scholarly journals Shifting from rice production to shrimp culture in coastal zones of Khulna: Determination of the determinants

2016 ◽  
Vol 13 (2) ◽  
pp. 257-264 ◽  
Author(s):  
M Anisuzzaman ◽  
MA Islam ◽  
KMM Rahman ◽  
MSR Shetu
Keyword(s):  
Logistic Regression ◽  
Saline Water ◽  
Binary Logistic Regression ◽  
Rice Cultivation ◽  
Primary Data ◽  
Bivariate Analysis ◽  
Coastal Zones ◽  
Shrimp Culture ◽  
Access To Credit ◽  
Land Holdings

This study aimed to investigate the determinants of shifting to shrimp culture from rice cultivation in coastal zones of Khulna district by using primary data collected from the four upazillas of Khulna, namely, Batiaghata, Dacope, Dumuria, and Paikgacha. Along with bivariate analysis, single-level binary logistic regression was carried out to identify the determinants of shifting. Through the bivariate analysis it had found that among all variables considered, some variables, precisely, amount of land holdings, access to credit, contact with GOs/NGOs, intrusion of saline water, perception of profitability of shrimp, and water logging had significant relation with shifting to shrimp culture. Similarly, the binary logistic regression had identified five significant determinants of shifting from rice cultivation to shrimp culture: occupation, land holding, access to credit, intrusion of saline water, and water logging.J. Bangladesh Agril. Univ. 13(2): 257-264, December 2015

scholarly journals A predictive model for early diagnosis of keratoconus

2020 ◽  
Author(s):  
GRACIA CASTRO-LUNA ◽  
ANTONIO PÉREZ-RUEDA
Keyword(s):  
Logistic Regression ◽  
Predictive Model ◽  
Early Stage ◽  
Corneal Thickness ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Bivariate Analysis ◽  
Diagnostic Model ◽  
Binary Logistic Regression Model ◽  
Cross Sectional

Abstract Background: The diagnosis of keratoconus in the early stages of the disease is necessary to initiate an early treatment of keratoconus. Furthermore, to avoid possible refractive surgery that could produce ectasias. This study aims to describe the topographic, pachymetric and aberrometry characteristics in patients with keratoconus, subclinical keratoconus and normal corneas. Additionally to propose a diagnostic model of subclinical keratoconus based in binary logistic regression models Methods: The design was a cross-sectional study. It included 205 eyes from 205 patients distributed in 82 normal corneas, 40 early-stage keratoconus and 83 established keratoconus. The rotary Scheimpflug camera (Pentacam® type) analyzed the topographic, pachymetric and aberrometry variables. It performed a descriptive and bivariate analysis of the recorded data. A diagnostic and predictive model of early-stage keratoconus was calculated with the statistically significant variables Results: Statistically significant differences were observed when comparing normal corneas with early-stage keratoconus/ in variables of the vertical asymmetry to 90º and the central corneal thickness. The binary logistic regression model included the minimal corneal thickness, the anterior coma to 90º and posterior coma to 90º. The model properly diagnosed 92% of cases with a sensitivity of 97.59%, specificity 98.78%, accuracy 98.18% and precision 98.78%Conclusions: The differential diagnosis between normal cases and subclinical keratoconus depends on the mínimum corneal thickness, the anterior coma to 90º and the posterior coma to 90º.

scholarly journals Corner kick effectiveness in the Greek Super League 2018-2019

2021 ◽  
pp. 29-37
Author(s):  
Mitrotasios M
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
The Other ◽  
Bivariate Analysis ◽  
Other Hand ◽  
Key Variables ◽  
Super League

The aim of the present study was to describe how corner kicks were taken and to identify key variables associated with final attempts during Greek Super League season 2018-19. There was a total of 424 final attempts after corner kick, of which, 16.3% were attempts off target, 6.8% attempts on target and 2.8% resulting in a goal. Bivariate analysis presented that attempts on target were increased when the ball was delivered outswing, no players positioned at the goal posts, >1 intervening attackers, attacking player the 1st contact and ball delivered into the central zones of the 18-yard box. Binary logistic regression (Final attempt/ No Final attempt) revealed that the model was statistically significant for the final attempt (p < 0.001) and showed that the intervening attackers (p < 0.001) and the player of the 1st contact (p < 0.001) contributed significantly to the model. These results can aid coaches to enhance on one hand the attacking effectiveness; on the other hand the defensive efficacy of corner kicks within Greek football.

