scholarly journals PEMODELAN TINGKAT KERAWANAN DEMAM BERDARAH DI KABUPATEN BANJAR DENGAN METODE ANALISIS REGRESI LOGISTIK YANG TERBOBOTI GEOGRAFIS

2019 ◽  
Vol 14 (4) ◽  
pp. 2393
Author(s):  
Dewi Sri Susanti ◽  
Pamona Dwi Rahayu ◽  
Oni Soesanto
Keyword(s):  
Logistic Regression ◽  
Dengue Fever ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Rate Model ◽  
Independent Variables ◽  
Dependent Variables ◽  
Geographically Weighted Logistic Regression ◽  
The Relationship ◽  
Maximum Likelihood Estimation Method

Regression analysis is a metodh for investigating the relationship between the dependent variable (Y) and independent variables (X). Logistic regression is a regression model that used related to the qualitative Dependent variable. If the Logistic regression influenced by factors of the location of each point from observation where the data is collected, it will be a Geographically Weighted Logistic Regression (GWLR). In the case of insecurity rate model of dengue fever has two or more categories, so that this case can be resolved by GWLR. This research aims to clarify the procedure of testing the parameters GWLR model and form insecurity rate model of dengue fever with GWLR method in Banjar Regency. Dependent variable with catagoric is Insecurity rate of dengue fever ( ) and independent variables is the population density ( ), the distance from the capital of the subdistrict to capital of regency ( ), fogging per subdistrict ( ), the percentage of households living clean and healthy ( ), pesentase healthy homes ( ), the percentage of access to decent sanitation ( ). The results from this research are estimate parameters using Maximum Likelihood Estimation method and presented in the form of thematic map that shows not all dependent variables give influence on Insecurity rate dengue fever

scholarly journals Functional SAC model: With application to spatial econometrics

2021 ◽  
Vol 55 (1) ◽  
pp. 1-13
Author(s):  
Alassane Aw ◽  
Emmanuel N. Cabral
Keyword(s):  
Maximum Likelihood ◽  
Spatial Econometrics ◽  
Spatial Data ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Explanatory Variables ◽  
Dependent Variables ◽  
Spatial Autoregressive ◽  
The Relationship ◽  
Maximum Likelihood Estimation Method

Spatial autoregressive combined (SAC) models have been widely studied in the literature for the analysis of spatial data in various areas such as geography, economics, demography, regional sciences. This is a linear model with scalar response and scalar explanatory variables which allows for spatial interactions in the dependent variables and the disturbances. In this work we extend this modeling approach from scalar to functional covariate. The parameters of the model are estimated via the maximum likelihood estimation method. A simulation study is conducted to evaluate the performance of the proposed methodology. As an illustration, the model is used to establish the relationship between unemployment and illiteracy in Senegal.

scholarly journals Empirical Analysis in the Relationship Between the Consumption and Economic Growth Based on the Structural Equation Model

2016 ◽  
Vol 4 (5) ◽  
pp. 419-427
Author(s):  
Erxin Zhang ◽  
Wancai Yang
Keyword(s):  
Economic Growth ◽  
Structural Equation Model ◽  
Structural Equation ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Equation Model ◽  
Positive Effects ◽  
Structure Equation Model ◽  
The Relationship ◽  
Maximum Likelihood Estimation Method

AbstractThis paper constructs the relationship between consumption and economic growth by a structure equation model and uses the provincial panel data of 29 provinces (municipalities, autonomous regions) from 1992 to 2010 in China, using maximum likelihood estimation method to analyze empirically the relationship between the consumption and economic growth in China. The result shows that the path coefficients between consumptions and economic growth are all positive, that suggests the consumption has significant positive effects on the economic growth. Also in this paper, it gives a new try to use a structural equation model to research the relationship between consumption and economic growth.

