scholarly journals Apakah Empati Mempengaruhi Kepatuhan Pajak?

Owner ◽  
2022 ◽  
Vol 6 (1) ◽  
pp. 507-517
Author(s):  
Joko Sustiyo ◽  
Danang Desta Yudha
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Regression Model ◽  
Tax Compliance ◽  
Binary Logistic Regression ◽  
Wald Test ◽  
Empathic Concern ◽  
Binary Logistic Regression Analysis ◽  
Significance Level ◽  
Lemeshow Test

Research on the impact of empathy as a non-economic factor on taxpayer compliance has not been studied in Indonesia. Most research still focuses on economic factors that affect tax compliance. To find out whether empathy affects tax compliance, this study uses binary logistic regression analysis because the dependent variable is nominal and categorical. The significance of the regression equation parameters was tested by the Ratio Likelihood Test and the Wald Test. Then, the goodness of fit model was tested using the Hosmer-Lemeshow Test. The likelihood ratio test shows that there is at least one coefficient from the regression model that has an effect on the 5% significance level. Based on the Wald test, there is no independent variable that has a significant effect on tax compliance with a 5% significance level. The Hosmer-Lemeshow test states that the binary logistic regression model in this study is feasible to use. Binary logistic regression analysis shows that only one predictor has a significant effect on the tax compliance variable, namely empathic concern items. The odds ratio value of 1.054 on the empathic concern items variable shows that taxpayers who have empathy will be 1.054 times more tax compliant than respondents who do not have empathy. In other words, respondents who have empathy will tend to be more obedient in paying taxes than those who do not have this trait. Therefore, the government can formulate regulations that support the emergence of empathic concern items in the community so that tax compliance increases.

scholarly journals Relevansi Informasi Laporan Keuangan Accrual Basis: Kemampuan Rasio Keuangan Dalam Memprediksi Status Financial Distress Pemerintah Daerah Kabupaten Dan Kota Se- Indonesia Periode 2015-2017

2019 ◽  
Vol 1 (2) ◽  
pp. 795-813
Author(s):  
Waninda Waninda ◽  
Fefri Indra Arza
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Financial Distress ◽  
Binary Logistic Regression ◽  
City Government ◽  
Performance Ratio ◽  
Binary Logistic Regression Analysis ◽  
Regional Government ◽  
Significance Level

This study aims to predict the financial distress status of district and city governments in Indonesia. Research examines the relevance of financial statement information consisting of profitability ratio, liquidity ratio, performance ratio and capital stress ratio in predicting district and city government financial distress in Indonesia in 2015-2017. This study uses agency theory. The sampling method in this study used purposive sampling. This study consisted of 134 samples of districts / cities in Indonesia, the financial data used in the study were audited regional government financial reports, namely reports on audit results for 2015-2017. The type of data used is secondary data. The analysis used is binary logistic regression analysis. Based on the results of binary logistic regression analysis with a significance level of 5%, that of the four types of ratios measured using fourteen measurements obtained results (1) Profitability ratio as measured by profit margin ratio affects financial distress with an β coefficient of 51,548 and a significance value of 0,000 < 0.05, (2) The performance ratio measured by operating revenue to total revenue has an effect on financial distress with an β coefficient of -41.180 and a significance value of 0.015> 0.05, and a depreciation ratio influences financial distress with an β coefficient of 40.004 and a value significance of 0.004 <0.05

scholarly journals LOGISTIC REGRESSION ON THE PRIMIPARAL AGE OF WOMEN IN GOMBE, GOMBE STATE

2020 ◽  
Vol 5 (7) ◽  
pp. 7-16
Author(s):  
A.U. Kinafa ◽  
M.B. Mohammed ◽  
A. Abdulkadir
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Regression Model ◽  
Logistic Regression Analysis ◽  
Logistic Regression Model ◽  
Healthcare Providers ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Challenging Problem ◽  
First Child

Failure of women to undergo a successful first child delivery is becoming one of the most challenging problem and a major concern to most of our healthcare providers. In this paper, we apply the binary logistic regression analysis to investigate whether age of women at first birth have a relationship with the outcome of their delivery (Success or failure). The data was collected from Gombe Town Maternity and was subjected to analysis. From the result of the analysis, we observed that most of the women at tender age (12-17) are classified to fail (69%) during their first child delivery while most of the women at higher age (19 and above) have a better chance of succeeding during their first parturition. Also, the result shows that the average age at which women ought to conceive successfully is 19 years. The Wald statistics result also shows that the logistic regression model fits the data very well.

scholarly journals Binary Logistic Regression Analysis on Predicting Academics Performance

