scholarly journals PENERAPAN ALGORITMA C4.5 PADA KLASIFIKASI POTENSI SISWA DROP OUT

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Muhamad Muhamad ◽  
Agus Perdana Windarto ◽  
Suhada Suhada
Keyword(s):  
Learning System ◽  
Drop Out ◽  
Dropping Out ◽  
Student Dropout ◽  
The World ◽  
C4.5 Algorithm ◽  
New Students ◽  
Education Today

Students are one of the substances that need to be considered in relation to the world of education today. The difficulty of getting students makes the school have to optimize the learning system and infrastructure as well to attract the interest of new students and also make students who have gone to school not drop out or drop out. One of the factors contributing to the large number of students dropping out is because of the lack of policies and actions from the education institutions to keep their students from dropping out. The purpose of this study was to classify potentially dropout students and not have the potential to drop out with the C4.5 algorithm as a reference in making policies and actions to reduce the number of students dropping out. The classification results of the C4.5 algorithm are evaluated and validated with RapidMinerStudio to determine the accuracy of the C4.5 Algorithm in classifying potential dropouts.Keywords: Student dropout, Classification, C4.5 Algorithm

scholarly journals FAMILY'S SOCIO-ECONOMIC INFLUENCE ON THE DROPOUT OF INDIAN STUDENTS: A CASE STUDY IN THE DISTRICT OF KUALA MUDA KEDAH

2019 ◽  
Vol 2 (9) ◽  
pp. 77-91
Author(s):  
TH. Subra ◽  
Mohamad Ainuddin Iskandar Lee Abdullah ◽  
Kala Devi
Keyword(s):  
Low Income ◽  
Drop Out ◽  
Dropout Rates ◽  
Dropping Out ◽  
Low Socioeconomic ◽  
Student Dropout ◽  
Indian Student ◽  
The Family ◽  
Parental Commitment ◽  
Indian Students

The problem of dropping out of Indian students should be addressed especially with regard to low-income households (B40). There are many factors driving the dropout of Indian students in schools. The purpose of this study is to examine the socioeconomic factors of the family and the parents' commitment to Indian student dropout. Among its objectives are to identify the socioeconomic influence of the family and the parents' commitment to the dropout of Indian students; learn about the implications of Indian student dropout rates and identify steps to curb Indian student dropout problems. This study was conducted in selected areas in Kuala Muda District of Kedah State, Malaysia involving high school dropout Indian students. This research is qualitative and cannot be extended to other states as researchers use interviewing observation and documentation research. The respondents to this study were 5 dropout students, mostly from B40 families. The findings of this study found that low socioeconomic influence of parents and lack of parental commitment to children's education caused students to drop out of school. The implications of dropping Indian students are also discussed and some suggestions have been made to reduce dropout rates among Indian students.

scholarly journals The Connection between Extracurricular, Leisure Time Activities, Religiosity and the Reasons for Drop-out

2019 ◽  
Vol 1 (1) ◽  
pp. 55-67
Author(s):  
Judit Váradi ◽  
Zsuzsanna Demeter-Karászi ◽  
Klára Kovács
Keyword(s):  
Education Research ◽  
Extracurricular Activities ◽  
Leisure Time ◽  
Tertiary Education ◽  
Dropout Rate ◽  
Further Education ◽  
Drop Out ◽  
Dropping Out ◽  
Educational Sociology ◽  
Student Dropout

The interruption of tertiary education and the reduction in the dropout rate have been a central issue in educational sociology and education research. Exploring the possible reasons for dropping out can significantly contribute to reducing the trend. Our aim is to map the links between students dropping out and individual factors. Consequently, we investigate the connection between extracurricular and leisure-time activities, health behaviour and religiosity in relation to dropout. This is explained by the fact that one of the axioms of the literature on dropout is that belonging to civil networks usually strengthens the commitment to the successful completion of studies. In our analysis, we used the database created during the research carried out in 2018 by the Center for Higher Education Research and Development (CHERD-H) in the framework of project No. 123847 of the National Research, Development and Innovation Fund of Hungary, entitled The Role of Social and Organisational Factors in Student Dropout (DEPART 2018, N=605). Our results show that the neglect of study obligations among those who are disappointed in the course and further education is closely related to the shift in value preferences and an increase in the time spent with entertainment activities and partying. It can also be stated that students take part indifferent types of extracurricular activities only to a limited extent, and the different forms of participation in activities and religiosity are not related to the causes of dropout.

