Judul: Driving Factors and Cluster Analysis of Happiness in Indonesia
Abstrak: Kesejahteraan merupakan salah satu tujuan pembangunan negara. Pengukuran keberhasilan pembangunan negara seringnya menggunakan ukuran moneter, seperti produk domestik bruto (PDB). Akan tetapi, PDB berpotensi mengabaikan aspek yang berkontribusi pada kualitas hidup dan kebahagiaan seseorang. Tesis ini berfokus untuk mengkaji faktor-faktor pendorong kebahagiaan di Indonesia dan mengkategorikan provinsi-provinsi tersebut ke dalam kategori-kategori yang memiliki karakteristik serupa agar kebijakan dapat lebih tepat sasaran dan efisien. Indeks kebahagiaan Indonesia yang dihasilkan dari survei kebahagiaan tahun 2021 dianalisis menggunakan metode statistic regresi linier berganda. Hasil penelitian menunjukkan bahwa koefisien Gini berpengaruh negatif terhadap kebahagiaan, dan PDB per kapita memiliki pengaruh positif. Tesis ini selanjutnya mengkategorikan 34 provinsi di Indonesia ke dalam 3 kategori tingkat tinggi, rendah, dan sedang dari nilai masing-masing indikator. Dari hasil tersebut, pemerintah dapat memfokuskan kebijakan terkait ketimpangan antar daerah dan PDB per kapita, berdasarkan karakteristik setiap kluster., Welfare is one of the goals of state development. Measuring the success of a country's development often uses monetary measures, such as gross domestic product (GDP). However, GDP tends to ignore aspects that contribute to a person's quality of life and happiness. This thesis focuses on examining the factors driving happiness in Indonesia and categorizing the provinces into categories that have similar characteristics so that policies can be more targeted and efficient. The Indonesian happiness index resulting from the 2021 happiness survey was analyzed using the multiple linear regression statistical method. The results show that the Gini coefficient has a negative effect on happiness, and GDP per capita has a positive effect. This thesis further categorizes 34 provinces in Indonesia into 3 categories of high, low, and medium levels of the value of each indicator. From these results, the government can focus policies related to inequality between regions and GDP per capita, based on the characteristics of each cluster.
Keyword: happiness, cluster analysis, subjective well-being, Gini coefficient

Judul: Structural Equation Modeling in the Case of Spatial Dependence (Case Study: Happiness Index in Indonesia 2021)
Abstrak: Kesejahteraan masyarakat mencerminkan keberhasilan pembangunan di suatu daerah. Indeks kebahagiaan merupakan indikator subjektif yang dapat menggambarkan kesejahteraan masyarakat di suatu daerah. Pendidikan, ekonomi, kesehatan, dan kemiskinan diasumsikan memiliki pengaruh terhadap indeks kebahagiaan. Penelitian ini bertujuan untuk mengetahui indikator yang paling berpengaruh pada tiap peubah laten serta mengetahui peubah laten yang memengaruhi indeks kebahagiaan menggunakan model spasial. Data penelitian ini diperoleh dari Badan Pusat Statistik (BPS) dengan jumlah indikator adalah 22 yang dikelompokkan ke dalam lima peubah laten. Metode yang digunakan untuk menganalisis hubungan antar peubah laten adalah Structural Equation Modeling (SEM). Pendekatan pada metode analisis SEM untuk jumlah data yang kecil dan tidak memenuhi asumsi distribusi normal adalah Structural Equation Modeling-Partial Least Square (SEM-PLS). Peubah laten yang berpengaruh signifikan terhadap indeks kebahagiaan pada beberapa model spasial adalah lag indeks kebahagiaan dan kemiskinan. Indikator yang paling berpengaruh pada peubah laten kemiskinan adalah indeks kedalaman kemiskinan, sedangkan indikator dari peubah laten indeks kebahagiaan yang paling berpengaruh adalah indeks kepuasan hidup., Community welfare reflects the success of development in an area. The happiness index is a subjective indicator that can describe the welfare of the community in an area. Education, economy, health, and poverty are assumed to have an influence on the happiness index. This study aims to determine the most influential indicator on each latent variable and determine the latent variable that affects the happiness index using a spatial model. The data for this study were obtained from the Badan Pusat Statistik (BPS) with 22 indicators grouped into five latent variables. The method that can be used to analyze latent variables is Structural Equation Modeling (SEM). The approach to the SEM analysis method for a small amount of data and does not meet the assumption of a normal distribution is Structural Equation Modeling-Partial Least Square (SEM-PLS). Latent variables that have a significant effect on the happiness index in some spatial models are the happiness index lag and poverty. The indicator has the most influence on the latent variable of poverty is the poverty depth index, while the indicator has the most influence on the latent variable of the happiness index is the life satisfaction index.
Keyword: happiness index, SEM-PLS, spatial

Judul: Light Microscope Study of ConnectiveTissue in The Spleen of Common Rousette Bat (Rousettus amplexicaudatus)
Abstrak: The spleen is the largest lymphoid organ. As a secondary lymphoid organ, in addition to its immune function, the spleen also has functions as blood filtration, storage, and hematopoiesis. The spleen has different morphologies between species that support different physiological functions, one of which is the difference in the structure of the capsule and trabeculae. Capsule and trabeculae of the spleen generally consist of connective tissue and smooth muscle. The thickness of smooth muscle composed together with connective tissue in the capsule and trabecula determines the function of the spleen that is divided spleen into three storage, defense, and intermediate. Bats are the reservoir of various zoonotic diseases. Bats are thought to have unique immune systems compared to other mammals but the characteristics of its immune organs such as the spleen have never been studied before. This study was conducted to examine the characteristics of capsulae and trabecula of the Common Rousette (Rousettus amplexicaudatus).
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