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI PEROLEHAN KREDIT OLEH PENGUSAHA MIKRO

2018 ◽  
Vol 4 (3) ◽  
Author(s):  
Abdul Azis Safii ◽  
Tri Suwarno
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Large Scale ◽  
Logistic Regression Model ◽  
Banking Sector ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Access To Credit ◽  
The Poor ◽  
Micro Enterprises

Abstract: The number of micro-entrepreneurs and the dominant number of micro enterprises compared to medium and large-scale enterprises in Indonesia are not balanced by the provision of access to credit and venture capital for micro businesses. This resulted in a micro-sector sector identical to the poor being vulnerable to exploitation by moneylenders who exploit the difficulties of micro entrepreneurs accessing credit from the banking sector. This study examines the factors that determine the accessibility of credit by micro entrepreneur in Bojonegoro regency. A total sum of 270 micro entrepreneurs who have applied for banking loan were sampled from the study area. With an binary logistic regression model the research resulting that education, skill on entrepreneur, and monthly net profits generated by the microenterprise are significant in determining the accessibility of microcredit. Keywords: micro entrepreneur, microcredit, credit accessibility Abstrak: Perkembangan jumlah pengusaha mikro serta dominannya jumlah usaha mikro dibandingkan dengan usaha menengah dan usaha besar di Indonesia, tidak diimbingi dengan penyediaan akses kredit dan modal usaha bagi para pelaku usaha mikro. Hal tersebut mengakibatkan sektor usaha mikro yang identik dengan masyarakat miskin rentan dieksploitasi oleh rentenir yang memanfaatkan sulitnya para pengusaha mikro mengakses kredit dari sektor perbankan. Penelitian ini menggunakan data primer yang di ambil langsung dari pengusaha mikro dengan teknik kuesioner. Analisis data dengan metode binary logistic regression mendapatkan hasil variabel yang berpengaruh signifikan terhadap akses kredit para pengusaha mikro adalah variabel usia pengusaha, laba bersih usaha tiap bulan, dan jumlah karyawan yang di pekerjakan. Kata kunci : usaha mikro, microcredit, akses kredit

scholarly journals The value of university internships

2021 ◽  
Vol 40 ◽  
pp. 127-148
Author(s):  
Sandra Fachelli ◽  
Eric Fernández-Toboso
Keyword(s):  
Logistic Regression ◽  
University Students ◽  
Labour Market ◽  
Binary Logistic Regression ◽  
Regression Technique ◽  
Job Placement ◽  
Bivariate Analysis ◽  
University Graduates ◽  
Using Data

Universities place particular importance on their internship projects for university students. The purpose of this study is to identify if the internships have an impact on the students’ entry to the labour market. The methodology used is based on the bivariate analysis and the multiple binary logistic regression technique, using data from the 2014 Survey on the Labour Insertion of University Graduates (EILU), carried out by the INE. The sample used comprises 30,379 graduates and in the internships section, 21,622 university graduates. The results obtained confi rm that internships are a tool for job placement.

scholarly journals A predictive model for early diagnosis of keratoconus

2020 ◽  
Author(s):  
GRACIA CASTRO-LUNA ◽  
ANTONIO PÉREZ-RUEDA
Keyword(s):  
Logistic Regression ◽  
Predictive Model ◽  
Corneal Thickness ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Bivariate Analysis ◽  
Diagnostic Model ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Logistic Regression Models

Abstract Background: The diagnosis of keratoconus in the early stages of the disease is necessary to initiate an early treatment of keratoconus. Furthermore to avoid possible refractive surgery that could produce ectasias. This study aims to describe the topographic, pachymetric and aberrometry characteristics in patients with keratoconus, subclinical keratoconus and normal corneas. Additionally to propose a diagnostic model of subclinical keratoconus based in binary logistic regression models Methods: The design was a cross-sectional study. It included 205 eyes from 205 patients distributed in 82 normal corneas, 40 subclinical keratoconus and 83 established keratoconus The rotary Scheimpflug camera (Pentacam® type) analyzed the topographic, pachymetric and aberrometry variables. It performed a descriptive and bivariate analysis of the recorded data. A diagnostic and predictive model of subclinical keratoconus was calculated with the statistically significant variables Results: Statistically significant differences were observed when comparing normal corneas with subclinical keratoconus/ in variables of the vertical asymmetry to 90º and the central corneal thickness. The binary logistic regression model included the minimal corneal thickness, the anterior coma to 90º and posterior coma to 90º. The model properly diagnosed 92% of cases Conclusions: The differential diagnosis between normal cases and subclinical keratoconus depends on the mínimum corneal thickness, the anterior coma to 90º and the posterior coma to 90º.