The effect of college acquisitions and mergers on student dropout behaviour: evidence from the UK

2020 ◽  
Vol 72 (3) ◽  
pp. 606-632
Author(s):  
Rossella Iraci Capuccinello ◽  
Steve Bradley
Keyword(s):  
Further Education ◽  
Drop Out ◽  
Dropping Out ◽  
Negative Effects ◽  
Policy And Practice ◽  
Student Dropout ◽  
Positive Effects ◽  
One Year ◽  
The Uk ◽  
Over Time

Abstract We investigate the effect of college acquisitions on the probability of students dropping out of college. Using administrative data for the further education (FE) sector, which covers multiple cohorts, we estimate matching models and combine them with difference-in-differences methods to remove the effects of unobserved student and college heterogeneity. Overall our findings show that acquisitions reduce the probability of dropout by 0.01 percentage points, but this varies in magnitude and direction over time. In general, positive effects of acquisitions on drop out behaviour tend to be small (e.g. 0.001 for acquisitions in 2004) and dissipate over time, whereas negative effects persist and tend to increase in magnitude over time (e.g. −0.05 one year later and −0.07 two years later). We discuss the implications for policy and practice in the sector, as well as suggesting a need for similar analyses in other education sectors, such as primary and secondary schooling.

An Information System for Coping with Student Dropout

2011 ◽  
Vol 7 (3) ◽  
pp. 62-73
Author(s):  
Ester Aflalo ◽  
Eyal Gabay
Keyword(s):  
At Risk ◽  
Information System ◽  
Drop Out ◽  
Dropping Out ◽  
Control Group ◽  
Students At Risk ◽  
Student Dropout ◽  
Research Population ◽  
Research Findings ◽  
Experimental Group

Student dropout prevention is one of the most important challenges of the education system. This study examines the effectiveness of a Local Authority Information Center (LAIC), developed in Israel to cope with that problem. The research population included 418 regular attendance officers (RAOs), educators who deal with students who drop out and those who are at risk of dropping out. The RAOs were divided into an experimental group, who performed their work using the information system, and a control group who used manual means. The research findings show that the information system improved the comprehensive nature of the information and its relevance for students at risk of dropping out, and resulted in an increase in the number of students treated by the RAOs. This improvement was maintained over a period of three years. The LAIC is likely to offer an effective and professional approach to reducing the problem of student dropout.

Alignment

2016 ◽  
pp. 33-50
Author(s):  
Pier Giuseppe Rossi
Keyword(s):  
Teaching And Learning ◽  
Enactive Approach ◽  
The World ◽  
Strategic Role ◽  
Education Today ◽  
Current Context ◽  
The Subject

The subject of alignment is not new to the world of education. Today however, it has come to mean different things and to have a heuristic value in education according to research in different areas, not least for neuroscience, and to attention to skills and to the alternation framework.This paper, after looking at the classic references that already attributed an important role to alignment in education processes, looks at the strategic role of alignment in the current context, outlining the shared construction processes and focusing on some of the ways in which this is put into effect.Alignment is part of a participatory, enactive approach that gives a central role to the interaction between teaching and learning, avoiding the limits of behaviourism, which has a greater bias towards teaching, and cognitivism/constructivism, which focus their attention on learning and in any case, on that which separates a teacher preparing the environment and a student working in it.

Implementasi Data Mining dengan Algoritma C4.5 untuk Memprediksi Tingkat Kelulusan Mahasiswa

2014 ◽  
Vol 6 (1) ◽  
pp. 15-20 ◽  
Author(s):  
David Hartanto Kamagi ◽  
Seng Hansun
Keyword(s):  
Data Mining ◽  
Drop Out ◽  
Time Pass ◽  
Academic Fields ◽  
C4.5 Algorithm ◽  
Index Terms ◽  
Using Data ◽  
Academic Year ◽  
Source Of Information ◽  
Test Result