ANALISA PENGARUH IKLIM ORGANISASI DAN KOMPETENSI TERHADAP KINERJA PEGAWAI PT HUTAMA KARYA

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Erik Wardhana, MM.
Keyword(s):  
Organizational Climate ◽  
Employee Performance ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Free Variable ◽  
Independent Variables ◽  
Dependent Variables ◽  
Correlational Approach ◽  
Survey Research Methods ◽  
The Relationship

This study entitled "Analysis of Effect of Climate Organization and Competence Againt Employee PT. Hutama Karya ". The purpose of this study was to obtain information on the relationship between the free variable that organizational climate (X1) and competence (X2) with the dependent variable is employee performance (Y), either partially or simultaneously, This study used survey research methods with the correlational approach and predictive, which aims for the relationship and influence between independent and dependent variables. The sampling technique can be done randomly (simple random sampling) of 852 employees, which is considered to resprentatif is 89 people. And to solve problems, to analyze and examine the relationship and influence between the independent variables on the dependent variable used models kausalistik through regression analysis with SPSS 14.0

scholarly journals A multi-group higher-order factor analysis for studying the gender-effect in Teacher Job Satisfaction

METRON ◽  
2021 ◽  
Author(s):  
Carlo Cavicchia ◽  
Pasquale Sarnacchiaro
Keyword(s):  
Job Satisfaction ◽  
Factor Analysis ◽  
Secondary School Teachers ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Higher Order ◽  
Teacher Job Satisfaction ◽  
Public Secondary School ◽  
Order Factor ◽  
Maximum Likelihood Estimation Method

AbstractTeachers’ performances also depend on whether and how they are satisfied with their job. Therefore, Teacher Job Satisfaction must be considered as the driver of teachers’ accomplishments. To plan future policies and improve the overall teaching process, it is crucial to understand which factors mostly contribute to Teacher Job Satisfaction. A Common Assessment Framework and Education questionnaire was administered to 163 Italian public secondary school teachers to collect data, and a second-order factor analysis was used to detect which factors impact on Teacher Job Satisfaction, and to what extent. This model-based approach guarantees to detect factors which respect important properties: unidimensionality and reliability. All the coefficients are estimated according to the maximum likelihood estimation method in order to make inference on the parameters and on the validity of the model. Moreover, a new multi-group test for higher-order factor analysis was proposed and implemented. Finally, we analyzed in detail whether the factors impacting Teacher Job Satisfaction are characterized by gender.

scholarly journals A Student’s Guide to the Classification and Operationalization of Variables in the Conceptualization and Design of a Clinical Study: Part 1

2021 ◽  
Vol 43 (2) ◽  
pp. 177-179 ◽  
Author(s):  
Chittaranjan Andrade
Keyword(s):  
Clinical Study ◽  
Significant Relationship ◽  
Research Experience ◽  
Process Variables ◽  
Know How ◽  
Independent Variables ◽  
Cause And Effect ◽  
Confounding Variables ◽  
Dependent Variables ◽  
The Relationship

Students without prior research experience may not know how to conceptualize and design a study. This article explains how an understanding of the classification and operationalization of variables is the key to the process. Variables describe aspects of the sample that is under study; they are so called because they vary in value from subject to subject in the sample. Variables may be independent or dependent. Independent variables influence the value of other variables; dependent variables are influenced in value by other variables. A hypothesis states an expected relationship between variables. A significant relationship between an independent and dependent variable does not prove cause and effect; the relationship may partly or wholly be explained by one or more confounding variables. Variables need to be operationalized; that is, defined in a way that permits their accurate measurement. These and other concepts are explained with the help of clinically relevant examples.

Large rotary dairies achieve high cow throughput but are not more labour efficient than medium-sized rotaries

2013 ◽  
Vol 53 (6) ◽  
pp. 573 ◽  
Author(s):  
J. P. Edwards ◽  
J. G. Jago ◽  
N. Lopez-Villalobos
Keyword(s):  
Milk Yield ◽  
Mixed Models ◽  
Telephone Survey ◽  
Independent Variables ◽  
Milk Flow ◽  
Efficiency Measures ◽  
Dependent Variables ◽  
A Site ◽  
The Relationship ◽  
Total Labour

