scholarly journals ANALISIS DETERMINAN BALITA PENDEK DAN SANGAT PENDEK DI INDONESIA 2015-2018 DENGAN REGRESI DATA PANEL

2020 ◽  
Vol 8 (2) ◽  
pp. 56-61
Author(s):  
Astrid C. A. Pangaribuan ◽  
Kuncoro Dwi Dhanutama ◽  
Miko Oktavio Wijaya ◽  
Putri Tareka Navasha ◽  
Rani Nooraeni
Keyword(s):  
Panel Data ◽  
Cross Section ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Individual Effect ◽  
Capita Expenditure ◽  
School Participation ◽  
Effect Model ◽  
Per Capita

Balita pendek dan sangat pendek (kerdil) adalah kondisi dimana balita memiliki panjang atau tinggi badan yang kurang dibandingkan dengan umur. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi persentase balita kerdil di Indonesia pada tahun 2015–2018. Penelitian ini menggunakan data sekunder berupa data panel yang bersumber dari website Badan Pusat Statistik dan publikasi Kementerian Kesehatan Republik Indonesia. Variabel bebas dalam penelitian ini adalah angka partisipasi sekolah, rata-rata pengeluaran per kapita rumah tangga untuk makanan, tingkat pengangguran terbuka, dan persentase balita gizi buruk dan kurang.  Metode analisis yang digunakan adalah regresi data panel dengan Fixed Effect Model (FEM). Setelah dilakukan estimasi model terpilih, didapatkan hasil bahwa rata-rata pengeluaran per kapita rumah tangga untuk makanan dan persentase balita gizi buruk kurang berpengaruh signifikan. Sementara itu, berdasarkan hasil Individual Effect atau Cross-Section Fixed Effect, persentase balita kerdil tertinggi berada di Provinsi Sulawesi Barat sedangkan yang terendah berada di Provinsi Kepulauan Riau. Kata kunci: Pengeluaran perkapita, partisipasi sekolah, tingkat pengangguran terbuka, balita gizi buruk  Abstract Toddler short and very short (dwarf) is a condition where toddlers have a length or height less than age. This study aims to analyze the factors that influence the percentage of stunted toddlers in Indonesia in 2015-2018. This study uses secondary data in the form of panel data sourced from the website of the Central Statistics Agency and the publication of the Ministry of Health of the Republic of Indonesia. The independent variables in this study are school participation rates, the average per capita household expenditure for food, open unemployment rates, and the percentage of malnourished and under-aged children. The analytical method used is panel data regression with the Fixed Effect Model (FEM). After estimating the selected model, the results show that the average per capita expenditure of households for food and the percentage of malnourished children under five is not significantly influential. Meanwhile, based on the results of the Individual Effect or Cross-Section Fixed Effect, the highest percentage of dwarf children was in West Sulawesi Province while the lowest was in Riau Islands Province. Keywords: Per capita expenditure, school participation, open unemployment rate, malnutrition toddlers 

scholarly journals ANALISIS REGRESI DATA PANEL TERHADAP INDEKS PEMBANGUNAN MANUSIA (IPM) JAWA TIMUR TAHUN 2006-2015

2018 ◽  
Vol 18 (2) ◽  
pp. 69
Author(s):  
Muhammad Jamil Hidayat ◽  
Alfian Futuhul Hadi ◽  
Dian Anggraeni
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Cross Section ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Series Data ◽  
Cross Section Data ◽  
Section Data ◽  
Effect Model ◽  
Per Capita