2021 ◽  
pp. 1-6
Author(s):  
E. K. Akinyem ◽  
O. A. Ogunleye ◽  
H.O Olaoye ◽  
J. Brakoru
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Educational Level ◽  
Logistic Regression Model ◽  
Social Scientist ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Binary Logistic Regression Model ◽  
Future Performance ◽  
Lemeshow Test

This paper considers the application of logistic regression model to predict academics performance of students. The choice of this model becomes imperative as a result of dichotomous relationship existing in the model (either pass or fail). 100 students from the four department where engaged in the study. Statistical package for social scientist (SPSS) was used for the analysis. The results show that monthly allowance of students, and study time of the students were significant predictors. While gender and educational level of parent were insignificant predictors. The fitness of the model was assessed using Hosmer and Lemeshow test, split-sample approach and other supplementary indices to validate the model. The fitted model indicated that fitted binary logistic regression model could be used to predict the future performance of students.

scholarly journals Changes in Fish Consumer Behavior during the COVID-19 Pandemic in Bandung City

2021 ◽  
pp. 19-36
Author(s):  
Nabila Nur Rania ◽  
Zuzy Anna ◽  
Achmad Rizal ◽  
Asep Agus Handaka Suryana
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Qualitative Data ◽  
Binary Logistic Regression ◽  
Sampling Technique ◽  
Wald Test ◽  
Binary Logistic Regression Analysis ◽  
Fresh Fish ◽  
Before And After

This research was conducted in Cicendo District, Bandung City, West Java. To analyze factors that influence changes in fish consumers behaviour and preference before the COVID-19 pandemic. Case study with quantitative and qualitative data analysis was employed and an accidental sampling technique method using 100 respondents. The results showed changes in factors during the COVID-19 pandemic are the system and place of purchase, the frequency of fish consumption, the amount of consumption of fish and products consumed, and the price of fish. Based on binary logistic regression analysis, before and after the Covid-19 pandemic, the Wald test showed that income, education and age variables had an influence on preferences between fresh fish and processed fish. Preferences between fresh freshwater fish and marine fish before and after the COVID-19 pandemic, the Wald test shows that employment and income variables have an influence.

ANALISIS DAMPAK VOLUNTARY AND FORCED COMPLIANCE TERHADAP TINGKAT KEPATUHAN PAJAK UMKM DI KOTA SEMARANG

2018 ◽  
Vol 1 (2) ◽  
pp. 28
Author(s):  
Khikmah Rizqi Awaliyah ◽  
Evi Yulia Purwanti
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Tax Evasion ◽  
Tax Compliance ◽  
Secondary Data ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Tax Revenue ◽  
Binary Logistic Regression Analysis ◽  
Compliance Problem

The increasing ratio and realization of MSMEs tax revenue in Semarang City is not matched with the level of tax compliance where the realization of tax revenue in Semarang City every year is always under 100% of the target set.This shows the low level of MSMEs tax compliance problem in Semarang City. This study aims to analyze the effect of tax knowledge, justice perspective, perceptions of tax evasion opportunities, and perceptions of tax sanctions on the level of tax compliance of MSMEs in Semarang City. The type of data used in this study is the primary data obtained from 101 samples of MSMEs in Semarang City as well as the secondary data obtained from several related agencies as the supporting data. Data analysis was conducted by using binary logistic regression analysis. The results of study showed that tax knowledge and perception of justice variables significantly influence MSMEs tax compliance in Semarang City. Most of the actors of MSMEs (>50% of respondents) have a high taxknowledge, especially in tax-aware indicators about the obligation to have NPWP for MSME which has a turnover of not more than 4.8 billion but have a low perception of justice where only 1 of 5 indicators that have the number of respondents >50% of indicators of perception of justice about the assumption that tax regulations are set for the benefit of all parties not only for the sake of one party, the rest of the respondents feel that the MSMEs tax is still not fair. Meanwhile, the perception variables of tax evasion opportunities and perception of tax sanctions have no significant effect to MSMEs tax compliance in Semarang City.

scholarly journals Predicting Burn Mortality Using a Simple Novel Prediction Model

2021 ◽  
Author(s):  
Sneha Sharma ◽  
Raman Tandon
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Prediction Model ◽  
Receiver Operating Characteristic ◽  
Logistic Regression Analysis ◽  
Operating Characteristic ◽  
Binary Logistic Regression ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Binary Logistic Regression Analysis