It was hypothesised that large rotary dairies (>60 clusters) are not more operator efficient than medium-sized rotaries (40–60 clusters). This was tested by collecting and analysing milking data, during peak and late lactation, from block calving herds milked in rotary dairies fitted with electronic milk meters. Data were collected from a total of 61 unique farms around New Zealand, with rotary dairies ranging in size from 28 to 80 clusters, for two 5-day periods during spring (September–November 2010; 47 farms; average milk yield 23.1 kg/day) and autumn (February–April 2011; 60 farms; average milk yield 16.4 kg/day). A telephone survey was conducted to collect basic farm details: size, land area, the number of herds managed (including hospital herds), number of operators in the dairy and total labour input. A site visit was conducted to collect data such as the number of bails/stalls over the entrance and exit of the platform. The herd management software on each farm was programmed to record similar fields for each of the six machine manufacturers represented. Variables recorded included cow, date, identification time, bail number, milk yield, milking duration, and average milk flow rate. Calculations were performed to determine the number of cows milked and milk harvested per hour as well as the operator efficiency values for these measures and an estimate of cluster utilisation. Mixed models were used to determine the relationship between the dependent variables, cows milked per hour, milk harvested per hour, cows milked per operator per hour, milk harvested per operator per hour, and cluster utilisation, and the independent variables collected. Cows milked and milk harvested per hour increased linearly with rotary size, during both spring and autumn and there was a quadratic relationship between operator efficiency measures and rotary size, which peaked at ~60 clusters. Cluster utilisation, the amount of time clusters were harvesting milk out of the plant running time, was estimated at 46 ± 6%. Larger rotary dairies on average achieved greater throughput; however, they were not more operator efficient than medium-sized rotaries. Thus, large rotary dairies are best suited to farms where the additional throughput is required.

scholarly journals Pengaruh Kompensasi Finansial Terhadap Kinerja Karyawan Pada PT Penggadaian (Persero) Cabang Jambi

2020 ◽  
Vol 5 (2) ◽  
pp. 209
Author(s):  
Fadil Iskandar
Keyword(s):  
Statistical Tests ◽  
Financial Compensation ◽  
Independent Variables ◽  
Correlational Research ◽  
Dependent Variables ◽  
And Performance ◽  
Relationship Of ◽  
The Relationship ◽  
Descriptive Method ◽  
Variable Performance

This research aims to find out how implementation of the financial compensation and performance job of PT Penggadaian (Persero) Branch  of Jambi. Next also to analyze implamentation and how the influence of financial compensation on performance job in PT Penggadaian (Persero) of Banch Jambi. This research uses descriptive method quantitative correlational research with the form that describes the relationship of independent variables with dependent variables. The research on the analysis tools using simple regression with hypothesis prove with statistical tests t. The results showed that a significant effect on performance financial compensation of performance job which are characterized by tcount > ttable and Prog. sig < α (0.05). While the correlation value i.e. 64% of these mean that have relationship very closely between financial compensation variables with variable performance job.

scholarly journals PENGARUH REVIU RKA-K/L OLEH APIP TERHADAP EFISIENSI ALOKASI ANGGARAN KEMENTERIAN AGAMA

2019 ◽  
Vol 1 (1) ◽  
pp. 12
Author(s):  
Edy Effendi ◽  
Muhammad Imron
Keyword(s):  
Linear Regression ◽  
Simple Linear Regression ◽  
Independent Variables ◽  
Dependent Variables ◽  
Before And After ◽  
The Impact ◽  
The Relationship ◽  
Positive Effect

Research on the role of the APIP review of the Ministry/agency Work Plan and Budget document to determine the impact on the efficiency of ministry/agency spending (case study at the Ministry of Religion). The method used in this study uses simple linear regression with dummy. The use of linear regression is used to examine the relationship between independent variables (certain types of expenditure) and dependent variables (total expenditure). Whereas, dummy is used to find out before and after the APIP review is done. Throughout the author's search, this research has never been done. Based on the results of linear regression obtained, the APIP review significantly had a positive effect on official travel expenditure and honorarium but did not significantly affect building spending and equipment. Abstrak   Penelitian atas peran reviu APIP atas dokumen Rencana Kerja dan Anggaran Kementerian Negara/Lembaga untuk mengetahui dampaknya terhadap efisiensi belanja kementerian/lembaga (studi kasus pada Kementerian Agama). Metode yang digunakan dalam penelitian ini menggunakan regresi linier sederhana dengan dummy. Penggunaan regresi liner digunakan untuk meneliti hubungan antara variable independen (jenis belanja tertentu) dan variable dependen (total belanja). Sedangkan, dummy digunakan untuk mengetahui sebelum dan setelah reviu APIP dilakukan. Sepanjang penelusuran penulis, penelitian ini belum pernah dilakukan. Berdasarkan hasil regresi linier diperoleh, reviu APIP signifikan berpengaruh positif terhadap  belanja perjalanan dinas dan honorarium tetapi tidak signifikan berbengaruh terhadap belanja gedung dan alat.

