scholarly journals PENGARUH TINGKAT PUTUS SEKOLAH, KEMISKINAN DAN PENGANGGURAN TERHADAP KRIMINALITAS DI INDONESIA

2018 ◽  
Vol 7 (2) ◽  
pp. 147
Author(s):  
Maulidya Rahmi ◽  
Melti Roza Adry
Keyword(s):  
Elementary School ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Drop Out ◽  
Research Use ◽  
Estimation Result ◽  
Effect Model ◽  
School Drop Out ◽  
The Law

This research aims to know and analyze determine drop out, poverty, and unemployment to criminality in Indonesia. This research use panel least square and Fixed effect model. The estimation result should that elementary school drop out has a positive and significant effect on criminality in Indonesia, poverty doesn’t h ave effect to criminality in Indonesia, unemployment doesn’t have effect to criminality in Indonesia. From the result of this research, goverment and the police should be do some sosialization at school and also give sosialization in front of citizen. The sosialization is about the law of criminality and increasing parents educations and anticipate negativity on environment.

Determinants of Foreign Direct Investment in ASEAN

2008 ◽  
Vol 43 (3) ◽  
pp. 21-51 ◽  
Author(s):  
P.R. Bhatt
Keyword(s):  
National Income ◽  
Least Square Method ◽  
Fixed Effect Model ◽  
Positive Influence ◽  
Fixed Effect ◽  
Least Square ◽  
Negative Sign ◽  
Significant Variable ◽  
Fdi Inflows ◽  
Effect Model

The ASEAN region has become one of the most attractive investment locations in the developing world. It attracted FDI to the tune of US$19 billion in 2003. Among ASEAN countries, Singapore topped the list with US$11 billion FDI inflows followed by Malaysia (US$2.5 bn), Brunei (US$.0 bn), and Vietnam (USɁ5 bn) in 2003. An attempt has been made in this paper to understand the determinants of FDI in ASEAN. The empirical model is estimated for five countries of ASEAN and ASEAN region as a whole for the period 1976-2003. The estimation of the model shows that there is a positive influence of the size of the economy (GNI) on FDI inflows in the case of Indonesia and Singapore. The infrastructure is significant for Indonesia and Malaysia in attracting FDI. Exchange rate had influence on FDI for Malaysia. The openness of the economy was significant in attracting FDI for Indonesia. The model is estimated for panel data of ASEAN region by pooled least square method and fixed effect model. In the case of pooled least square method, gross national income (GNI) is very significant and having expected sign. This implies that market size attracted FDI in the ASEAN region. The depreciation of the currency attracted FDI inflows in ASEAN as indicated by the variable XR which is significant with negative sign. Infrastructure is another significant variable in this model. Openness variable is significant but negative sign. When the model was estimated by fixed effect model it is found that all variables are significant with expected sign except in the case of the variable openness.

scholarly journals Analisis Regresi Panel pada Pemodelan Tingkat Kematian Bayi di Provinsi Sulawesi Selatan

2020 ◽  
Vol 2 (2) ◽  
pp. 115
Author(s):  
Syafruddin Side ◽  
S. Sukarna ◽  
Raihana Nurfitrah
Keyword(s):  
Panel Data ◽  
Infant Mortality ◽  
Regression Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Dummy Variable ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Penelitian ini membahas mengenai estimasi parameter model regresi data panel pada pemodelan tingkat kematian bayi di Provinsi Sulawesi Selatan dari tahun 2014 sampai dengan 2015. Data yang digunakan adalah data sekunder dari Dinas Kesehatan Provinsi Sulawesi Selatan yang berupa jumlah kematian bayi, berat bayi lahir rendah, persalinan yang ditolong oleh tenaga kesehatan, penduduk miskin, bayi yang diberi ASI ekslusif dan rumah tangga berperilaku bersih sehat di seluruh Kabupaten/Kota di Provinsi Sulawesi Selatan tahun 2014-2016. Analisis data dilakukan dengan menggunakan penghitungan manual dan dengan menggunakan software EViews 9. Pembahasan dimulai dari melakukan estimasi parameter model regresi data panel, menentukan model regresi data panel terbaik, , menguji asumsi model regresi data panel, pengujian signifikansi parameter dan interpretasi model regresi. Dalam penelitian ini diperoleh kesimpulan yaitu estimasi model regresi data panel terbaik dengan pendekatan fixed effect model.Kata kunci:Regresi Data Panel, Kematian Bayi, Fixed Effect Model, Least Square Dummy Variable. This research discusses about parameter estimation of panel data regression model of infant mortality level modelling in South Sulawesi from 2014 to 2015. The data used were secondary data from Dinas Kesehatan Provinsi Sulawesi Selatan in the form of number of infant mortality, low weight of infant, childbirth rescued by health workers, poor population, infants who were given exclusive breast milk and household that behaves well in the whole district/town in South Sulawesi year 2014-2016. Data analysis was performed using the calculation manually and by using EViews 9 software. The discussion started from doing parameter estimation of panel data regression model, determining the best panel data regression model, testing the assumption of panel data regression model, testing the signification of parameter and interpretation of regression model. Conclusion of this research are the estimation of regression model is the best panel data regression model with fixed effects model approach.Keywords:Panel Data Regression, Infant Mortality, Fixed Effect Model, Least Square Dummy Variable.

