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

ANALISIS PENDAPATAN ASLI DAERAH DAN FAKTOR-FAKTOR YANG MEMPENGARUHINYA PADA KABUPATEN/KOTA DI PROVINSI SUMATERA BARAT

2019 ◽  
Vol 4 (3) ◽  
pp. 536
Author(s):  
Olvi Verdian Abdillah ◽  
Hefrizal Handra ◽  
Adrimas Adrimas
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Central Government ◽  
Time Series Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Series Data ◽  
Section Data ◽  
Effect Model ◽  
West Sumatra

<p class="MsoNormal" style="margin-bottom: .0001pt; text-indent: 0cm;"><em><span style="font-family: 'Times New Roman','serif'; letter-spacing: 0pt;" lang="EN-US">This study aims to analyze the factors that affect of the Local Own-Source Revenue (OSR) in West Sumatra. As for the data used is the data panel, which is the combination of time series data for 2010-2017 and cross-section data in 19 regencies/city in West Sumatra. Based on the the regression test using the Fixed Effect Model (FEM) obtained results that all of the three independent variables are significantly affect to OSR. On the other hand, based on the partial test, obtained that only dummy variables which representing the policy of transfer authority to managing of rural and urban land and buildings taxes (PBB-P2) from the central government to the local government does not significantly affect the OSR, while the two other variables per-capita GDRP and the number of electric customers partially significantly affect PAD.</span></em></p><p class="MsoNormal" style="margin-bottom: .0001pt; text-indent: 0cm;"><em><span style="font-family: 'Times New Roman','serif'; letter-spacing: 0pt;" lang="EN-US"><br /></span></em></p><p class="MsoNormal" style="margin-bottom: .0001pt; text-indent: 0cm;"><span style="font-family: 'Times New Roman','serif'; letter-spacing: 0pt;" lang="EN-US">Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi Pendapatan Asli Daerah (PAD) di Sumatera Barat. Adapun data yang digunakan merupakan data panel, yaitu kombinasi data time series tahun 2010-2017 dan data cross-section pada 19 Kabupaten/Kota di Sumatera Barat. Berdasarkan hasil uji regresi menggunakan Fixed Effect Model (FEM) diperoleh hasil bahwa secara bersama-sama ketiga variabel bebas signifikan mempengaruhi PAD.Sementara pada uji parsial diperoleh hasil bahwa hanya variabel dummy yang mewakili kebijakan transfer kewenangan pengelolaan Pajak Bumi Bangunan Pedesaan dan Perkotaan (PBB-P2) dari pusat ke daerah tidak signifikan mempengaruhi PAD, sementara dua variabel bebas lainnya yaitu PDRB Perkapita dan jumlah pelanggan listrik secara parsial signifikan mempengaruhi PAD.</span></p><p class="MsoNormal" style="margin-bottom: .0001pt; text-align: center; text-indent: 0cm;" align="center"><strong><em><span style="font-family: 'Times New Roman','serif'; letter-spacing: 0pt; mso-ansi-language: IN;" lang="IN">ABSTR</span></em></strong><strong><em><span style="font-family: 'Times New Roman','serif'; letter-spacing: 0pt;" lang="EN-US">ACT</span></em></strong><strong></strong></p><em><span style="font-size: 11pt; font-family: 'Times New Roman', serif; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-attachment: initial; background-origin: initial; background-clip: initial;" lang="EN-US">This study aims to analyze the factors that affect of the Local Own-Source Revenue (OSR) in West Sumatra. As for the data used is the data panel, which is the combination of time series data for 2010-2017 and cross-section data in 19 regencies/city in West Sumatra. Based on the the regression test using the Fixed Effect Model (FEM) obtained results that all of the three independent variables are significantly affect to OSR. On the other hand, based on the partial test, obtained that only dummy variables which representing the policy of transfer authority to managing of rural and urban land and buildings taxes (PBB-P2) from the central government to the local government does not significantly affect the OSR, while the two other variables per-capita GDRP and the number of electric customers partially significantly affect PAD.</span></em>

scholarly journals Estimation Model And Selection Method Of Panel Data Regression : An Overview Of Common Effect, Fixed Effect, And Random Effect Model

2018 ◽  
Author(s):  
rizka zulfikar
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Cross Section ◽  
Fuzzy Time Series ◽  
Series Data ◽  
Unbiased Estimation ◽  
Cross Section Data ◽  
Section Data ◽  
Panel Data Regression ◽  
Data Regression