Abstract Background Prediction of outcome for burn patients allows appropriate allocation of resources and prognostication. There is a paucity of simple to use burn-specific mortality prediction models which consider both endogenous and exogenous factors. Our objective was to create such a model. Methods A prospective observational study was performed on consecutive eligible consenting burns patients. Demographic data, total burn surface area (TBSA), results of complete blood count, kidney function test, and arterial blood gas analysis were collected. The quantitative variables were compared using the unpaired student t-test/nonparametric Mann Whitney U-test. Qualitative variables were compared using the ⊠2-test/Fischer exact test. Binary logistic regression analysis was done and a logit score was derived and simplified. The discrimination of these models was tested using the receiver operating characteristic curve; calibration was checked using the Hosmer—Lemeshow goodness of fit statistic, and the probability of death calculated. Validation was done using the bootstrapping technique in 5,000 samples. A p-value of <0.05 was considered significant. Results On univariate analysis TBSA (p <0.001) and Acute Physiology and Chronic Health Evaluation II (APACHE II) score (p = 0.004) were found to be independent predictors of mortality. TBSA (odds ratio [OR] 1.094, 95% confidence interval [CI] 1.037–1.155, p = 0.001) and APACHE II (OR 1.166, 95% CI 1.034–1.313, p = 0.012) retained significance on binary logistic regression analysis. The prediction model devised performed well (area under the receiver operating characteristic 0.778, 95% CI 0.681–0.875). Conclusion The prediction of mortality can be done accurately at the bedside using TBSA and APACHE II score.

scholarly journals Predicting organizational performance from motivation in Oromia Seed Enterprise Bale branch

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Askalech Feyisa Jobira ◽  
Abdulnasir Abdulmelike Mohammed
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Intrinsic Motivation ◽  
Organizational Performance ◽  
Logistic Regression Analysis ◽  
Extrinsic Motivation ◽  
Binary Logistic Regression ◽  
Moderate Level ◽  
Binary Logistic Regression Analysis ◽  
Study Results

AbstractMotivation is one of the most researched yet crucial topics in academia from various perspectives. Despite this, researches show mixed results about the effect of extrinsic motivation on intrinsic motivation and organizational performance. Studies in Ethiopia also lack causal analysis and theoretical underpinning that made contributions from academia very little. Hence, this research is important to assess the effect of extrinsic motivation on intrinsic motivation and organizational performance from a cognitive evaluation theory perspective. The researchers adopted an explanatory research design with a quantitative approach. The entire 119 employees of the Oromia Seed Enterprise, Bale branch were included in the study to collect primary data through a close-ended questionnaire. The collected data was processed by SPSS software version 20. The relationship analysis was addressed by correlation and binary logistic regression analysis. Seen from extrinsic and intrinsic motivation aspects, the findings of the study showed that Oromia Seed Enterprise had a moderate level of organizational performance and a moderate level of employees’ motivation. The correlation analysis result indicated that employees’ extrinsic and intrinsic motivation had a positive relationship with organizational performance. The binary logistic regression analysis also indicated that extrinsic and intrinsic motivation had a positive and significant influence on organizational performance. However, the interaction effect of intrinsic and extrinsic motivation on organizational performance was not significant, implying the absence of influence when both intrinsic and extrinsic motivations happen at the same time. Finally, the study results have a theoretical contribution for compensating the lack of actual experience in the Ethiopian organization’s context. Equally, the understanding of the moderated relationship among the study variables may encourage Oromia Seed Enterprise and its managers to develop a practical motivation system, which entertains the complex interaction of motivation variables to improve organizational performance. In addition, studies of this nature can inform policymakers to strengthen an incentive system as well as other motivation veins in the Ethiopian public organizations.

scholarly journals Association between the non-HDL-cholesterol to HDL-cholesterol ratio and non-alcoholic fatty liver disease in Chinese children and adolescents: a large single-center cross-sectional study

2020 ◽  
Author(s):  
Shouxing Yang ◽  
Jinwei Zhong ◽  
Mengsi Ye ◽  
Lei Miao ◽  
Guangrong Lu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Children And Adolescents ◽  
Binary Logistic Regression ◽  
Hdl Cholesterol ◽  
Chinese Children ◽  
Binary Logistic Regression Analysis ◽  
Cross Sectional ◽  
Alcoholic Fatty Liver ◽  
Chinese Children And Adolescents