Panel data is a combination of time series and cross section data. Panel data regression is used because in a time there is time researchers can’t perform analysis only by using time series data and cross section data only. This is because the number of factors used in the analysis phase, so that if the researcher only uses cross section data then the researcher can’t see the influence of factors that affect as well as on the growth of HDI that occurs from time to time in a certain period. Whereas it is quite possible that the conditions between one year and another will be different. Based on the model estimation, it is used with fixed effect model (FEM) approach. Modeling HDI with FEM in 2006-2015 period resulted in R2 value of 94.23%. The results showed that from 2006-2015 the ratio of student-teacher (RST), health facilities (HF), percentage of expenditure per capita by group of food (PPF) and regional per capita expenditure (PPE) have significant effect to HDI. Keywords: HDI, Panel, Fixed Effect Model

scholarly journals Analisis Regresi Balanced Panel dengan Komponen Galat Dua Arah pada Kasus Melek Huruf Masyarakat di Provinsi NTB

2021 ◽  
Vol 3 (1) ◽  
pp. 10
Author(s):  
Muhammad Irwansyah ◽  
R. Ruliana ◽  
Muhammad Kasim Aidid
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Cross Section ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Common Effect ◽  
Effect Model

Abstract. Analsis regresi adalah suatu metode untuk melihat pengaruh antara satu atau lebih peubah bebas terhadap peubah terikat. Data yang digunakan untuk analisis regresi ada yang berupa penggabungan antara data cross section dengan data time series yang dikenal dengan nama data panel. Data panel yang memiliki jumlah pengamatan waktu yang sama di setiap objek pada tabulasi silang merupakan data panel lengkap (Balanced panel). Penelitian ini mencari nilai dugaan terhadap model regresi data panel dengan komponen galat dua arah yaitu galat pada waktu dan galat pada individu. Analisis regresi data panel dapat menggunakan tiga pendekatan yaitu common effect model, fixed effect model, dan random effect model. Pemilihan model terbaik dari ketiga pendekatan regresi data panel menggunakan uji hausman, uji chow, dan uji lagrange multipler. Dalam penelitian ini didapatkan model terbaik yaitu model random effect dimana peubah yang memiliki pengaruh signifikan terhadap melek huruf di Provinsi NTB yaitu rasio murid guru tingkat SMP rasio murid guru tingkat SMA, dan persentase penduduk miskin. Model regresi data panel yang terbentuk yaitu: Y = 117,5728 - 0,1967X5 - 0,3091X6 - 0,3297X7 + eKeywords: regresi data panel, common effect model, fixed effect model, random effect model, melek huruf.

scholarly journals PENGARUH TINGKAT PENDIDIKAN, PENGANGGURAN , DAN KEMISKIAN TERHADAP KRIMINALITAS DI INDONESIA

2019 ◽  
Vol 1 (1) ◽  
pp. 21
Author(s):  
Suci Rahmalia ◽  
Ariusni Ariusni ◽  
Mike Triani
Keyword(s):  
Panel Data ◽  
Significant Influence ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Equation Model ◽  
Fixed Effect ◽  
Regression Equation ◽  
Panel Regression ◽  
Level Of Education ◽  
Effect Model

This study aims to determine and analyze the influence of (1) Level of Education, (2) Unemployment, and (3) Poverty against crime in Indonesia by using the panel regression equation model and using the Fixed Effect Model (FEM) approach. The estimation results show that (1) the level of education has a negative and not significant effect on criminality in Indonesia, (2) unemployment has a negative and significant effect on crime in Indonesia, (3) poverty has a positive and significant influence on crime in Indonesia.This type of research is descriptive and associative. Data type is secondary data. This study uses panel data, which uses 31 provinces in Indonesia using the Fixed Effect Model (FEM) approach.The results of this study indicate that: (1) The level of education has a negative and insignificant influence on crime in Indonesia, (2) Unemployment has a negative and significant effect on crime in Indonesia, (3) Poverty has a positive and significant influence on crime in Indonesia.

scholarly journals ANALISIS INSTRUMEN KEBIJAKAN FISKAL TERHADAP PERTUMBUHAN EKONOMI DI 35 KABUPATEN / KOTA PROVINSI JAWA TENGAH TAHUN 2013 – 2017

2019 ◽  
Vol 17 (1) ◽  
pp. 1-8
Author(s):  
Fitri Bahari ◽  
Nugroho SBM
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Cross Section ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Effect Model

