scholarly journals ANALISIS PENGARUH SOSIAL EKONOMI TERHADAP PENGELOLAAN SAMPAH DI SUMATERA BARAT (STUDI KASUS DAERAH PERKOTAAN)

2020 ◽  
Vol 2 (1) ◽  
pp. 107
Author(s):  
Nesyana Dewi ◽  
Melti Roza Adry
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Waste Management ◽  
Cross Section ◽  
Urban Areas ◽  
Secondary Data ◽  
Cross Section Data ◽  
Income Per Capita ◽  
Section Data ◽  
Per Capita

This study aims to determine the effect of education, income per capita, age and knowledge on waste management in urban areas West Sumatera. This study uses secondary data in the form of cross section data of urban West Sumatera. Data obtained from BPS- Susenas West Sumatera. This study uses logistic regression analysis. The result of this study indicate that (1) education has not significant effect on waste management in urban areas West Sumatera (2) income per capita has not significant effect on waste management  in urban areas West Sumatera (3) age has not significant effect on waste management in urban areas West Sumatera (4) knowledge has a significant effect on waste management in urban areas West Sumatera

scholarly journals Conventional and Current way of Interpretation and Cost Forecasting

2020 ◽  
Vol 1 (6) ◽  
pp. 30-33
Author(s):  
Shahin ripon Nazmul ◽  
Riyaaz Sanjoy
Keyword(s):  
Regression Analysis ◽  
Production Process ◽  
Cross Section ◽  
Series Data ◽  
Cross Section Data ◽  
Short Term ◽  
Section Data ◽  
Production Factors ◽  
Cost Forecasting

This study discuses Short-term cost interpretation, regression analysis with time-series data, long term cost interpretation, Regression analysis using cross-section data, cost forecasting and Changes in the productivity of production factors. Short-term cost interpretation lead to short-term decisions, the concept of incramental costs has a very important role which includes variable costs and changes in fixed costs.  Long term cost interpretation to analyze the production function of several different firms, long-run cost estimates can be used. Based on these conditions, the estimation of long-term costs uses cross-section data. Forecasting costs for various levels of output in the coming period requires an assessment of changes in the efficiency of the production process physically, plus changes in the prices of production factors used in the production process.

scholarly journals Brand Loyalty of Baby Diaper Products

2018 ◽  
Vol 21 (1) ◽  
pp. 79-88
Author(s):  
Sajeeb Kumar Shrestha
Keyword(s):  
Regression Analysis ◽  
Cross Section ◽  
Brand Loyalty ◽  
Brand Image ◽  
Descriptive Statistics ◽  
Brand Experience ◽  
Cross Section Data ◽  
Section Data ◽  
Factors Influencing ◽  
Quality Design

This study tries to measure the factors influencing brand loyalty of baby diapers in Kathmandu City. Primary cross section data were collected using structured questionnaires. 200 working mothers were chosen as sample of the study. Reliability analysis, descriptive statistics and regression analysis was done to filter the questions, to summarize the data and to test the hypotheses. This research confirmed convenience, product quality, design, brand experience and brand image factors are important factors for brand loyalty of baby diaper products. Price has no support for brand loyalty.

scholarly journals Pengaruh Perkembangan Bank Umum Syariah Terhadap Pertumbuhan Ekonomi Indonesia Periode 2010-2015

2017 ◽  
Vol 4 (12) ◽  
pp. 952
Author(s):  
Firmansyah Putra ◽  
Muhammad Nafik Hadi Ryandono
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Cross Section ◽  
Annual Report ◽  
Secondary Data ◽  
Islamic Banking ◽  
Islamic Banks ◽  
Cross Section Data ◽  
Production Index ◽  
Section Data

The study aims to examines the influence of Islamic banks on economic growth in Indonesia during the period 2010–2015. Secondary data that were used in this research were in the form of monthly time series and cross-section data during the year 2010–2015. The data were obtained based on monthly statistical banking report from Bank Indonesia (BI) andmonthly statistical reports of the Monthly Industrial Production Index in the Large and Medium scale from Central Bureau of Statistics (BPS) of Indonesia and also annual report from each islamic banks that conclude in this observation. Total assets, and total financing as variables that are representing the Islamic bank. GDP (Gross Domestic Product) is the variable that representing economic growth. By using Multiple Regression Analysis, the result shows that generally, Islamic banking affects economic growth in Indonesia.

scholarly journals Impact of Population Ageing on Unemployment and Entrepreneurial Activity: the Case of Slovenia

Organizacija ◽  
2015 ◽  
Vol 48 (4) ◽  
pp. 232-245 ◽  
Author(s):  
Marjetka Troha Akanni ◽  
Žiga Čepar
Keyword(s):  
Regression Analysis ◽  
Unemployment Rate ◽  
Secondary Data ◽  
Population Ageing ◽  
Lower Number ◽  
Entrepreneurial Activity ◽  
Economic Welfare ◽  
Cross Section Data ◽  
Ceteris Paribus ◽  
Section Data

Abstract Purpose: The purpose of the research is to investigate impact of population ageing on unemployment and entrepreneurial activity in Slovenia since it is one of the topical issues in an ageing Europe and has many implications for economic and non-economic welfare. Design and Methodology: First, we introduce the phenomenon of population ageing and provide some literature review on population ageing impact on unemployment and entrepreneurial activity. Second, we employ multiple regression analysis on cross-section data for Slovenian municipalities. We use secondary data collected from databases of Statistical Office of Republic of Slovenia and Employment Service of Slovenia on demographic and economic variables by 210 municipalities for the year 2009. Results: The regression analysis results confirm our first hypothesis: municipalities with higher ageing index and higher average age also have higher registered unemployment rate. If ageing index (average age) is higher by 1 %, the registered unemployment rate is higher on average by 0.532 % to 0.670 % (by 2.431 % to 3.379 %), ceteris paribus. Our regression analysis also confirms our second hypothesis: municipalities with higher average age also have lower number of enterprises per 100 population. If average age is higher by 1% (by 1 year), the number of enterprises per 100 population is lower on average by 1.7 % (by 0.182 enterprises), ceteris paribus. Conclusion: We may conclude that population ageing without properly addressing it, consequently leads into lower economic welfare. That additionally highlights the importance of a proper demographic and social policy when governing labour market policy.