Abstract Background: The non-HDL-cholesterol to HDL-cholesterol (NHDLC/HDLC) ratio is closely related to a variety of dyslipidemia-related diseases. This study aimed to inspect the relationship between the NHDLC/HDLC ratio and non-alcoholic fatty liver (NAFLD) in children and adolescents.Methods: In this cross-sectional survey, a total of 7,759 eligible Chinese children and adolescents (5,692 boys and 2,067 girls) received routine medical examinations. The anthropometric and laboratory data of the subjects were collected. NAFLD was diagnosed by liver ultrasonography. Binary logistic regression analysis was performed on the NHDLC/HDLC ratio, NHDLC, HDLC and NAFLD. Receiver operating characteristic (ROC) curve analysis was exploited to compare the diagnostic significance of the above parameters for NAFLD.Results: The total prevalence of NAFLD was 4.36%, and the prevalence in boys was higher than that in girls (5.61% vs. 1.9%, P < 0.001). The prevalence of NAFLD was positively correlated with the NHDLC/HDLC ratio (P < 0.001). The binary logistic regression analysis demonstrated that the OR was 8.61 (95% CI, 5.90-12.57, P < 0.001) in tertile 3 (highest NHDLC/HDLC ratio) compared with tertile 1 (lowest NHDLC/HDLC ratio). After adjustment for age, sex, body mass index (BMI), alanine aminotransferase (ALT), uric acid (UA), total bilirubin (TB), fasting plasma glucose (FPG) and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), the OR for tertile 3 (OR=1.83, 95% CI, 1.04-3.22, P = 0.035) was still significantly higher than that of tertile 1. The area under the curve (AUC) of the NHDLC/HDLC ratio of boys was 0.787, which was significantly greater than that of NHDLC and HDLC (0.719 and 0.726, P < 0.001). For girls, the AUC of the NHDLC/HDLC ratio was 0.763, which was also significantly greater than that of NHDLC (0.661, P < 0.001). Furthermore, the cutoff point of the NHDLC/HDLC ratio was 2.475 in boys and 2.695 in girls. In addition, the AUC of the NHDLC/HDLC ratio was 0.761 in subjects with normal ALT levels (ALT ≤ 40 U/L), which was significantly higher than that of NHDLC (0.680, P < 0.001) and HDLC (0.724, P = 0.007). For subjects with elevated ALT levels (ALT > 40 U/L), the AUC of the NHDLC/HDLC ratio (0.746) was also significantly greater than that of NHDLC (0.646, P < 0.001)Conclusions: The NHDLC/HDLC ratio was positively correlated with NAFLD in Chinese children and adolescents. It may serve as an effective indicator to help identify NAFLD in children and adolescents.

scholarly journals PENGARUH KEBUTUHAN BERPRESTASI DAN KARAKTERISTIK PERSONAL TERHADAP KINERJA USAHA WIRAUSAHA WANITA (Survey pada Petani Tanaman Obat Keluarga (TOGA) di Kecamatan Jumantono Kabupaten Karanganyar)

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Setyaningsih SU ◽  
Edi Wibowo
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Women Entrepreneurs ◽  
Business Performance ◽  
Binary Logistic Regression ◽  
Personal Characteristics ◽  
Binary Logistic Regression Analysis ◽  
Entrepreneurship Training ◽  
Analysis Technique ◽  
Business Experience

This study aims to analyze the effect of the needs of achievement and personal characteristics (education, age, experience, training) on business performance. This research is census research, using 63 respondents of women entrepreneurs to Toga farmers in Jumantono District, Karanganyar Regency. Data analysis technique using binary logistic regression analysis. The conclusions from the results of this study indicate that the needs of achievement and personal characteristics of business experience have a significant effect on business performance, while the variables of education, age, and entrepreneurship training have no significant effect on business performance. Based on the results of this study, the odds/probabilities of the performance of women's entrepreneurial business in Toga farmers in Jumantono District, Karanganyar Regency can be predicted by the needs of achievement and business experience. The implication of this finding is that to achieve high business performance, Toga farmers in Jumantono District, Karanganyar Regency need to increase their needs for achievement and business experience.Keywords: needs of achievement, education, age, experience, training, business performance

scholarly journals Determining factors in MSMEs success: An empirical study in Mexico

2022 ◽  
Vol 6 (1) ◽  
pp. e384
Author(s):  
Rubén Molina-Sánchez ◽  
Domingo García-Pérez-de-Lema ◽  
Alejandra López-Salazar ◽  
Roberto Godínez-López
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Empirical Study ◽  
Small And Medium Enterprises ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Technology And Innovation ◽  
Determining Factors ◽  
Quality Technology ◽  
Medium Enterprises

This work empirically analyzes the competitive factors that help make micro, small, and medium enterprises (MSMEs) successful. To do this, an empirical study with a sample of 614 companies in Guanajuato, Mexico, has been carried out. The results of the binary logistic regression analysis show that quality, technology, and innovation are the main variables that determine a company’s success. These findings could provide guidelines to help MSMEs improve their competitiveness, and they could help public administrations better support MSME growth.

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