Penelitian ini bertujuan untuk menganalisis pengaruh pajak, belanja pegawai, belanja barang dan jasa, belanja tidak langsung terhadap pertumbuhan ekonomi di 35 Kabupaten/ Kota Provinsi Jawa Tengah pada tahun 2013-2017, sebagai akibat pengambilan kebijakan fiskal. Data yang digunakan dalam penelitian ini adalah data panel (data time series selama lima tahun dari 2013-2017, dan data cross-section sebanyak 35 data yang mewakili Kabupaten/ Kota Di Provinsi Jawa Tengah). Metode analisis penelitian ini mengunakan regresi data panel fixed effect model. Analisis regresi data panel digunakan untuk mengetahui pengaruh variabel-variabel independen terhadap pertumbuhan ekonomi. Hasil estimasi dalam penelitian ini menunjukan bahwa variabel belanja tidak langsung berpengaruh positif dan signifikan terhadap pertumbuhan ekonomi, variabel pajak, belanja pegawai berpengaruh negatif dan signifikan terhadap pertumbuhan, sedangkan variabel belanja barang dan jasa tidak berpengaruh terhadap pertumbuhan ekonomi. Dapat disimpulkan bahwa variabel belanja lagsung, pajak, dan belanja pegawai memiliki pengaruh terhadap pertumbuhan ekonomi sebagai dampak pengambilan kebijakan fiskal. Namun variabel belanja barang dan jasa tidak memiliki pengaruh terhadap pertumbuhan ekonomi di Kabupaten/ Kota Provinsi Jawa Tengah. Berdasarkan hasil penelitian diperlukan efektifitas alokasi anggaran belanja maupun penerimaan pemerintah, agar lebih dapat merespon kebijakan fiskal regional yang diambil pemerintah.

scholarly journals Determinants of Structural Transformation in ASEAN

2020 ◽  
Vol 35 (2) ◽  
pp. 137
Author(s):  
Kalies Sirieh Puspitowati ◽  
Deden Dinar Iskandar
Keyword(s):  
Panel Data ◽  
Structural Transformation ◽  
Value Added ◽  
Fixed Effect Model ◽  
Dependency Ratio ◽  
Service Value ◽  
Income Per Capita ◽  
Effect Model ◽  
Per Capita ◽  
Asean Countries

This study aims to analyze the determinants of the structural transformation in ASEAN countries. This study uses quantitative panel data from 9 countries in ASEAN from 2000 to 2017, thus makes up for 162 observations. This study employs panel data regression analysis with fixed effect model approach. In this study, the shifting of sectoral value added away from agriculture sectors indicates structural transformation. In particular, sectoral value added consists of the industrial value added and service value added. The results of this study shows that dependency ratio, income per capita, education, and trade significantly affect the increase of industrial value added during observation period. On the other hand, total population, dependency ratio, income per capita, education, control of corruption, and trade significantly increase the service value added over time.

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 Determinants of Financial Performance of Nepalese Commercial Banks: Evidence from Panel Data Approach

2020 ◽  
Vol 32 (2) ◽  
pp. 45-59
Author(s):  
Purna Man Shrestha
Keyword(s):  
Panel Data ◽  
Financial Performance ◽  
Commercial Banks ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Lagrangian Multiplier ◽  
Effect Model ◽  
Specific Factors ◽  
The Impact ◽  
Bank Specific Factors

The impact of bank specific factors on the financial performance of Nepalese commercial banks is analyzed in this paper. The financial performance is measured by using return on assets (ROA). Similarly, managerial efficiency (ME), liquidity (LIQ), credit risk (CR), assets quality (AQ) and operational efficiency (OE) is used as proxy of bank specific factors. This study used panel data of 17 commercial banks for the period of 2010/11 to 2017/18. Breusch and Pagan Lagrangian multiplier test showed that Pooled Regression model is not appropriate and Hausman test concluded that Fixed Effect model is appropriate rather than Random Effect model. Using the Fixed Effect model; this study concludes that bank specific factors have significant impact on financial performance of Nepalese commercial banks. Finally, this study reveals that ME, AQ and OE have significant positive impact, and CR has negative impact on the financial performance of Nepalese commercial banks.  