scholarly journals Analisis Konsekuensi Ekonomi Akibat Kejahatan di Indonesia

2020 ◽  
Vol 20 (2) ◽  
pp. 146-159
Author(s):  
Tarina Palokoto ◽  
Evi Yulia Purwanti ◽  
Y. Bagio Mudakir
Keyword(s):  
Cross Section ◽  
Government Expenditure ◽  
Domestic Investment ◽  
Cross Section Data ◽  
Spatial Lag ◽  
Section Data ◽  
Spatial Lag Model ◽  
Spatial Dependencies ◽  
Lag Model ◽  
Per Capita

Crime affects people’s decisions in carrying out economic activity. This study aims to analyze the influence of several crime typologies and non-crime variables on per capita Gross Regional Domestic Product (GRDP) and identify the existence of spatial dependencies of per capita GRDP in Indonesia. The study used cross section data with the Spatial Lag Model (SLM). The results show that there is a negative spatial autocorrelation in per capita GRDP. Murder and labor affect GRDP per capita negatively. Meanwhile, fraud, embezzlement, and corruption; local government expenditure, life expectancy, domestic investment, and foreign investment affect per capita GRDP positively per capita GRDP. ------------------------------------- Kejahatan memengaruhi keputusan masyarakat melakukan kegiatan ekonomi. Penelitian ini bertujuan menganalisis pengaruh dari beberapa tipologi kejahatan dan variabel nonkejahatan terhadap Produk Domestik Regional Bruto (PDRB) per kapita serta mengidentifikasi adanya dependensi spasial dari PDRB per kapita di Indonesia. Penelitian ini menggunakan data cross section dengan Spatial Lag Model (SLM). Hasil penelitian menunjukkan terdapat autokorelasi spasial negatif pada PDRB per kapita. Kejahatan pembunuhan dan tenaga kerja memengaruhi PDRB per kapita secara negatif dan signifikan. Sementara itu, variabel kejahatan penipuan/perbuatan curang, penggelapan, dan korupsi; pengeluaran pemerintah daerah, angka harapan hidup, Penanaman Modal Dalam Negeri (PMDN), serta Penanaman Modal Asing (PMA) berpengaruh positif dan signifikan terhadap PDRB per kapita.

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 PENGARUH FAKTOR SOSIAL EKONOMI TERHADAP PERILAKU MASYARAKAT DALAM PENGELOLAAN SAMPAH PERDESAAN DI PROVINSI SUMATERA BARAT

2020 ◽  
Vol 2 (1) ◽  
pp. 93
Author(s):  
Ayu Rahmadani Utama ◽  
Dewi Zaini Putri
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Waste Management ◽  
Solid Waste ◽  
Employment Status ◽  
Solid Waste Management ◽  
Secondary Data ◽  
Rural Solid Waste ◽  
West Sumatra ◽  
Household Members

This study aims to determine and analyze the influence of age (X1), gender (X2), education (X3), income (X4), employment status (X5), number of household members (X6), and knowledge (X7) towards rural waste management opportunities in West Sumatra Province. This type of research is descriptive and associative research while the type of data is secondary data. The data used is the 2017 SUSENAS data with documentation data collection techniques from the Central Statistics Agency. Analysis of the data used is logistic regression analysis with all respondents totaling 5,996 people. The results showed: (1) Age was not significant to the opportunities for rural solid waste management in West Sumatra Province. (2) Gender is significant for rural waste management opportunities in West Sumatra Province. (3) Significant education towards rural waste management opportunities in West Sumatra Province. (4) Income is not significant to the opportunities for rural waste management in West Sumatra Province. (5) Significant employment status of opportunities for rural solid waste management in West Sumatra Province. (6) The number of household members is not significant to the opportunities for rural waste management in West Sumatra Province. (7) Insignificant knowledge of opportunities for rural solid waste management in West Sumatra Province.

Modeling Sovereign Rating of India

2021 ◽  
pp. 391-414
Author(s):  
Rituparna Das ◽  
Gargi Guha Niyogi
Keyword(s):  
Principal Component Analysis ◽  
Logistic Regression ◽  
Cross Section ◽  
Direct Investment ◽  
Internal Model ◽  
Principal Component ◽  
Cross Section Data ◽  
Institutional Variables ◽  
Section Data ◽  
Investment Grade

Against the background that India has been continuously receiving for over a decade till now the same investment grade of sovereign rating, the authors research what the important indicators of sovereign rating are and how to predict the probability that the ratio of foreign direct investment to gross domestic product of a country will be above average. They reviewed existing works and detected certain gaps. In the course of plugging those gaps, the authors collected cross section data available on economic, financial, and institutional variables of the emerging economies of ASEAN and SAARC members. They applied principal component analysis to distill relatively more effective variables determining sovereign rating, and then they applied logistic regression to these variables in order to compute the above probability. The methodology has proved successful in reproducing the past and useful as an internal model of assessing relative sovereign riskiness of an emerging economy among its peers. The work prescribed some policy to improve the aforesaid ratio of India.

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