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All Journal Techno.Com: Jurnal Teknologi Informasi PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic RADIAL : Jurnal Peradaban Sains, Rekayasa dan Teknologi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Journal of Students‘ Research in Computer Science (JSRCS) AMMA : Jurnal Pengabdian Masyarakat Journal Of Computer Science Contributions (JUCOSCO)
RAFIKA SARI
Informatika, Fakultas Ilmu Komputer, Universitas Bhayangkara Jakarta Raya
Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Social Sciences

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Journal : PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic

 1 
Team-Teaching-Based Course Scheduling Using Genetic Algorithm Rafika Sari; Khairunnisa Fadhilla Ramdhania; Rakhmat Purnomo
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol 10 No 1 (2022): March 2022
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v10i1.4416

Abstract

Scheduling problems occur in various fields, e.g., education, health institutions, transportation, sports, etc. Main scheduling problems in education is course scheduling which creates schedules for students and lecturers. In this study, course scheduling allocates the lecturers in the form of team teaching and courses into the class and a certain time to even out the workload of lecturers per day and a group of students per day in one week without breaking the constraint. The method used in this research is a genetic algorithm where Universitas Bhayangkara Jakarta Raya as the case study. The genetic algorithm process is done by getting several candidate solutions that undergo a process of selection, mutation, and crossing over to produce chromosomes with the best fitness values. The objective function in this research is minimizing the average variance of the workload of lecturers and students per day in one week. The parameters used in genetic algorithm are determined based on the Design of Experiments mechanism (DOE). The optimal parameter values ​​used to run the program are as: population size = 50, with probability of crossing over = 0.4 and probability of mutation = 0.008. The results of scheduling with genetic algorithms show that the value of the workload variance lecturers and students by considering team teaching is better than actual scheduling. The application of the genetic algorithm method results in a decrease in the standard value deviation of the workload of lecturers and a group of students in one week is 0.114 (3.68%) and 3.11 (55.7%). In addition, course scheduling uses a genetic algorithm with consider team teaching better than genetic algorithm without considering team teaching because there is no class schedule that clashes in real conditions.
Decision Support System Design for Informatics Student Final Projects Using C4.5 Algorithm Rafika Sari; Hasan Fatoni; Khairunnisa Fadhilla Ramdhania
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol 11 No 1 (2023): March 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i1.5954

Abstract

Academic consultation activities between students and academic supervisors are necessary to help students carry out academic activities. Based on the transcript of grades obtained, many students do not choose the appropriate final project/thesis specialization fields based on their academic abilities, resulting in a lot of inconsistencies between the course grades and the final project specialization fields. The purpose of this research is to minimize the subjectivity aspect of students in choosing their final project academic supervisors and minimize the inconsistencies between the course grades and the final project specialization fields. The method used in this research is classification data mining using the Decision Tree and C4.5 Algorithm methods, with the attributes involved being courses, course grades, and specialization courses. The C4.5 Decision Tree algorithm is used to transform data (tables) into a tree model and then convert the tree model into rules. The implementation of the C4.5 Decision Tree algorithm in the specialization field decision support system has been successfully carried out, with an accuracy rate of 70% from the total calculation data. The data used in this research is a sample data from several senior students in the Informatics program at Ubhara-Jaya. The results of the research decision support system can be used as a good recommendation for the Informatics program and senior students to direct their final project research. It is expected that further research will use more sample data so that the accuracy rate will be better and can be implemented in website or mobile-based applications.
Co-Authors Abrar Hiswara Aida Fitriyani Aida Fitriyani Aida Fitriyani, Aida Ajif Yunizar Pratama Yusuf Akmal Najib Alif Septiyanto Andy Achmad Hendharsetiawan Bayu Dwimas Nuansyah Citra Urba Ningrum Diah Angraina Fitri Diah Angraina Fitri Dinda Dwi Puspita Adjar Dwi Adi Setiawan Endang Retnoningsih Fani Khoirotunnisa Fata Nidaul Khasanah Fata Nidaul Khasanah Fillah Akhyar Rezqi Adesta Fisca Ardi Prasetiawati Hasan Fatoni Herlawati Herlawati Ibni Khoerul Umam Illa Nur’aini Imam Aji Pranoto Ira Wikartika Joniwarta, Joniwarta Julian Firman Danu Khairunnisa Fadhilla Ramdhania Kurniasari Kurniasari Kusdarnowo Kusdarnowo Lisa Adhani Maulana Rifqi Pratama Muhammad Faris Muhammad Ganang Martyana Muhammad Rafi Muzakki Muzaid Ahtian Nurul Azizah Prabandari, Rosiana Disiati Prima Dina Atika Purnomo, Rakhmat Raditia Muhammad Ardan Rahmadya Trias Handayanto Rakhmi Khalida Ratna Sari Ratna Sari Reghita Suryani Putri Renilda Filiandini Rosiana Disiati Prabandari Safarin Novarizal Seta Samsiana Simon Wardian Siti Setiawati Steven Arrow Rinel Sibarani Subarkah Subarkah Sugeng Murdowo Sugiyatno Sugiyatno Sunu Febrian Eko Saputro Susilawati Susilawati Syifa Rahmadhani Tyathanesia Dianfitri As-Sanaj Yoga Saputra