scholarly journals A SURVEY ON RURAL SCHOOL STUDENTS EDUCATION PERFORMANCE USING DATA MINING TECHNIQUES

2021 ◽  
pp. 209-212
Author(s):  
Suresh Solomon. G ◽  
Nancy Jasmine Goldina
Keyword(s):  
Data Mining ◽  
Rural Areas ◽  
Urban Areas ◽  
Research Study ◽  
Rural School ◽  
Vital Role ◽  
School Students ◽  
And Performance ◽  
Using Data ◽  
Education Performance

In India there exists a lot of Rural areas in which the educational performance of the rural school students are inferior when compared it to the performance of the urban areas due to the lack of facilities, environment, income, employment opportunities and exposure. Equality is one among the basic principle of our country, so it’s a mere responsibility of any research study to perform a detailed analysis towards the performance of rural school students by focusing on to the factors to be monitored and improved so that the Rural areas also raise to the equilant level of competition with the Urban areas. For this goal Data mining plays a vital role in order to handle the data in proper way for analysis and prediction of performances for the improvement of rural school student’s education domain results. This paper presents a survey on Data Mining strategies used for prediction and performance analysis of rural school students education improvements. KEYWORDS—Data Mining, Rural, Urban, Prediction, Performance

scholarly journals Rurality and Origin–Destination Trajectories of Medical School Application and Matriculation in the United States

2021 ◽  
Vol 10 (6) ◽  
pp. 417
Author(s):  
Lan Mu ◽  
Yusi Liu ◽  
Donglan Zhang ◽  
Yong Gao ◽  
Michelle Nuss ◽  
...  
Keyword(s):  
Medical School ◽  
Rural Areas ◽  
Urban Areas ◽  
The United States ◽  
Application Rate ◽  
School Students ◽  
Rural Counties ◽  
Physician Shortages ◽  
The Us ◽  
Using Data

Physician shortages are more pronounced in rural than in urban areas. The geography of medical school application and matriculation could provide insights into geographic differences in physician availability. Using data from the Association of American Medical Colleges (AAMC), we conducted geospatial analyses, and developed origin–destination (O–D) trajectories and conceptual graphs to understand the root cause of rural physician shortages. Geographic disparities exist at a significant level in medical school applications in the US. The total number of medical school applications increased by 38% from 2001 to 2015, but the number had decreased by 2% in completely rural counties. Most counties with no medical school applicants were in rural areas (88%). Rurality had a significant negative association with the application rate and explained 15.3% of the variation at the county level. The number of medical school applications in a county was disproportional to the population by rurality. Applicants from completely rural counties (2% of the US population) represented less than 1% of the total medical school applications. Our results can inform recruitment strategies for new medical school students, elucidate location decisions of new medical schools, provide recommendations to close the rural–urban gap in medical school applications, and reduce physician shortages in rural areas.

IMPLEMENTASI ALGORITMA K-Modes UNTUK MENENTUKAN STRATEGI MARKETING STMIK BUDI DARMA

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Ewin Karman Nduru ◽  
Efori Buulolo ◽  
Pristiwanto Pristiwanto
Keyword(s):  
High School ◽  
Data Mining ◽  
High School Students ◽  
Marketing Strategy ◽  
Process Data ◽  
School Students ◽  
The North ◽  
The Government ◽  
Using Data ◽  
North Sumatra

Universities or institutions that operate in North Sumatra are very many, therefore, of course, competition in accepting new students is very tight, universities or institutions do certain ways or steps to be able to compete with other campuses in gaining interest from community or high school students who will continue their studies to a higher level. STMIK BUDI DARMA Medan (College of Information and Computer Management), is the first computer high school in Medan which was established on March 1, 1996 and received approval from the government through the Minister of Education and Culture, on July 23, 1996 with operating license number 48 / D / O / 1996, in promoting the campus, the team usually formed a promotion team to various regions in the North Sumatra Region to provide information to the community. Students who have learned in this campus are quite a lot who come from various regions in North Sumatra, from this point the need to process data from students who are active in college to be processed using data mining to achieve a target, one method that can be used in data mining, namely the ¬K-Modes clustering (grouping) algorithm. This method is a grouping of student data that will be a help to campus students in promoting, using the K-Modes algorithm is expected to help and become a reference for marketing in determining the marketing strategy STMIK Budi Darma MedanKeywords: STMIK Budi Darma, Marketing Strategy, K-Modes Algorithm.

scholarly journals Frequency of consumption of fruits, vegetables and soft drinks: a comparative study among adolescents in urban and rural areas

2014 ◽  
Vol 17 (2) ◽  
pp. 371-380 ◽  
Author(s):  
Iza Cristina de Vasconcelos Martins Xavier ◽  
Carla Menêses Hardman ◽  
Maria Laura Siqueira de Souza Andrade ◽  
Mauro Virgilio Gomes de Barros
Keyword(s):  
High School Students ◽  
Rural Areas ◽  
Urban Areas ◽  
Soft Drinks ◽  
Fruit Juices ◽  
Daily Consumption ◽  
School Students ◽  
Cross Sectional ◽  
Validated Questionnaire ◽  
Urban And Rural Areas

