Article Per Year (5 Year)
p-Index From 2020 - 2025
0.562
P-Index
This Author published in this journals
All Journal Indonesian Journal of Artificial Intelligence and Data Mining JTAM (Jurnal Teori dan Aplikasi Matematika) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan
Fadilah, Alif Nur
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Pelatihan penggunaan classpoint sebagai media pembelajaran interaktif guru di Smk Negeri Kebasen Ikhsan, Ali Nur; Kuncoro, Adam Prayogo; Iftinani, Alifah Dafa; Fadilah, Alif Nur
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 8, No 4 (2024): December
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v8i4.27056

Abstract

Abstrak Pelatihan Penggunaan ClassPoint sebagai Media Pembelajaran Interaktif Guru di SMK Negeri Kebasen bertujuan untuk meningkatkan keterampilan pengajaran dan pembelajaran guru dalam mengintegrasikan teknologi modern ke dalam ruang kelas. Dalam kegiatan ini, dilakukan workshop yang berfokus pada pengenalan dan penerapan ClassPoint sebagai alat pembelajaran interaktif. Metode workshop melibatkan sesi presentasi, demonstrasi praktis, dan diskusi interaktif untuk memberikan pemahaman yang mendalam tentang potensi serta penggunaan efektif ClassPoint dalam menyampaikan materi pelajaran. Hasil pelatihan ini dapat memberikan wawasan baru bagi guru-guru SMK Negeri Kebasen dalam memanfaatkan teknologi pendidikan untuk menciptakan lingkungan pembelajaran yang lebih dinamis dan menarik bagi siswa Kata kunci: pelatihan; pengabdian masyarakat; video pembelajaran; classpoint. Abstract The Training on Using ClassPoint as an Interactive Learning Tool for Teachers at Kebasen State Vocational School aims to enhance teachers' skills in integrating modern technology into the classroom. This training includes a workshop focused on the introduction and application of ClassPoint as an interactive learning tool. The workshop involves presentation sessions, practical demonstrations, and interactive discussions to provide a comprehensive understanding of the potential and effective use of ClassPoint in delivering lesson material. The outcome of this training is expected to provide new insights for Kebasen State Vocational School teachers, enabling them to utilize educational technology to create a more dynamic and engaging learning environment for students. Keywords: training; community service; learning videos; classpoint.
A Comparison of Welch Powell Algorithm and Greedy Algorithm in Odd Semester Lecture Room Scheduling Optimization Faculty of Computer Science Fadilah, Alif Nur; Subarkah, Pungkas; Pramudya, Reyvaldo Shiva; Syabani, Amin
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 4 (2024): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i4.23142

Abstract

Scheduling is a systematic method to optimize work time, and avoid failure when problems occur. Scheduling is widely applied in the world of education, one of which is in preparing course schedules. Scheduling itself needs to be optimized to ensure a smooth lecture process without any problems between courses. As happened at the Faculty of Computer Science, Amikom Purwokerto University, where in the preparation of the schedule there is no information about lecture rooms. Therefore, the author compiled a lecture hall scheduling optimization journal by comparing the performance between the Welch Powell Algorithm and the Greedy Algorithm as optimization and graph coloring on the lecture hall schedule.The data used in this study are 88 courses spread across 3 study programs, namely Informatics Study Program, Information Systems Study Program, and Informatics Engineering Study Program. This research uses a comparative method on graph vertex coloring, where execution time as duration, lines as algorithm complexity, and manual algorithm calculation as parameters. Based on the research that has been done, the results of 14 full spectrum colors are obtained which are then applied to 23 lecture rooms that can be used without clashes at the Faculty of Computer Science. This can minimize the possibility of overlapping room usage between courses. In addition to comparing the performance of the Welch-Powell Algorithm and the Greedy Algorithm to produce optimal scheduling of lecture rooms, this research can also optimize the schedule of lecturers when entering class to optimize students to be more organized in entering lecture classes at the Faculty of Computer Science, Amikom Purwokerto University.
Performance Comparison of Decision Tree J48, CART, and Naïve Bayes Algorithms for Predicting Chronic Kidney Disease Ikhsan, Ali Nur; Fadilah, Alif Nur; Iftinani, Alifah Dafa
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 1 (2024): March 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i1.26472

Abstract

Chronic Kidney Disease could be a worldwide issue that proceeds to extend with high treatment costs. Accurate diagnosis is essential for managing this disease. There is a requirement for a technique to anticipate chronic kidney disease, with prevalent use being made of Decision Tree J48, Naive Bayes, and CART algorithms which offer benefits like swift computation, ease of use, and high precision. The researchers aimed to determine the comparison results of Decision Tree J48, CART, and Naive Bayes algorithms for predicting chronic kidney disease. From the research findings, it was concluded that the CART algorithm had the highest accuracy rate of 97.25% in predicting chronic kidney disease, compared to the J48 Decision Tree algorithm and the Naïve Bayes algorithm with accuracy rates of 96.5% and 93.5% respectively. The CART algorithm can be utilized by pathologists to develop a program for predicting chronic kidney disease.
Co-Authors Adam Prayogo Kuncoro Iftinani, Alifah Dafa Ikhsan, Ali Nur Pramudya, Reyvaldo Shiva Subarkah, Pungkas Syabani, Amin