scholarly journals Banks Efficiency and the Determinants of Non-Performing Financing of Full-Fledged Islamic Banks in Indonesia

2017 ◽  
Author(s):  
chandra setiawan
Keyword(s):  
Data Envelopment Analysis ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Var Model ◽  
Data Envelopment ◽  
Islamic Banks ◽  
Temporal Relationships ◽  
Effect Model ◽  
The Mean

This paper investigates the efficiency of Indonesian Full-fledged Islamic Banks by employing Data Envelopment Analysis (DEA) approach; the determinants of Non-Performing Financing (NPF) during the period 2012(Q1) to 2016 (Q2) by using Panel Least Square for fixed effect model; the inter-temporal relationships between banks efficiency and NPF are run using VAR model to test the two hypotheses: Bad Debts and Bad Management. The finding of DEA indicates the mean score on Full-fledged Islamic Banks in Indonesia is approach to efficient with the score 96.54% and Bank Rakyat Indonesia Syariah (BRIS) is the most technical efficient. The result shows that Full-fledged Islamic Banks in Indonesia is not support the bad management and Bad Luck hypothesis, probably NPF of full-fledged is average 4.5% that is still below of the critical standard of Bank Indonesia.

scholarly journals APLIKASI REGRESI DATA PANEL DENGAN PENDEKATAN FIXED EFFECT MODEL (STUDI KASUS: PT PLN GIANYAR)

2014 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
NI PUTU ANIK MAS RATNASARI ◽  
I PUTU EKA NILA KENCANA ◽  
G.K. GANDHIADI
Keyword(s):  
Panel Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Dummy Variable ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Panel data regression has three approaches. One of these approaches is Fixed Effect Model (FEM). FEM is common estimated using Least Square Dummy Variable. The use of dummy variable in FEM is based on assumption that slope coefficients are constant but intercept varies over individuals. One of application of FEM is to find out motivation of employees at PT PLN Gianyar for non-outsourcing and outsourcing employees based on existence, relatedness, and growth. This research yields the following two models:with 67% motivation non-outsourcing employees represented by existenceand73% motivation non-outsourcing employees represented by existence and growth.

scholarly journals Determinan Kemiskinan di Provinsi Jawa Tengah Tahun 2011-2014

2018 ◽  
Vol 7 (3) ◽  
pp. 235-242
Author(s):  
Emi Megawati ◽  
Lesta Karolina Br Sebayang
Keyword(s):  
Significant Influence ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Simultaneous Test ◽  
Central Java ◽  
Effect Model ◽  
Independent Variable ◽  
Central Java Province

Berdasarkan data dari BPS, kemiskinan di Provinsi Jawa Tengah pada tahun 2011-2014 masih berada di peringkat kedua setelah DI Yogyakarta di Pulau Jawa-Bali. Penelitian ini menggunakan data panel dengan pendekatan Fixed Effect Model (FEM) dengan metode Generalized Least Square (GLS). Sumber data yang diperoleh dari Badan Pusat Statistik (BPS) dan Direktorat Jendral Perimbangan Keuangan Indonesia. Hasil penelitian menunjukan bahwa variabel IPM berpengaruh negatif dan signifikan terhadap kemiskinan di Provinsi Jawa Tengah. Sedangkan variabel PDRB dan pembiayaan pendidikan berpengaruh tidak signifikan terhadap kemiskinan di Provinsi Jawa Tengah. Hasil uji secara bersama-sama menunjukan bahwa secara keseluruhan variabel bebas secara bersama-sama dapat menunjukan pengaruhnya terhadap kemiskinan. nilai dari Adjusted R2 sebesar 0,995 yang berarti 99,5 persen kemiskinan dapat dijelaskan oleh variabel bebas. Sedangkan sisanya 0,50 persen dijelaskan oleh variabel di luar model. Based on data from BPS, during years 2011-2014 Central Java Province are in number 2 after DI Yogyakarta in Java-Bali. This research use panel data with Fixed Effect Model (FEM) approach and by using Geberalized Square (GLS) method. The data source is secondary data are obtained from the Central Statistics Agency and the Directorate General of Financial Balance Indonesia. The result of this research show that HDI variable give the negative and significant influence to the poverty in Central Java province. GDRP and financing of education not significant influence to the poverty in Central Java province. Simultaneous test results showed that, overall, the independent variable (HDI, GDRP and financing of education) together can show its effect on poverty. the value of Adjusted R2 of 0,995, which means 99,5 percent of poverty can be explained by the independent variable. While the remaining 0,50 percent is explained by variables outside the model.

