ABSTRAKTujuan penelitian ini menganalisis tentang aliran modal asing ke Indonesia dengan pull dan push factors. Determinan yang digunakan pada Pull dan Push factors adalah GDP Domestik. GDP Global, Suku bunga domestic, suku bunga internasional dan resiko politik negara. Penelitian menggunakan pendekatan kuantitatif dengan menggunakan data time series dengan rentang waktu 20 tahun pasca krisis moneter di Indonesia (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017). Analisis data menggunakan persamaan regresi linear berganda. Hasil penelitian menemukan bahwa ternyata faktor yang dominan mempengaruhi aliran modal asing adalah pull factors baik jenis portofolio investment dan foreign direct investment. Variabel yang paling dominan mempengaruhi aliran modal asing di Indonesia yaitu variabel risiko politik domestik. Risiko politik domestik erat kaitannya dengan iklim investasi. Disisi lain pengaruh aliran modal asing signifikan dan positif dalam menjelaskan pertumbuhan ekonomi di Indonesia. ABSTRACTThe purpose of this study is to analyze the flow of foreign capital into Indonesia with pull and push factors. Determinants used on Pull and Push factors are Domestic GDP. Global GDP, domestic interest rates, international interest rates and the country's political risks. The study uses a quantitative approach using time series data with a span of 20 years after the monetary crisis in Indonesia (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017). Data analysis using multiple linear regression equations. The results of the study found that it turned out that the dominant factors influencing foreign capital flows were pull factors both the type of portfolio investment and foreign direct investment. The most dominant variable affecting the flow of foreign capital in Indonesia is the domestic political risk variable. Domestic political risk is closely related to the investment climate. On the other hand the influence of foreign capital flows is significant and positive in explaining economic growth in Indonesia.

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The purpose of this study is to analyze the factors of natural resources, income per capita, infrastructure, education, institutions and population against inequality between regions and welfare in Indonesia. The study uses panel data regression analysis analyzing secondary data consisting of 33 provincial cross section data and 10 years time series data (2008-2017). The results of the study found inequality between regions in Indonesia with different intensities. Factors of natural resources, income per capita, infrastructure, education, wealth and population have a positive and significant effect on inequality between regions. Furthermore, 2% of the inequality variables between regions affect the level of welfare and the rest are influenced by natural resources, per capita income, infrastructure, education, institutions and population.

This research is an applied research using qualitative approach.Data collection used in-depth interview technique was used to gather information from fisherman in Jeneponto, Bulukumba, Pangkep and Barru districts. Besides conducting in-depth interviews, documentation of data is also done through library and secondary data through related institutions in 4 sample research areas. The result of the research shows that the majority of the fishermen who live in the coastal áreas are willing to work hard, have a rather low level of self discipline, independence and responsibility. Further, fishermen cooperative institution is seemed as needed to help fishermen for access of capital and marketing their seabased products.

Penelitian ini bertujuan untuk mengetahui model Markowitz pada saham Indeks LQ45, sehingga diperoleh komposisi saham yang dapat dijadikan pilihan investasi atau membentuk portofolio. Populasi penelitian ini adalah seluruh saham-saham emiten atau perusahaan go public yang pernah masuk dalam Indeks LQ45 di Bursa Efek Indonesia periode Februari 2017-Januari 2021 sebanyak 66 saham perusahaan dan sampel penelitian ini adalah 65 saham perusahaan yang dipilih berdasarkan teknik nonprobability sampling dengan metode purposive sampling. Pengumpulan data penelitian menggunakan teknik dokumentasi. Analisis data dilakukan model Markowitz dengan mengumpulkan data harga saham penutupan (closing price) bulanan sampai mendapatkan portofolio optimal kemudian mengukur kinerja portofolio optimal dari model Markowitz. Berdasarkan hasil penelitian terdapat 11 saham pembentuk portofolio optimal model Markowitz dengan expected return portofolio sebesar 0,96% per bulan dengan risiko portofolio (varianportofolio sebesar 0,12% per bulan dan standar deviasi sebesar 3,41% per bulan).