scholarly journals The Impact of International Remittances on Poverty Alleviation in Bangladesh

2019 ◽  
Vol 4 (1) ◽  
pp. 67-86 ◽  
Author(s):  
Bezon Kumar
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Poverty Alleviation ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Binary Logistic Regression Model ◽  
Household Poverty ◽  
International Remittances ◽  
The Impact

This article mainly explores to what extent international remittances alleviate household poverty in Bangladesh. This study uses primary data collected from 216 households and employs multi-methods. Firstly, I measure the level of household poverty through Foster-Greer-Thorbecke index. The article secondly focuses on the impact of remittances on household poverty using a binary logistic regression model. I found that the level of poverty among remittance recipient households is notably lower than households that are not receiving remittances. Similarly, the probability of a household being poor is alleviated by 28.07 per cent if the household receives remittance. It can be suggested that nursing international remittances can be useful for poverty alleviation in Bangladesh. 

scholarly journals THE DETERMINANTS OF REVERSE MORTGAGE CHOICE OF INDIAN ELDERLY HOMEOWNERS FOR SUSTAINABLE LIVELIHOOD: A LOGIT ANALYSIS

2019 ◽  
Vol 7 (4) ◽  
pp. 309-317
Author(s):  
Sarita Gupta ◽  
Dr. Sanjay Kumar
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Later Life ◽  
Primary Data ◽  
Logit Analysis ◽  
Sustainable Livelihood ◽  
Housing Wealth ◽  
Home Equity ◽  
Reverse Mortgage ◽  
Insurance Cover

Purpose: In the regime of stretched old-age social security, federals and policymakers are presuming housing wealth as a means of sustainable livelihood for elderly homeowners.  The current study attempts to discover which demographic and financial factors are significant determinants of home equity liquidation through reverse mortgage of Indians in later life. Methodology: Binary logistic regression is applied to survey-based primary data of 410 elderly homeowners through SPSS software. Main Findings: Results of binary logistic regression model depicts that elderly considering an RM likely to be female, older, having poor health, childless or having girl child only, long life expectancy, resident of metro, employed, cash-constrained, not having any kind of insurance cover and those children are financially well are significantly more willing to opt for RM scheme. Implication: Study renders implications for Government and NHB, to provide refinancing facility to commercial banks so that home equity liquidation product like Reverse Mortgage can be able to fulfill income needs of greying India. Novelty/Originality: Length of research in European and western countries have been carried out to explore the attitude of older homeowner for housing wealth liquidation but Indian context, is largely untapped that how Indian older homeowner perceive their housing wealth and which factor influences them to delete it. In this way, current study attempts to bridge the research gap.

scholarly journals ANALISIS FAKTOR YANG MEMPENGARUHI STATUS PENERIMAAN BERAS KELUARGA MISKIN MENGGUNAKAN REGRESI LOGISTIK BINER DI KECAMATAN LANGSA BARAT

2020 ◽  
Vol 14 (2) ◽  
pp. 181-192
Author(s):  
Amelia Amelia ◽  
Fitra Mulyani ◽  
Ulya Nabilla
Keyword(s):  
Logistic Regression ◽  
Economic Status ◽  
Secondary Data ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Binary Logistic Regression Analysis ◽  
Binary Logistic Regression Model ◽  
The Status ◽  
Rice Consumption ◽  
The Government

Poverty is an inability to meet basic needs measured by expenditure, including rice consumption. Based on data from the Central Statistics Agency (BPS), as much as 95% of Indonesia's population consumes rice as the main food, with an average rice consumption of 102 kg/person/ year (BPS, 2013). Furthermore, BPS stated that almost 1/4 of them or around 25.95 million people were included in the category of the poor population as of March 2018. So the government made a policy to tackle the problem through the program of giving poor family rice (Raskin), namely subsidized rice assistance to households poor. However, in the implementation of the Raskin program, there was a deviation of around 40% of Indonesia's population with a middle-upper social-economic status receiving Raskin and 12.5% ​​of the population with a socio-economic status upon receiving Raskin. Therefore this study aims to analyze the significant factors that affect the status of rice in poor families using binary logistic regression analysis. The location of the study was conducted in the District of West Langsa because the district was one of the districts receiving the most Raskin in the City of Langsa. The data used in this study are primary data and secondary data. The results of the analysis show that the factors that influence Raskin's acceptance status are the level of education, type of floor, type of fuel, expenditure for food, and frequency of purchasing new clothes. The binary logistic regression model obtained is

scholarly journals Analisis Faktor-Faktor yang Mempengaruhi Keputusan Migrasi Commuter di Kabupaten Demak