scholarly journals The Determinants of Sukuk Issuance: Evidence from Top Sukuk Issuing Countries

2021 ◽  
Vol 16 (1) ◽  
pp. 21-34
Author(s):  
Mohamad Nizam Jaafar ◽  
◽  
Amirul Afif Muhamat ◽  
Norzita Abdul Karim ◽  
Mohd Faizal Basri ◽  
...  
Keyword(s):  
Panel Data ◽  
Random Effect Model ◽  
Political Stability ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Macroeconomic Variables ◽  
Brunei Darussalam ◽  
Effect Model ◽  
Control Of Corruption

Macroeconomic variables may influence the issuance of Sukuk. The purpose of this study was to determine the relationship between macroeconomic variables namely Gross Domestic Product (GDP) per capita, inflation, rules of law, corruption of control and political stability. This study used a panel data study consisting of 11 countries that were mostly involved in the issuance of Sukuk. The countries are Bahrain, Brunei Darussalam, Indonesia, Kuwait, Malaysia, Pakistan, Qatar, Saudi Arabia, Singapore, Turkey and United Arab Emirates. The data was generated from 2006 until 2015 and collected from the authorized sources such as the Islamic Finance Information Services (IFIS), World Development Indicator and World Economic Outlook. This research employed several statistical methods like descriptive statistics, unit root test, and correlation analysis. In order to meet the objective of this research, an econometrics estimation of Pool Ordinary least square model, Fixed Effect Model and Random Effect Model were tested. The output from the Fixed Effect Model indicates that only GDP and control of corruption have a significant relationship to Sukuk issuance. It can be concluded that when the GDP increases, the number of Sukuk issued will increase accordingly. This is also applicable to corruption where better control of corruption will lead to an increase in Sukuk issuance. Therefore, good policies should in place to ensure a conducive economic environment that will encourage participation in the Sukuk market. Keywords: Sukuk, Islamic capital market, macroeconomic, panel data, least square model

scholarly journals IMPACT OF INVESTMENT, LABOR, AND INFRASTRUCTURE ON JAVA ISLAND ECONOMIC GROWTH 2011-2017

2018 ◽  
Vol 1 (3) ◽  
pp. 230-241
Author(s):  
Maya Aprilia Sari
Keyword(s):  
Economic Growth ◽  
Local Governments ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Clean Water ◽  
Domestic Investment ◽  
Central Java ◽  
Effect Model

The study aims to determine and analyze the effect of investment, labor, and infrastructure on economic growth in Java in 2011-2017. This research is a quantitative study using secondary data from six provinces in Java (DKI Jakarta, West Java, Central Java, Special Region of Yogyakarta, East Java and Banten) obtained from the Central Statistics Agency. Analysis of the data used in this study is panel regression of fixed effect model data using the General Least Square (GLS) method. The results showed that individually the domestic investment variable, labor, clean water infrastructure had a significant influence on economic growth while foreign investment had no significant effect on economic growth. Suggestions: 1) local governments are expected to increase the potential of each region to attract investors; 2) local governments are expected to create a conducive investment climate and facilitate investment licensing; 3) local governments are expected to increase the allocation of education funds and provide training in foreign languages ​​and skills to the workforce; 4) local governments should make better plans for the distribution of clean water and improve the efficiency of the use of clean water.© 2019, Universitas Negeri Semarang Penelitian bertujuan untuk mengetahui dan menganalisis pengaruh investasi,tenaga kerja, dan infrastruktur terhadap pertumbuhan ekonomi di Pulau Jawa tahun 2011-2017. Penelitian ini merupakan penelitian kuantitatif menggunakan data sekunder enam provinsi di Pulau Jawa (DKI Jakarta, Jawa Barat, Jawa Tengah, Daerah Istimewa Yogyakarta, Jawa Timur, dan Banten) yang diperoleh dari Badan Pusat Statistik.Analisis data yang digunakan pada penelitian ini adalah regresi data panel model fixed effect menggunakan metode General Least Square (GLS). Hasil penelitian menunjukkan bahwa secara individu variabel penanaman modal dalam negeri, tenaga kerja, infrastruktur air bersih memiliki pengaruh signifikanterhadap pertumbuhan ekonomi sedangkanpenanaman modal luar negeri tidak berpengaruh signifikan terhadap pertumbuhan ekonomi. Saran: 1) pemerintah daerah diharapkan meningkatkan potensi setiap daerah agar menarik para investor; 2) pemerintah daerah diharapkan menciptakan iklim investasi yang kondusif dan mempermudah perizinan investasi; 3) pemerintah daerah diharapkan meningkatkan alokasi dana pendidikan dan memberikan pelatihan bahasa asing dan ketrampilan kepada tenaga kerja; 4) pemerintah daerah hendaknya membuat perencanaan distribusi air bersih yang lebih baik lagi dan meningkatkan efisiensi penggunaan air bersih.

