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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI) Education, Language, and Culture Journal Teknovokasi : Jurnal Pengabdian Masyarakat Journal of Embedded Systems, Security and Intelligent Systems Abdi Samulang : Jurnal Pengabdian Kepada Masyarakat Media Elektrik
Andi Alviadi Nur Risal
Universitas Megarezky
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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Evaluasi Estimasi Biaya Perangkat Lunak melalui Ekstraksi Katalog Dari Dokumen Spesifikasi Kebutuhan luqman fanani mz; Andi Ikmal Rachman; Suriansyah B; Gita Pratiwi; Agus Halid; Alviadi Nur Risal
Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI) Vol 7 No 1 (2024): Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Lamappapoleonro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57093/jisti.v7i1.198

Abstract

Software cost estimation is an important early stage in the software development cycle. This process requires careful analysis of the project, taking into account various factors that affect cost and time to completion such as errors in the initial identification of what kind of software will be built and its utilization. One of the main challenges in budgeting is the lack of clear reference prices, which often results in the use of historical data as the basis for calculations. This research proposes a combination of methods to improve the accuracy and reliability of cost estimation, including text summarization and word2vec for sentence analysis and weighting, and catalog extraction to identify SRS documents as system features, including ambiguity features. The goal is to provide a more effective tool for future software project budgeting, ensuring cost estimation that matches the complexity of the project and proper assignment of experts. With this method, it is expected that companies can reduce the risk of miscalculation and inappropriate assignment of experts, thereby avoiding financial losses and project delays.
Balanced clustering for student admission school zoning by parameter tuning of constrained k-means Zainuddin, Zahir; Nur Risal, Andi Alviadi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp2301-2313

Abstract

The Indonesian government issued a regulation through the Ministry of Education and Culture, number 51 of 2018, which contains zoning rules to improve the quality of education in school educational institutions. This research aims to compare the performance of the k-means algorithm with the constrained k-means algorithm to model the zoning of each school area based on the shortest distance parameter between the school location and the domicile of prospective students. The study used data from 2,248 prospective students and 22 public school locations. The results of testing the k-means algorithm in grouping showed the formation of non-circular patterns in the cluster membership with different numbers of centroid cluster members. In contrast, testing the constrained k-means algorithm showed balanced outcomes in cluster membership with a membership value of 103 for each school as the cluster center. The research findings state that the developed constrained k-means algorithm solves the problem of unbalanced data clustering and overlapping issues in the process of new student admissions. In other words, the constrained k-means algorithm can be a reference for the government in making decisions on new student admissions.
Implementasi K-Means Clustering Untuk Rekomendasi Kelas Unggulan di SMK 1 Teknologi dan Rekayasa Mimika Risal, Andi Akram Nur; Desy Maryani; Nur Fadillah; Andi Alviadi Nur Risal
Journal of Embedded Systems, Security and Intelligent Systems Vol 5, No 3 (2024): November 2024
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v5i3.5446

Abstract

New student admission is a strategic step for schools to ensure the quality of education and optimal resource management. This research aims to analyse new student candidate data at SMK Negeri 1 Teknologi dan Rekayasa Mimika using the K-Means clustering method. Student data is grouped into three clusters based on academic grades to detect prospective students who have the potential to enter superior classes. The analysis results show that cluster 3 has the highest average academic score, making it possible for students in cluster 3 to enter the general superior class. cluster 2 showed excellence in certain aspects, particularly E grades, making it suitable for specific programmes oriented towards talent development. Finally, cluster 1 has the lowest average score and requires further assistance to improve academic performance. Evaluating the cluster results using Silhouette Score, all three clusters are in the "Good" category (0.51-0.70), with the highest score in cluster 3 (0.594). The recommendation from this study is to prioritise students from Cluster 3 for general superior classes and some from cluster 2 for special superior programs, so as to support the vision of SMK Negeri 1 Technology and Engineering Mimika in improving the quality of data-based education.
ECONOMIC ANALYSIS OF POWER PLANT USING UNIT COMMITMENT SCHEDULING Ratih Puspita Siwi; Ayu Annisa Akbar; Lista Litta; Andi Alviadi Nur Risal
Jurnal Media Elektrik Vol. 21 No. 3 (2024): MEDIA ELEKTRIK
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/metrik.v21i3.3277

Abstract

Unit commitment is the scheduling of disconnected generation of generating units in an electric power system within a certain period, with the aim of meeting load demand. This scheduling is usually determined based on human load demand which always changes over time. This research aims to determine the production costs of thermal plants using the Second Order Gradient method to obtain economical operating costs, to determine fuel costs based on plant loading, and to determine the most economical scheduling using unit commitment. This is to determine the most optimal on/off schedule for generating units to be operated to meet the estimated load to achieve minimum fuel costs in rupiah.
Pelatihan Teknik Parafrase dalam Penulisan Ilmiah Berbasis Artificial Intelligence Risal, Andi Alviadi Nur; Indargairi; Risal, Andi Akram Nur; Rivai, Andi Tenri Ola; Firman , Risman
TEKNOVOKASI : Jurnal Pengabdian Masyarakat Volume 3: Issue 1 (January 2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/teknovokasi.v3i1.6819

