scholarly journals Usaha Ternak Domba sebagai Jalur Keluar dari Kemiskinan Buruh Tani di Perdesaan

2020 ◽  
Vol 7 (3) ◽  
pp. 189
Author(s):  
Sondi Kuswaryan ◽  
Cecep Firmansyah ◽  
Muhammad Hasan Hadiana
Keyword(s):  
Regression Model ◽  
Poverty Alleviation ◽  
Binary Logistic Regression ◽  
Farm Labor ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Poor Households ◽  
Simple Regression Model ◽  
Poverty Status ◽  
Household Members

ABSTRAKPenelitian ini bertujuan untuk mengevaluasi kemungkinan usaha ternak domba sebagai aktivitas nafkah untuk pengentasan kemiskinan, serta menentukan jumlah kepemilikan domba yang dapat  membawa rumah tangga buruh tani keluar dari kemiskinan. Survey telah dilakukan di Desa Walangsari Kecamatan Kalapanunggal Kabupaten Sukabumi, melibatkan rumah tangga buruh tani miskin sebanyak 65 orang dan 22 orang tidak miskin. Faktor yang berpengaruh terhadap kemiskinan dianalisis menggunakan model regresi logistik biner, sedangkan jumlah kepemilikan domba yang harus dipelihara untuk keluar dari kemiskinan ditentukan dengan model regresi sederhana. Hasil penelitian menunjukkan bahwa usia kepala keluarga, dan pengalaman beternak tidak mempengaruhi kemiskinan, sedangkan jumlah kepemilikan domba, jumlah anggota rumah tangga, keterlibatan dalam kelembagaan, serta sumber pendapatan dari non pertanian mempengaruhi status kemiskinan rumah tangga buruh tani. Pada rata-rata jumlah anggota rumah tangga sebanyak 4,45 orang,untuk keluar dari kemiskinan buruh tani harus memelihara minimal sebanyak 36,63 ekor domba per rumah tangga. Hasil penelitian ini menegaskan bahwa usaha ternak domba dapat digunakan sebagai sarana untuk pengentasan kemiskinan buruh tani, program pengentasan kemiskinan akan efektif bila melibatkan kelembagaan lokal.Kata Kunci: buruh tani, jumlah kepemilikan domba, kemiskinanABSTRACTThis study aims to determine the possibility of sheep farming as a livelihood activity for poverty alleviation and to determine the amount of sheep ownership that can bring farm laborers households out of poverty. Survey research has been carried out in Walangsari Village, Kalapanunggal District, Sukabumi Regency, involving 65 poor farmer households and 22 non-poor households. Factors affecting poverty were analyzed using a binary logistic regression model, while the number of sheep ownership needed to escape poverty was determined by a simple regression model. The results showed that the age of the head of the family, and experience of sheep farmers did not affect poverty, while the number of sheep ownership, number of household members, involvement in institutions, and sources of income from non-agriculture affected the poverty status of farm laborers' households. In the average number of household members as many as 4.45 people, to get out of poverty must maintain a minimum of 36.63 sheep per household. This research explains that sheep farming can be used as a means to reduce the poverty of farm laborers, and poverty alleviation programs will be effective if they involve local institutions.Keywords: farm labor, number of sheep ownership, poverty

scholarly journals Modeling and Analyzing the Factors Affecting the Mortality of Pedestrians in Urban Accidents

2018 ◽  
Vol 14 (4) ◽  
pp. 10-21
Author(s):  
Ahmet Tortum ◽  
Alireza Motamadnia
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Motor Vehicle ◽  
Binary Logistic Regression ◽  
Education Level ◽  
Road Surface ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Surface Conditions

Abstract The nature of urban and rural accidents has been different from each other in some of the factors and even the severity of damage rate, mayhem, and death. In this research, using statistical methods and binary logistic regression model, we have addressed to analyze important parameters such as age, gender, education level, the color of the pedestrian dress, season of accident, time of accident, the speed of the vehicle colliding with pedestrians and road surface conditions at the time of accident on the way of death (at the scene of the incident or in the hospital) pedestrians who have been traumatized. After the creation of the binary logistic regression model, it was determined that only the parameters of speed and the accident time have been significant in the level less than 5%. And other parameters such as age, gender, the season of accident occurrence, the color of the pedestrian dress, road surface conditions and education level had no significant effect in terms of statistical on the incidence of mortality arising from a pedestrian accident with the motor vehicle. The results revealed that by adopting decisions related to the traffic calming, attention to passages lighting and brightness the mortality rate of a pedestrian due to the urban accidents can be reduced.