2018 ◽  
Vol 5 (4) ◽  
pp. 345-353
Author(s):  
Ahmad Shidiq
Keyword(s):  
Logistic Regression ◽  
Marital Status ◽  
Secondary Data ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Migration Decision ◽  
Significant Positive Effect ◽  
Rural Regions ◽  
Negative Effect ◽  
Positive Effect

Fenomena migrasi sangat mewarnai di beberapa negara berkembang, termasuk di berbagai daerah di Indonesia. Di Indonesia terutama banyak tenaga kerja yang berasal dari daerah pedesaan mengalir ke daerah perkotaan, Salah satunya dari Kabupaten Demak. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi keputusan migrasi commuter di Kecamatan Karangtengah Kabupaten Demak antara lain adalah pendapatan pendidikan, pekerjaan daerah asal, jumlah tanggungan serta status perkawinan. Dalam penelitian ini menggunakan data primer melalui instrumen kuesioner terhadap sampel yaitu sebanyak 89 responden, dan menggunakan data sekunder yaitu data dari instansi-instansi terkait serta literatur buku. Penelitian ini dilakukan di Kecamatan Karangtengah Kabupaten Demak. Analisi yang digunakan dalam penelitian ini adalah binary logistic regression. Hasil penelitian menunjukkan bahwa pendapatan berpengaruh negatif dan signifikan terhadap keputusan migrasi commuter, pendidikan berpengaruh positif dan tidak signifikan terhadap keputusan migrasi commuter, pekerjaan di daerah asal berpengaruh positif dan tidak signifikan terhadap keputusan migrasi commuter, jumlah tanggungan daerah asal berpengaruh negatif dan tidak signifikan terhadap keputusan migrasi commuter, status perkawinan berpengaruh positif dan signifikan terhadap keputusan migrasi commuter. The phenomenon of migration is very coloring in some developing countries , including in the various regions in Indonesia . In Indonesia especially many workers coming from rural regions flowed into the urban area, One of Demak District. This study aims to determine the factors that influence the decision of commuter migration in Sub Karangtengah Demak district include the earnings of education, employment areas of origin, number of dependents and marital status. In this research, using primary data through a questionnaire on the sample of 89 respondents, and using secondary data is data from relevant agencies and literature books. This research was conducted at Sub Karangtengah, Demak District. The analysis used in this study is a binary logistic regression. The results showed that the income a significant negative effect on the migration decision commuter, education has positive and not significant to the migration decision commuter, work in the area of origin has positive and not significant to the migration decision commuter, number of dependents homelands negative and not significant to decision commuter migration, marital status and significant positive effect on the decision commuter migration.

scholarly journals Analysis of Factors that Influence Migration in Alian and Ayah Subdistrict, Kebumen Regency, Central Java

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Diah Tiara Rahmasari ◽  
Abdul Aziz Ahmad
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Influential Factor ◽  
Primary Data ◽  
Or Education ◽  
Central Java ◽  
The Family ◽  
Medium Level ◽  
Work Skill ◽  
The Government

This research aimed to analyses migrants’ income contribution to income of the family at hometown, the influences of income, age, numbers of family to be responsible to, education, and marriage status on decision about migration in Kebumen. The method used in the research was survey of primary data which is gained through interviews and questionnaires. The data in this research were 91 migrants in Alian and Ayah Districts. Data analysis techniques used were binary logistic regression. The results showed that the contribution of migrants’ income to family’s income after migrating to the two districts was in medium level. It showed that the needs to live in migration place were expensive. Consequently, the income obtained in migration place could not give enough contribution to the family in hometown. Based on the analysis, the variable of the numbers of people the migrants had positive and significant effect for migration. Income and marriage variables status had negative and significant effect. While age and education variables had no contribution to the migration. Income is the most influential factor in migration, so the government or related organizations should give attentions to the citizen’s prosperity by creating making the job activities. The government and the society should cooperate in developing the economic potential in each area. It is also by giving the society some loans and work-skill coaching or education to increase their income. Those are to encourage the society to be more creative and autonomous.Keywords: Binary Logistic Regression, Citizen’s Prosperity, Marriage Status.

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