scholarly journals Pengaruh Konsumsi Energi dan Deforestasi Terhadap Output Nasional Lima Negara Anggota ASEAN

2021 ◽  
Vol 10 (2) ◽  
pp. 105-112
Author(s):  
Neni Kristiana ◽  
Lorentino Togar Laut ◽  
Jalu Aji Prakoso
Keyword(s):  
Panel Data ◽  
Co2 Emissions ◽  
Negative Impact ◽  
National Income ◽  
Electricity Consumption ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Coal Consumption ◽  
Effect Model ◽  
National Output

The economic development aimed at improving people’s welfare often ignores the negative impact of the surrounding environment. The high use of energy aimed to increase the national income of the five ASEAN members hurts the environment by increasing CO2 levels in the air.  This research aims to analyze the effect of CO2 emissions, coal consumption, electricity consumption and deforestation on national output in five ASEAN members. The variable used in this research is national output as the dependent variable and CO2 emissions, coal consumption, electricity consumption and deforestation as the independent variables. This research uses secondary data. The data is the panel data of five ASEAN members (Indonesia, Malaysia, Thailand, Philippines, Myanmar) from 2002 until 2018.  The research method in this time is panel data regression, using Fixed Effect Model. This research shows that in five ASEAN members from 2002 until 2018, CO2 emissions harm national output, coal consumption, and electricity consumption positively affects national outcome, while deforestation does not affect national output.

scholarly journals Pengaruh Perkembangan Usaha Mikro, Kecil, dan Menengah Terhadap Pendapatan Nasional Pada Sektor UMKM di Indonesia

2019 ◽  
Vol 8 (2) ◽  
pp. 127-135
Author(s):  
Lies Maria Hamza ◽  
Devi Agustien
Keyword(s):  
Panel Data ◽  
Small And Medium Enterprises ◽  
National Income ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Effect Model ◽  
Medium Enterprises

This study aims to analyze the influence of the development of Micro, Small, and Medium Enterprises on the national income of the UMKM sector in Indonesia. This research used a panel data method with Fixed Effect Model. The data used are secondary in the value of GDP of UMKM, Labours of UMKM, investment of UMKM, and the number of units of UMKM from the 2000-2013 period. The results showed that labors of UMKM and placement of UMKM have a positive and significant effect on the national income of the UMKM sector in Indonesia. While for the number of units of UMKM not affect the national income of the UMKM sector in Indonesia.

Dana pihak ketiga, Inflasi dan Pembiayaan Mudharabah terhadap Non Performing Financing pada Bank Islam di Indonesia dan Malaysia

2019 ◽  
Vol 16 (2) ◽  
pp. 74-80
Author(s):  
Afrillia Tiara Putri ◽  
Saadah Yuliana ◽  
Anna Yulianita
Keyword(s):  
Panel Data ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Third Party ◽  
Coefficient Of Determination ◽  
Islamic Banks ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Negative Effect

This study aimed to analyze the influence of third party funds, inflation, and mudharabah against non performing financing on Islamic Banks in Indonesia and Malaysia. Data used is secondary data. The method used in this analysis is the panel data regression. The results showed that in partial third party fund and mudharabah significant negative effect on the Non Performing Financing, while inflation is positive and not significant to the Non Performing Financing. Variable Third Party Funds, Inflation and mudharabah jointly significant effect on Non Performing Financing. Based on the regression equation fixed effect model results show the results of the coefficient of determination (R2) is 0.369198, or 36.91 per cent means that the variation of the variable third party funds, inflation and mudharabah have an influence on the non performing financing for the coefficient of determination, while the rest 63.09 percent influenced by variables outside the model

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