Graduation Information is important for Universitas Multimedia Nusantara  which engaged in education. The data of graduated students from each academic year is an important part as a source of information to make a decision for BAAK (Bureau of Academic and Student Administration). With this information, a prediction can be made for students who are still active whether they can graduate on time, fast, late or drop out with the implementation of data mining. The purpose of this study is to make a prediction of students’ graduation with C4.5 algorithm as a reference for making policies and actions of academic fields (BAAK) in reducing students who graduated late and did not pass. From the research, the category of IPS semester one to semester six, gender, origin of high school, and number of credits, can predict the graduation of students with conditions quickly pass, pass on time, pass late and drop out, using data mining with C4.5 algorithm. Category of semester six is the highly influential on the predicted outcome of graduation. With the application test result, accuracy of the graduation prediction acquired is 87.5%. Index Terms-Data mining, C4.5 algorithm, Universitas Multimedia Nusantara, prediction.

Dropout from an internet-delivered CBT Intervention for Adults with Depression and Anxiety: A Qualitative Study (Preprint)

2020 ◽  
Author(s):  
Kate Lawler ◽  
Caroline Earley ◽  
Ladislav Timulak ◽  
Angel Enrique ◽  
Derek Richards
Keyword(s):  
Online Communication ◽  
Structured Interview ◽  
Routine Care ◽  
Drop Out ◽  
Group Differences ◽  
Dropping Out ◽  
Completion Rates ◽  
Depression And Anxiety ◽  
Lower Treatment ◽  
Perceived Change

BACKGROUND Treatment dropout continues to be reported from iCBT interventions and lower completion rates are generally associated with lower treatment effect sizes. However, evidence is emerging to suggest that completion of a pre-defined number of modules is not always necessary for clinical benefit nor considerate of the needs of each individual patient. OBJECTIVE The study aimed to carry out a qualitative analysis of patients’ experiences of an iCBT intervention in a routine care setting in order to achieve a deeper insight into the phenomenon of dropout. METHODS Fifteen purposively sampled participants (8 female) from a larger parent RCT were interviewed via telephone using a semi-structured interview schedule that was developed from the existing literature and research on dropout in iCBT. Data was analysed using the descriptive-interpretive approach. RESULTS The experience of treatment leading to dropout can be understood in terms of ten domains: Relationship to Technology, Motivation to Start, Background Knowledge and Attitudes towards iCBT, Perceived Change in Motivation, Usage of the Programme, Changes due to the Intervention, Engagement with Content, Experience Interacting with the Supporter, Experience of Online Communication and Termination of the Supported Period. CONCLUSIONS Patients who drop out of treatment can be distinguished in terms of their change in motivation: those who felt ready to leave treatment early and those who had negative reasons for dropping out. These two groups of participants have different treatment experiences, revealing potential attributes and non-attributes of dropout. The reported between group differences should be examined further to consider those attributes that are strongly descriptive of the experience and regarded with less importance those that have become loosely affiliated.

scholarly journals Preventing corneal blindness caused by keratitis using artificial intelligence

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhongwen Li ◽  
Jiewei Jiang ◽  
Kuan Chen ◽  
Qianqian Chen ◽  
Qinxiang Zheng ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
Vision Loss ◽  
Learning System ◽  
Automated Classification ◽  
Slit Lamp ◽  
Resource Limited ◽  
The World ◽  
Different Types ◽  
Corneal Blindness

AbstractKeratitis is the main cause of corneal blindness worldwide. Most vision loss caused by keratitis can be avoidable via early detection and treatment. The diagnosis of keratitis often requires skilled ophthalmologists. However, the world is short of ophthalmologists, especially in resource-limited settings, making the early diagnosis of keratitis challenging. Here, we develop a deep learning system for the automated classification of keratitis, other cornea abnormalities, and normal cornea based on 6,567 slit-lamp images. Our system exhibits remarkable performance in cornea images captured by the different types of digital slit lamp cameras and a smartphone with the super macro mode (all AUCs>0.96). The comparable sensitivity and specificity in keratitis detection are observed between the system and experienced cornea specialists. Our system has the potential to be applied to both digital slit lamp cameras and smartphones to promote the early diagnosis and treatment of keratitis, preventing the corneal blindness caused by keratitis.

Sign in / Sign up

Export Citation Format

Share Document