scholarly journals PENGARUH UPAH MINIMUM PROVINSI, PENDIDIKAN DAN KESEHATAN TERHADAP KEMISKINAN DI INDONESIA

2019 ◽  
Vol 1 (3) ◽  
pp. 939
Author(s):  
Nadia Islami ◽  
Ali Anis
Keyword(s):  
Panel Data ◽  
Minimum Wage ◽  
Research Method ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Ordinary Least Square ◽  
Education And Health ◽  
Effect Model ◽  
Library Studies

This research aims to examined the impactt of provincial minimum wage, education and health on poverty in Indonesia with the selected model is the Fixed Effect Model (FEM). The data used is panel data during the period 2012-2017, with the technique of collecting documentation data and library studies obtained from relevant institutions and agencies.The variables use are poverty, provincial minimum wage, education and health. The research method used is Ordinary Least Square (OLS). The estimation results show that, provincial minimum wage have a positive and significant effect on poverty in Indonesia. Education have a negative and significant effect on poverty in Indonesia. Health have a negative and its not significant effect on poverty in Indoneisa. Meanwhile simultaneously province minimum wage, education and health affect the poverty in Indonesia.

scholarly journals ANALISIS REGRESI UNTUK DATA PANEL PADA PEMODELAN TINGKAT KEMATIAN IBU DI PROVINSI SULAWESI SELATAN

2020 ◽  
Vol 2 (1) ◽  
pp. 20
Author(s):  
Muhammad Imran Rahman ◽  
Muhammad Nusrang ◽  
S. Sudarmin
Keyword(s):  
Parameter Estimation ◽  
Panel Data ◽  
Regression Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
South Sulawesi ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Abstrak. Penelitian ini membahas mengenai estimasi parameter model regresi data panel pada pemodelan tingkat kematian ibu di Provinsi Sulawesi Selatan dari tahun 2014 sampai dengan 2016. Data yang digunakan adalah data sekunder dari Dinas Kesehatan Provinsi Sulawesi Selatan yang berupa jumlah kematian ibu, perdarahan, hipertensi dalam kehamilan, infeksi dan gangguan sistem peredaran darah di seluruh Kabupaten/Kota di Provinsi Sulawesi Selatan tahun 2014-2016. Pembahasan dimulai dari melakukan estimasi parameter model regresi data panel, menentukan model regresi data panel terbaik, menguji asumsi model regresi data panel, pengujian signifikansi parameter dan interpretasi model regresi. Dalam penelitian ini diperoleh kesimpulan yaitu estimasi model regresi data panel terbaik dengan pendekatan fixed effect model dengan nilai 𝑅2 = 90%. Adapun peubahpeubah yang berpengaruh signifikan terhadap kematian ibu adalah perdarahan, hipertensi dalam kehamilan dan infeksi. Dari hasil analisis diperoleh juga daerah yang memiliki jumlah kematian ibu terbesar di Provinsi Sulawesi Selatan tahun 2014-2016 adalah Bone dan Jeneponto.Kata Kunci: Regresi data Panel, Angka Kematian Ibu, Fixed Effect Model, Least Square Dummy Variable.Abstract. This research discusses about parameter estimation of panel data regression model of mother mortality level modelling in South Sulawesi from 2014 to 2016. The data used were secondary data from Dinas Kesehatan Provinsi Sulawesi Selatan in the form of number of mother mortality, bleeding, infection, circulatory system disorders and metabolic disorders in the whole district/town in South Sulawesi year 2014-2016. The discussion started from doing parameter estimation of panel data regression model, determining the best panel data regression model, testing the assumption of panel data regression model, testing the signification of parameter and interpretation of regression model. Conclusion of this research are the estimation of regression model is the best panel data regression model with fixed effects model approach with value of 𝑅2 = 90%. The variables that significantly influence maternal mortality are bleeding, hypertension in pregnancy and infection. From the results of the analysis, it was also found that the regions that had the largest number of maternal deaths in South Sulawesi Province in 2014-2016 were Bone and Jeneponto.Keywords: Panel Data Regression, Mother Mortality Rate, Fixed Effect Model, Least Square Dummy Variable.

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