprivation levels in several dimensions supporting children’s living standards is vitally important for more representative measurement to monitor child poverty. The traditional approach measuring child poverty based on household income can not provide a comprehensive overview of children’s welfare. Therefore, multidimensional child poverty (MCP) that defines poor children by deprivation levels in several dimensions supporting children’s living standards is vitally important for a more representative measurement of child poverty. The thesis is motivated due to several reasons. First, several provinces in Indonesia had a medium level of human capital, while these provinces experienced high MCP rates in 2016. Second, a limited study includes district-level interactions in Indonesia’s child poverty study. It seems plausible to assume that socioeconomic factors generating MCP in one district are correlated to or even influenced by socioeconomic factors in neighbouring districts. Therefore, this thesis investigates the linkage between MCP and its determinants by incorporating spatial analysis. Indonesia’s national socioeconomic survey in March 2020 is used to construct multidimensional poverty experienced by children. Then this thesis analyses the factors influencing MCP at regional levels employing spatial regression analysis. The results find that district-level MCP in Indonesia and its driven factors are spatially correlated. Local household characteristics, industrial structure, and infrastructure strongly determine the MCP at regional levels. The thesis shows that female-headed households and infrastructure have spillover effects towards child poverty. It suggests that reducing childhood poverty at district levels has to consider spatial effects of the local determinants of MCP, such as by investing in women’s empowerment, internet access, and educational infrastructure.
Keyword: Child Poverty, MODA, Regional Poverty, SLX Model

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: Hydroxyapatite-Chitosan Composite Coating on Stainless Steel 316 to Improve Corrosion Resistance
Abstrak: Metals that were used in bone implantation should have good corrosion resistance that were not easily corroded when implanted into the body. Metal corrosion resistance of stainless steel 316 can be enhanced through the metal coating by hydroxyapatite-chitosan composite with composition ratio of hydroxyapatite (gram) and chitosan 3% (mL) 0.2:0, 0.2:0.1, 0.2:0.5, 0.2:1.0, and 0.2:1.5. Besides improving the corrosion resistance of metal, the presence of chitosan also maintain the position of hydroxyapatite on metal surfaces. Corrosion resistance increases with increasing amount of chitosan added and the best composition of hydroxyapatite-chitosan composite was 0.2:1.0.
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