The estimation in the regression analysis with cross section data is done by estimating the least squares method called Ordinary Least Square (OLS). Regression Method Data Panel will give the result of estimation which is Best Linear Unbiased Estimation (BLUE). Data Panel Regression is a combination of cross section data and time series, where the same unit cross section is measured at different times. So in other words, panel data is data from some of the same individuals observed in a certain period of time. If we have T time periods (t = 1,2, ..., T) and N the number of individuals (i = 1,2, ..., N), then with panel data we will have total observation units of N x T. If sum unit time is the same for each individual, then the data is called balanced panel. If instead, the number of time units is different for each individual, then it is called the unbalanced panel. While other data types, namely:time-series data and cross-section. In time series, one or more variables will be observed on one observation unit within a certain time frame. While data cross-section is the observation of several units of observation in a single point of time.Unlike the usual regression, panel data regression must go through the precise estimation modeling step.SEE ALSO :Zulfikar, R., &amp; Mayvita, P. A. (2017). THE EFFECTS OF POLITICAL EVENTS AGAINST ABNORMAL RETURN AND TOTAL VOLUME SHARIA SHARES ACTIVITY THAT LISTED IN JAKARTA ISLAMIC INDEX (JII). JEMA: Jurnal Ilmiah Bidang Akuntansi dan Manajemen, 14(02), 64-74.Zulfikar, R., &amp; AdeMayvita, P. (2017). Pengujian Metode Fuzzy Time Series Chen dan Hsu Untuk Meramalkan Nilai Indeks Bursa Saham Syariah Di Jakarta Islamic Index (JII). Wiga: Jurnal Penelitian Ilmu Ekonomi, 7(2), 108-124.

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 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 Determinant of Car Demand in Java Island

2019 ◽  
Vol 8 (1) ◽  
pp. 1-8
Author(s):  
Dyah Candra Kirana ◽  
Prasetyo Ari Bowo
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Cross Section ◽  
Time Series Data ◽  
Panel Data Analysis ◽  
Least Square ◽  
Series Data ◽  
Cross Section Data ◽  
Section Data ◽  
Per Capita

The purpose of this research is to examine factors that affect car demand in Java Island in 2012-2016. The research method used in this research is panel least square The data used in this research is panel data. The panel data consists of time series data (2012-2106) and cross section data (six province in Java Island, those are DKI Jakarta, Jawa Barat, Jawa Tengah, DI Yogyakarta, Jawa Timur, and Banten). Data were obtained from Central Bureau of Statistic Republic of Indonesia (BPS). Data analysis used is panel data analysis. The results showed that income per capita, population, and inflation have simultan effect on car demand in Java Island in 2012-2016. Per capita income has a positive and significant effect on car demand in Java Island in 2012-2016. Population has a positive and significant effect on car demand in Java Island in 2012-2016. Inflation has positive and insignificant effect on car demand in Java Island in 2012-2016.

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 Determinan Pengangguran Terdidik Lulusan Universitas di Pulau Jawa

2021 ◽  
Vol 10 (3) ◽  
pp. 178-187
Author(s):  
Leni Anjarwati ◽  
Whinarko Juliprijanto
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Cross Section ◽  
Quantitative Methods ◽  
Negative Impact ◽  
Positive Impact ◽  
Panel Data Analysis ◽  
Series Data ◽  
Cross Section Data ◽  
Section Data

This study aims to determine the factors that influence educated unemployment in Java. The data used in this study is secondary data using quantitative methods. Data analysis uses panel data analysis which is a combination of time series and cross-section data. The time-series data uses data for the 2015-2019 period and cross-section data from 6 provinces on the island of Java. The results showed that simultaneously all variables had a significant effect on the level of educated unemployment. While partially shows that the variable level of education and PMDN have a significant positive impact on educated unemployment, and the UMR variable has a significant negative impact on educated unemployment.