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 Prevalence and factors affecting the utilization of antenatal care in rural areas of Southwestern Ethiopia

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Assaye Belay ◽  
Tessema Astatkie ◽  
Solomon Abebaw ◽  
Bekele Gebreamanule ◽  
Wegayehu Enbeyle
Keyword(s):  
Logistic Regression ◽  
Antenatal Care ◽  
Regression Model ◽  
Rural Area ◽  
Rural Areas ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Southwestern Ethiopia

Abstract Background Antenatal care (ANC) is a health care intervention intended to ensure the safety of pregnancy. According to the World Health Organization, at least four ANC visits are recommended for a healthy pregnancy. However, whether this recommended number of visits was followed or not in the rural areas of Southwestern Ethiopia is not known. Therefore, the study aimed to investigate the prevalence of, and the associated factors of ANC utilization by pregnant women in the rural areas of Southwestern Ethiopia. Methods A community-based cross-sectional study design was used in three rural zones. The data were collected from n = 978 women through a structured questionnaire with face-to-face interview. The collected data were analyzed using descriptive statistics and a multiple binary logistic regression model. Results The results showed that 56% of women made the recommended minimum number of ANC visits and the remaining 44% of them underutilized the ANC service. The multiple binary logistic regression model identified zone, marital status of the woman, educational level of the husband, occupation of the husband, knowledge of danger signs of pregnancy, birth interval, source of information, timely visits, and transportation problem to be statistically significant factors affecting the prevalence of ANC visit utilization of women. Bench Maji zone had smaller odds ratio of ANC visit prevalence as compared to Kaffa zone. Women who lived in the rural area of Sheko zone are 2.67 times less likely to utilize ANC visit than those who lived in the rural area of Kaffa zone keeping other variables constant. Conclusion The study results highlight the need to increase the number of ANC visits, and the importance of using an appropriate model to determine the important socio-demographic factors that ANC service providers shall focus on to improve the health of the unborn baby and the mother during pregnancy.

Deciphering Links Between Sexual Violence and Castes in India

2021 ◽  
pp. 2455328X2110325
Author(s):  
Yogendra Musahar
Keyword(s):  
Regression Model ◽  
Sexual Violence ◽  
Economic Status ◽  
Family Health ◽  
Uttar Pradesh ◽  
Binary Logistic Regression ◽  
Wealth Index ◽  
Bivariate Analysis ◽  
Binary Logistic Regression Model ◽  
Explanatory Variables

The recent incident, the gang rape and murder of a 19-year-old woman in Hathras, a small village in Uttar Pradesh of India, once again sparks a debate on links between sexual violence and castes in India. This article aims to examine the links between sexual violence and castes in India. This study utilizes the national representative National Family Health Survey 4 (NFHS-4, 2015–16) data. A bivariate analysis was carried out to analyse the data. A binary logistic regression model was applied to predict the effect of explanatory variables, viz. type of place of residence, years of schooling complete, economic status in terms of wealth index and finally castes on predicted variable, i.e. sexual violence. The binary regression model indicates that there were links between sexual violence and castes. For secured and dignified life of women, caste-based sexual violence must be annihilated.

scholarly journals The Effects of Picking Up Primary School Pupils on Surrounding Street’s Traffic: A Case Study in Hanoi

2020 ◽  
Vol 14 (1) ◽  
pp. 237-250
Author(s):  
Dinh Hiep ◽  
Vu V. Huy ◽  
Teppei Kato ◽  
Aya Kojima ◽  
Hisashi Kubota
Keyword(s):  
Primary School ◽  
Traffic Safety ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Primary Schools ◽  
Traffic Accidents ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Almost All

Introduction: One of the significant characteristics of schools in Vietnam is that almost all parents send their children to school and/or pick up their children from school using private vehicles (motorcycles). The parents usually stop and park their vehicle on streets outside the school gates, which can lead to serious congestion and increases the likelihood of traffic accidents. Methods: The objective of this study is to find out factors affecting the picking up of pupils at primary school by evaluating the typical primary schools in Hanoi city. A binary logistic regression model was used to determine factors that influence the decision of picking up pupils and the waiting duration of parents. The behavior of motorcyclists during the process of picking up pupils at the primary school gate has been identified and analyzed in detail by the Kinovea software. Results and Discussion: The study showed that, on the way back home, almost all parents use motorbikes (89.15%) to pick up their children. During their waiting time (8.48 minutes in average), they made a lot of illegal parking actions on the street there by, causing a lot of “cognitive” errors and “crash” points surrounding in front of the primary school entrance gate. Risky picking-up behaviors were significantly observed, i.e. picking-up on opposite side of the school, making a U-turn, backing-up dangerously, parking on the middle of street, and parking on the street next to sidewalk). Conclusion: Based on the analyzed results, several traffic management measures have been suggested to enhance traffic safety and reduce traffic congestion in front of school gates. In addition, the results of the study will provide a useful reference for policymakers and authorities.

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

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