Abstract

This Community Service Program (PkM) is designed to enhance understanding and skills in paraphrasing techniques for academic writing by utilizing Artificial Intelligence (AI). Proficiency in paraphrasing is a crucial aspect for academics and researchers in producing original scholarly works and avoiding plagiarism. Therefore, this training aims to equip participants with paraphrasing techniques that align with academic standards while introducing various AI-based tools that can improve the quality of academic writing.The implementation of this program is divided into four main stages: preparation, execution, monitoring, and evaluation. The methods employed include theoretical material delivery, demonstrations of AI applications in paraphrasing, hands-on practice, and interactive discussion sessions. The evaluation results indicate an improvement in participants' understanding of paraphrasing techniques and the effectiveness of AI utilization in this process. Furthermore, the majority of participants acknowledged that AI-assisted paraphrasing accelerated and refined their outputs.This training has demonstrated a positive impact on the development of academic writing skills. To optimize future implementations, it is necessary to develop a more comprehensive program, including extending the training duration, providing interactive modules, and offering continuous mentoring to ensure the effective application of paraphrasing techniques.
Pemanfaatan Teknologi dalam Penulisan Parafrase Tulisan Ilmiah Runi, Runimeirati; Fadilah, Nur; Risal, Andi Alviadi Nur
TEKNOVOKASI : Jurnal Pengabdian Masyarakat Volume 3: Issue 1 (January 2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/teknovokasi.v3i1.6820

Abstract

Technological advances have had a significant impact on various aspects of research and scientific writing, including the paraphrasing process. Paraphrasing is an important technique in academics to convey information from other sources in a different language without changing the original meaning. Artificial intelligence (AI) and natural language processing (NLP)-based technologies have introduced various automatic paraphrasing tools that help writers improve originality and avoid plagiarism. This article discusses various types of paraphrasing technology, their benefits in academia, and the challenges faced in their use. The results of the study show that the use of paraphrasing technology can improve efficiency and accuracy in scientific writing, but still requires human evaluation to ensure academic quality and integrity. With the right use of technology, paraphrasing in scientific writing can be more effective and ethical.
Development of a Learning Model Using Practical Unit Modules for Electrical Installation at SMK Negeri 3 Makassar Siwi, Ratih Puspita Siwi; Risal, Andi Alviadi Nur
JURNAL PENDIDIKAN BAHASA DAN BUDAYA Vol 5 No 1 (2025): April (EDULEC)
Publisher : CV. Eureka Murakabi Abadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56314/edulec.v5i1.307

Abstract

Module is one of the teaching materials that can be used by students, either independently or with the assistance of a teacher. Therefore, it is important to develop modules so that they can function optimally as effective learning guides for students. The objective of this study was to develop a practical learning module for electrical installation. The research employed the Research and Development (R&D) method. The stages of the research included: (1) identifying potentials and problems, (2) data collection, (3) product design, (4) product validation, (5) product revision, (6) product testing, (7) further revision, and (8) analysis and reporting. The research design used was Pretest-Posttest Control Group Design. Based on the validity aspects, the results of the development of the practical module for electrical installation are as follows: (1) practical module 1 obtained a score of 85.86% and was categorized as valid; (2) practical module 2 obtained a score of 87.75% and was categorized as valid; and (3) practical module 3 obtained a score of 86.31% and was categorized as highly valid. Student learning activities using the practical electrical installation module were significantly higher compared to students who used worksheets (LKS). Learning outcomes in the cognitive, affective, and psychomotor domains of students who used the practical module were significantly higher than those who used worksheets, with a significance value of 0.001.
Python for Data Visualization: Pengembangan Soft Skill Literasi Data Mahasiswa Universitas Megarezky Risal, Andi Alviadi Nur; Arifin, Dafrid Cahyadi; Utama, Muh Ilham Budi; Amir, Nurdzakirah
ABDI SAMULANG: Jurnal Pengabdian Kepada Masyarakat Vol 4 No 2 (2025): JULI| ABDI SAMULANG
Publisher : Yayasan Habiburrahman Jamalu Bina Ummat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61477/abdisamulang.v4i2.63

Abstract

This Community Service Activity aims to improve the data literacy and visualization skills of students of the Information Systems Study Program at Megarezky University through Python for Data Visualization training: Developing Soft Skills for Data Literacy of Megarezky University Students. The training was carried out in the form of an interactive workshop based on direct practice, including the use of Pandas, Matplotlib, and Seaborn. The results of the pre-test and post-test showed an increase in technical understanding of 38%, with 82% of participants being able to apply Python syntax independently. In addition, mini projects arranged in groups showed the development of soft skills, such as critical thinking, teamwork, and visual communication. As many as 100% of groups compiled data narratives logically and communicatively. The output of the activity in the form of project reports and infographics can be used as portfolios and teaching materials. The final questionnaire showed that 96% of participants assessed the application training and expressed interest in taking further training. This activity is a strategy to strengthen students' data competencies based on practice. Keywords: Python, data visualization, data exploration, students, soft skills
Co-Authors Agus Halid Amir, Nurdzakirah Andi Akram Nur Risal Andi Ikmal Rachman Arifin, Dafrid Cahyadi Ayu Annisa Akbar Desy Maryani Firman, Risman Gita Pratiwi Litta, Lista Luqman Fanani Mz NUR FADILAH NUR FADILLAH Ratih Puspita Siwi Rivai, Andi Tenri Ola Runi, Runimeirati Suriansyah B Utama, Muh Ilham Budi Zahir Zainuddin