scholarly journals MODEL REGRESI DATA PANEL UNTUK MENGETAHUI FAKTOR YANG MEMPENGARUHI TINGKAT KEMISKINAN DI PULAU MADURA

2020 ◽  
Vol 9 (3) ◽  
pp. 355-363
Author(s):  
Artanti Indrasetianingsih ◽  
Tutik Khalimatul Wasik
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Series Data ◽  
Poverty Level ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Poverty arises when a person or group of people is unable to meet the level of economic prosperity which is considered a minimum requirement of a certain standard of living or poverty is understood as a state of lack of money and goods to ensure survival. Panel data regression is the development of regression analysis which is a combination of time series data and cross section data. Panel data regression is usually used to make observations of data that is examined continuously for several periods. The purpose of this study is to determine the factors that influence the level of poverty in Madura Island in the period 2008 - 2017. In this study the variables used in this study are life expectancy (X1), average length of school (X2), level open unemployment (X3), and labor force participation (X4) with the Comman Effect Model (CEM) approach, Fixed Effect Model and Random Effect Model (REM). To choose the best model from the three is the chow test, the hausman test and the breusch-pagan test. In this study, the best model chosen was the Fixed Effect Model. Keywords: CEM, Fixed Effect Model, Data Panel Regression, REM, Poverty level.

scholarly journals Pengaruh Rasio Keuangan Terhadap Financial Distress Pada Perusahaan Sektor Industri Dasar Dan Kimia Yang Terdaftar Di Bursa Efek Indonesia

2020 ◽  
Vol 5 (1) ◽  
pp. 11-28
Author(s):  
Andi Runis Makkulau
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Financial Distress ◽  
Time Series Data ◽  
Series Data ◽  
Sales Growth ◽  
Cross Section Data ◽  
Current Ratio ◽  
Section Data ◽  
Equity Ratio

Penelitian ini bertujuan untuk mengetahui dan menganalisis pengaruh Current Ratio, Cash Ratio, Debt To Equity Ratio dan Sales Growth terhadap Financial Distress pada Perusahaan Sektor Industri Dasar dan Kimia yang Terdaftar di Bursa Efek Indonesia. Populasi dalam penelitian ini adalah perusahaan sektor industri dasar dan kimia yang terdaftar di Bursa Efek Indonesia. Berdasarkan metode purposive sampling, sampel yang diperoleh yaitu sebanyak 10 perusahaan. Penelitian ini menggunakan data kuantitatif dan bersumber dari jenis data sekunder yaitu data panel yang merupakan data gabungan dari data runtut waktu (time series data) dan data silang (cross section data).           Hasil penelitian ini menunjukkan bahwa Current Ratio, Cash Ratio, Debt to Equity Ratio dan Sales Growth berpengaruh negatif tetapi tidak signifikan terhadap Financial Distress. Hal ini berarti bahwa Current Ratio, Cash Ratio, Debt to Equity Ratio dan Sales Growth tidak dapat menjelaskan Financial Distress.   Kata Kunci : Current Ratio, Cash Ratio, Debt To Equity Ratio, Sales Growth, Financial Distress  

scholarly journals Pengaruh PDRB, Upah Minimum Provinsi, dan Angkatan Kerja Terhadap Investasi Asing Langsung di Indonesia Tahun 2013-2016

2019 ◽  
Vol 4 (2) ◽  
pp. 101-109
Author(s):  
Siti Utma ◽  
◽  
Arif Rakhman
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Fixed Effects ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Fixed Effects Model ◽  
Common Effect ◽  
Effect Model

Penelitian ini bertujuan menganalisis pengaruh produk domestik regional bruto (PDRB), upah minimum provinsi (UMP), dan angkatan kerja terhadap investasi asing langsung di Indonesia tahun 2013 – 2016. Data yang digunakan dalam penelitian ini adalah data panel yang merupakan gabungan data provinsi sebagai cross section dan tahun 2013 – 2016 sebagai time series. Investasi asing langsung merupakan variabel dependen, sedangkan variabel Independen yang digunakan adalah produk domestik regional bruto (PDRB), upah minimum provinsi (UMP), dan angkatan kerja. Metode penelitian menggunakan analisis regresi dengan tiga model yaitu common effect model, fixed effect model, dan random effect model. Dari tiga model tersebut, fixed Effects Model (FEM) terpilih sebagai model regresi data panel yang paling tepat. Hasil regresi produk domestik regional bruto (PDRB) berpengaruh positif signifikan terhadap investasi asing langsung. Hal ini berarti setiap kenaikan produk domestik regional bruto (PDRB) akan menaikkan investasi asing langsung di Indonesia. Adapun variabel upah minimum provinsi (UMP) dan Angkatan Kerja, tidak berpengaruh signifikan terhadap investasi asing langsung di Indonesia tahun 2013 – 2016.

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