scholarly journals KETERKAITAN PERTUMBUHAN PENJUALAN PERPUTARAN PERSEDIAAN, PERPUTARAN PIUTANG, DAN PERPUTARAN KAS TERHADAP PROFITABILITAS PERUSAHAAN LQ 45 DI BURSA EFEK INDONESIA

2021 ◽  
Vol 5 (2) ◽  
pp. 781
Author(s):  
Sugiyarmasto Sugiyarmasto ◽  
Erlina Setyaningrum
Keyword(s):  
Stock Exchange ◽  
Financial Statements ◽  
Sales Growth ◽  
Analysis Method ◽  
Independent Variables ◽  
Dependent Variables ◽  
Regression Test ◽  
Inventory Turnover ◽  
Relationship Of ◽  
The Relationship

The research aims to determine and provide empirical evidence of , sales growth inventory turnover, receivables Turnover, and significant cash turnover on profitability in LQ 45 Company on Indonesia Stock Exchange year 2016-2018. The samples in this study used purposive sampling so obtained 21 company samples from 45 LQ 45 company population listed on the Indonesia Stock Exchange, with 63 observations of financial statements (21 companies x 3 years of financial statements warning). Dependent variables in this study, namely profitability. While independent variables in this study, sales growth namely inventory turnover, turnover receivables, , cash turnover. The data analysis method used is a type of multiple regression test to test the relationship of independent variables with the dependents The results of the research hypothesis testing proved that the turnover of receivables, and cash turnover significantly positively affect profitability. And sales growth has a negative and significant effect on profitability. While inventory turnover has a negative and insignificant effect on profitability in LQ 45 company in the Indonesia Keywords: sales growth,inventory turnover, turnover receivable, cash turnover,profitability

scholarly journals Model Regresi Logistik Terboboti Georafis pada Status Kemiskinan Kabupaten/Kota di Provinsi Sulawesi Selatan tahun 2016

2019 ◽  
Vol 1 (3) ◽  
pp. 87
Author(s):  
Sadriana Rustan ◽  
Muhammad Arif Tiro ◽  
Muhammad Nadjib Bustan
Keyword(s):  
Logistic Regression ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Geographical Location ◽  
Predictor Variable ◽  
Likelihood Estimation ◽  
Local Form ◽  
South Sulawesi ◽  
Weighted Logistic Regression ◽  
Geographically Weighted Logistic Regression

Abstrak. Analisis regresi logistik digunakan untuk menentukan hubungan antara peubah respon bersifat kategori dengan satu atau lebih peubah penjelas dengan asumsi bahwa respon tidak dipengaruhi oleh lokasi geografis (data spasial). Salah satu metode analisis spasial adalah Model Regresi Logistik Terboboti Geografis (RLTG). Model RLTG adalah bentuk regresi logistik lokal di mana lokasi geografis diperhatikan dan diasumsikan memiliki distribusi Bernoulli. Pendugaan parameter model RLTG menggunakan metode Maximum Likelihood Estimation (MLE) dengan memberikan bobot yang berbeda pada lokasi yang berbeda. Data dalam penelitian ini diperoleh dari publikasi Badan Pusat Statistik, yaitu data dan Informasi Kemiskinan di Provinsi Sulawesi Selatan. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi status kemiskinan di Provinsi Sulawesi Selatan dengan menggunakan model regresi logistik terboboti geografis dengan fungsi pembobot Kernel bisquare. Hasil penelitian menunjukkan bahwa peubah penjelas yang mempengaruhi status kemiskinan di Provinsi Sulawesi Selatan adalah persentase penduduk tidak bekerja dan persentase rumah tangga pengguna jamban bersama.Abstract. Logistic regression a analysis is used to determine the relationship between categorical response variables with one or more predictor variable assuming that the response is not influenced by geographical location (spatial data). One method of spatial analysis is Geographically Weighted Logistic Regression (GWLR). The GWLR model is a local form of logistic regression where the geographical location is considered and assumed to have a Bernoulli distribution. Estimating parameters of the RLTG model uses the Maximum Likelihood Estimation (MLE) method by giving different weights to different locations. The data were obtained from BPS publications, namely Data and Information on Poverty in South Sulawesi Province. This study aims to determine the factors that influence poverty status in South Sulawesi Province using a geographically weighted logistic regression model with kernel bisquare weighting function. The results showed that the explanatory variables that influence the status of poverty in the province of South Sulawesi were the percentage of the population not working and the percentage of common household toilet users.Keywords: logistic regression, kernel bisquare, GWLR and poverty.

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