Objective: To compare the frequency of consumption of fruits, vegetables and soft drinks among adolescents living in urban and rural areas of Pernambuco State. Methods: A cross-sectional study based on secondary analysis of data from a representative sample of high school students in Pernambuco (n = 4,207, 14 - 19 years) was conducted. Data were collected through a previously validated questionnaire. Adolescents who reported a daily consumption of soft drinks and occasional consumption of fruits, juices and vegetables were classified as exposed to inadequate standard of consumption of these foods. The independent variable was the place of residence (urban/rural). Data were analyzed by frequency distribution, χ2 test and binary logistic regression. Results: It was observed that students residing in rural areas had a higher prevalence of occasional consumption of natural fruit juices (37.6%; 95%CI 36.1 - 39.0) than those living in urban areas (32.1%; 95%CI 30.7 - 33.6). The proportion of students exposed to daily consumption of soft drinks was higher among those who reported they lived in urban areas (65.0%; 95%CI 63.5 - 66.4) compared to those who reported living in rural areas (55.3%; 95%CI 53.8 - 56.9). Conclusion: Adolescent students living in rural areas had a higher prevalence of low consumption of natural fruit juices while those residing in urban areas had a higher prevalence of daily consumption of soda drinks.

scholarly journals Income differentials on regional labour markets in Southwest Germany

2009 ◽  
Vol 56 (3) ◽  
pp. 379-396
Author(s):  
Alice Guyot ◽  
Stefan Berwing ◽  
Maria Lauxen-Ulbrich
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Descriptive Statistics ◽  
Pay Gap ◽  
Explanatory Variables ◽  
Income Differentials ◽  
Income Disparities ◽  
Regional Labour Markets ◽  
Using Data ◽  
Regional Types

The aim of our paper is to identify explanatory variables for income disparities between women and men across different regional types. Using data from the BA Employment Panel (BEP) descriptive statistics show that the gender pay gap grows wider from core regions to periphery. The main explanatory variables for the income differentials are vocational education in the men's case and size of enterprise in the women's case. Whereas in the case of women the importance of vocational status increases and the importance of size of enterprise decreases from rural areas to urban areas.

Sexual exploitation of adolescent students in Tanzania: Implication for social services

2018 ◽  
Vol 62 (3) ◽  
pp. 1104-1116 ◽  
Author(s):  
Budeba Petro Mlyakado ◽  
Jessica Chi-Mei Li
Keyword(s):  
Secondary School ◽  
Social Services ◽  
Rural Areas ◽  
Secondary School Students ◽  
Sexual Exploitation ◽  
Limited Information ◽  
School Students ◽  
Adolescent Students ◽  
Using Data ◽  
Collaborative Efforts

A considerable empirical research has been conducted on sexual exploitation of children and adolescents; however, limited information is available in developing countries. This study describes and discusses the prevalence, nature and characteristics of sexual exploitation of adolescents using data collected from 1116 secondary school students in Tanzania. Results indicate that 21 percent of the surveyed adolescent students had had at least one experience of sexual exploitation. Being a female, living in rural areas and being aged above 15 years were associated with high risk of sexual exploitation. This study underscores gender- and locality-specific social work interventional requirements, with emphasis on interdisciplinary collaborative efforts.

Improving Student's Campus Placement at Rural Area's of Palghar District Using Data Mining

2021 ◽  
Vol 13 (SUP 1) ◽  
pp. 66-69
Author(s):  
Yugandhara More
Keyword(s):  
Data Mining ◽  
Rural Areas ◽  
Significant Issue ◽  
Using Data

Data Mining is perhaps the best field to improve Campus Placement. Placement is significant issue for universities which are situated in provincial territory. Each association needs to improve their placements. Therefore for successful placement; in this paper I have collected data of various colleges of rural areas of Palghar District. After this I have analyzed that where the students are facing problems in Campus Placement and these problems report will be given to the colleges, then colleges could improve student's campus placement.

A Survey on Building Recommendation Systems Using Data Mining Techniques

2022 ◽  
pp. 24-56
Author(s):  
Rajab Ssemwogerere ◽  
Wamwoyo Faruk ◽  
Nambobi Mutwalibi
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Recommender Systems ◽  
Performance Measures ◽  
Data Mining Technique ◽  
Data Mining Techniques ◽  
Learning Hypothesis ◽  
Depth Study ◽  
And Performance ◽  
Using Data

Classification is a data mining technique or approach used to estimate the grouped membership of items on a basis of a common feature. This technique is virtuous for future planning and discovering new knowledge about a specific dataset. An in-depth study of previous pieces of literature implementing data mining techniques in the design of recommender systems was performed. This chapter provides a broad study of the way of designing recommender systems using various data mining classification techniques of machine learning and also exploiting their methodological decisions in four aspects, the recommendation approaches, data mining techniques, recommendation types, and performance measures. This study focused on some selected classification methods and can be so supportive for both the researchers and the students in the field of computer science and machine learning in strengthening their knowledge about the machine learning hypothesis and data mining.

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