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All Journal Jurnal Pendidikan Bahasa Inggris Nuansa Informatika English Review: Journal of English Education Cloud Information JOIN (Jurnal Online Informatika) Empowerment : Jurnal Pengabdian Masyarakat Indonesian Journal Of Business And Economics Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Abdimasku : Jurnal Pengabdian Masyarakat Journal of Technology and Informatics (JoTI) International Journal Administration, Business & Organization Journal of Innovation and Sustainable Empowerment Nuansa Informatika Jurnal Pengabdian Masyarakat Ilmu Komputer Scientific Exploration: Journal Of Indonesian Academic Research Fon: Jurnal Pendidikan Bahasa dan Sastra Indonesia
Erlan Darmawan
Univeritas Kuningan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences Other

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Journal : join jurnal online informatika

 1 
C4.5 Algorithm Application for Prediction of Self Candidate New Students in Higher Education Erlan Darmawan
JOIN (Jurnal Online Informatika) Vol 3 No 1 (2018)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v3i1.171

Abstract

Data mining has background with the condition of an abundance of data (the overload data) and the explosion information faced by companies, institutions or organizations that are stored for many years. This situation is also faced in several universities that stores various kinds of data, especially new admissions database. But the abundant data has not been widely used in digging the information or knowledge that can help university management in making strategic plans. Every year there are new students who retire that do not register,therefore, it takes an application that can process a lot of data to find out the possible retirement for new students. To find out the prediction retirement prospective students, this paper uses C.45 algorithm. The method can change the a very large fact into a decision tree that represents the rule. The result of this research is that the application can classify the new students in tree structure in order that it can produce a rule. This application is able to predict the possibility of the retirement of new student. With this application, it  is expected that the possibility of a prospective student will retire from college can be known at an early stage, so the management can make a decision easily. Development of this application built uses PHP as the interface application system and MySql in database processing. System development methodology used is the waterfall model
Evaluating Readiness and Acceptance of Artificial Intelligence Adoption Among Elementary School Teachers Darmawan, Erlan; Rahman, Titik Khawa Abdul; Thamrin, Nani Ronsani
JOIN (Jurnal Online Informatika) Vol 9 No 2 (2024)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v9i2.1385

Abstract

Artificial Intelligence (AI) is a computer system that mimics the human brain's ability to process information and make decisions. AI technology is used to learn patterns in data and make predictions or decisions based on that learning. Despite the potential benefits of AI in education, elementary school teachers face significant challenges in adopting AI technology due to limited training, lack of resources, and resistance to change. This research aims to identify the factors influencing the adoption of AI technology among primary school teachers in West Java, Indonesia. The study involved 384 participants and employed a quantitative approach. Specific factors influencing AI adoption were identified by developing a model for AI-based teaching and learning and assessing readiness factors. The results identified optimism, innovativeness, insecurity, discomfort, perceived validity, trust, usefulness, and ease of use as critical factors for successful AI adoption among primary school teachers in West Java. The customized adoption model provides a practical roadmap for integrating AI into teaching and learning processes, addressing regional specificities while remaining relevant to similar educational challenges worldwide. The assessment of readiness factors offers actionable insights for fostering a supportive environment for technology integration. The study concludes with recommendations for future research and implications for educators, administrators, and policymakers.
C4.5 Algorithm Application for Prediction of Self Candidate New Students in Higher Education Darmawan, Erlan
JOIN (Jurnal Online Informatika) Vol 3 No 1 (2018)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v3i1.171

Abstract

Data mining has a background with the condition of an abundance of data (the overload data) and the explosion of information faced by companies, institutions, or organizations that have been stored for many years. This situation is also faced in several universities that store various kinds of data, especially new admissions databases. However, the abundant data has not been widely used in digging the information or knowledge that can help university management in making strategic plans. Every year there are new students who retire and do not register, therefore, it takes an application that can process a lot of data to find out the possible retirement for new students. To find out the prediction of retirement prospective students, this paper uses C.45 algorithm. The method can change the very large fact into a decision tree that represents the rule. The result of this research is the application can classify the new students in a tree structure in order that it can produce a rule. This application is able to predict the possibility of the retirement of the new student. With this application, it is expected that the possibility of a prospective student retiring from college can be known at an early stage, so the management can make a decision easily. Development of this application uses PHP as the interface application system and MySql in-database processing. The system development methodology uses the waterfall model
Co-Authors Ade Nanang khozin Akhmad Izzudin Amin Alfiani Azzahra Alviani Azzahra Aminati, Lina Andri Ramdoni Anto Lospiyanto Dadan Nugraha Dede Irawan Erik Kurniadi Fadia Nur Fazriah Fahmi Yusuf Feri Friatna Galih Agustian Nurdaya Harun Al-Rasyid Herawati, Resma Mega Herma Wiharno Heru Budianto Jerry Dounald Rahajaan Koko Risnanto Lingga Adiputra Mia Maulianingsih Mia Maulianingsih Mochamad Widya Nurahman Muhamad Yunus Muhsin Muhsin Nita Mirantika Nita, Gita Sri Nunu Nugraha Nurfatimah, Siti Nuke Nuriman Nuriman, Nuriman Oktaviani, Evy Setia Rahman, Titik Khawa Abdul Ridwan Alamsyah Rika Septian Riki Aripani Rina Risnawati RIO ANDRIYAT KRISDIAWAN Rio Priantama Sri Rahayu Suseno, Endra Suwarto, Gentur Priguna Thamrin, Nani Ronsani Toni Khalimi Toto Supartono Untari, Dini Yasir Maulana Yayan Suryana Yeye Fajriani Yulyanto Yulyanto