Article Per Year (5 Year)
p-Index From 2020 - 2025
0.92
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Nusantara Hasana Journal Indonesian Community Journal
Nasir Usman
STMIK Profesional Makassar, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
Pelatihan pemanfaatan chatGPT untuk efektivitas belajar dan penyelesaian tugas akademis siswa-siswi di SMK Muhammadiyah 3 Makassar Andi Harmin; Dikwan Moeis; Nasir Usman
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 8, No 1 (2024): March
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v8i1.22216

Abstract

AbstrakSalah satu cabang teknologi yang semakin populer adalah kecerdasan buatan atau Artificial Intelligence (AI), yang tak hanya menjadi bagian integral dalam kehidupan sehari-hari tetapi juga membawa manfaat signifikan dalam dunia pendidikan. Efisiensi dan produktivitas dalam proses belajar meningkat, sedangkan pengembangan kemampuan siswa/i menjadi lebih terfokus. AI menjadi katalisator dalam menciptakan generasi yang siap menghadapi tantangan masa depan. Salah satu teknologi AI yang banyak dimanfaatkan dalam dunia pendidikan saat ini adalah keberadaan ChatGPT. ChatGPT singkatan dari "Chat Generative Pre-trained Transformer" merupakan model kecerdasan buatan yang dikembangkan oleh OpenAI, dirancang untuk memahami dan menghasilkan teks dengan cara yang menyerupai interaksi manusia. Dengan memahami cara menggunakan ChatGPT dan menerapkan teknologi kecerdasan buatan, dapat meningkatkan minat belajar generasi muda, menjadikan ini sebagai sarana pembelajaran yang efektif, dan memberikan kemudahan bagi mereka dalam mendapatkan informasi. Kegiatan pengabdian kepada masyarakat ini dilaksanakan pada hari Selasa tanggal 14 November 2023 melalui penyelenggaraan pelatihan yang ditargetkan kepada siswa/i Sekolah Menengah Kejuruan Muhammadiyah 3 Makassar. Pelatihan ini bertujuan untuk mendukung proses belajar siswa/i, meningkatkan efektivitas belajar dan kemampuan mengerjakan tugas-tugas akademis mereka. Metode yang digunakan meliputi penyampaian materi, sesi tanya jawab, dan kegiatan praktikum. Hasil dari pelatihan menunjukkan bahwa penggunaan ChatGPT memberikan manfaat yang signifikan bagi siswa/i. ChatGPT memiliki kemampuan yang baik dalam menjawab pertanyaan, merangkum dokumen, menerjemahkan teks, dan memahami kode program. Tanggapan siswa/i setelah pelatihan juga sangat positif terhadap pemanfaatan ChatGPT dalam proses pembelajaran, hal ini terlihat melalui kuesioner yang dibagikan setelah pelatihan, sebagian besar siswa/i (lebih dari 70%) dari total 22 peserta pelatihan menilai bahwa pelatihan yang diberikan sangat bermanfaat, mudah dipahami dan menambah pengetahuan. Oleh karena itu, dapat disimpulkan bahwa ChatGPT efektif dalam memenuhi kebutuhan pembelajaran siswa/i di SMK Muhammadiyah 3 Makassar. Kata kunci: chatgpt; artificial intelligence; pengabdian masyarakat; pelatihan. AbstractOne branch of technology that is increasingly popular is artificial intelligence (AI), which is not only an integral part of everyday life but also brings significant benefits in the world of education. Efficiency and productivity in the learning process increase, while the development of students' abilities becomes more focused. AI is a catalyst in creating a generation that is ready to face the challenges of tomorrow. One of the AI technologies that is widely used in the world of education today is the existence of ChatGPT. ChatGPT stands for "Chat Generative Pre-trained Transformer" is an artificial intelligence model developed by OpenAI, designed to understand and generate text in a way that resembles human interaction. By understanding how to use ChatGPT and applying artificial intelligence technology, it can increase the interest in learning of the younger generation, make this an effective learning tool, and make it easier for them to get information. This community service activity will be carried out on Tuesday, November 14, 2023 through targeted training for students of Muhammadiyah 3 Makassar Vocational High School. This training aims to support students' learning process, improve learning effectiveness and the ability to do their academic tasks. The methods used include material delivery, question and answer sessions, and practicum activities. The results of the training showed that using ChatGPT provided significant benefits for students. ChatGPT has a good ability to answer questions, summarize documents, translate text, and understand program code. Student responses after training were also very positive towards the use of ChatGPT in the learning process, this can be seen through questionnaires distributed after training, most students (more than 70%) from a total of 22 trainees rated that the training provided was very useful, easy to understand and increased knowledge. Therefore, it can be concluded that ChatGPT is effective in meeting the learning needs of students at SMK Muhammadiyah 3 Makassar. Keywords: chatgpt; artificial intelligence; community service; training.
Microsoft Copilot Training for Monitoring Student Learning: A Case Study Vocational High School Makassar - Indonesia Dikwan Moeis; Nasir Usman; Muhammad Faisal; Andi Harmin; Ida Mulyadi; Musdalifa Thamrin
I-Com: Indonesian Community Journal Vol 4 No 3 (2024): I-Com: Indonesian Community Journal (September 2024)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/icom.v4i3.5134

Abstract

Artificial intelligence (AI) has become an increasingly popular technology and brings significant educational benefits. This technology increases the learning process's efficiency and productivity, allowing for the development of students' abilities in a more focused manner. AI is a catalyst in preparing generations to face future challenges. One example of AI's application in education is Microsoft Copilot, an artificial intelligence model developed by Microsoft in collaboration with OpenAI. Microsoft Copilot is designed to understand and support various academic tasks through human-like interactions. Training on using Microsoft Copilot was carried out for students of SMKS Wahyu Makassar. This training aims to support the learning process, increase learning effectiveness, and assist students in doing academic assignments. The evaluation results showed that Microsoft Copilot provided significant benefits, with positive feedback from participants. Most students found this training useful, easy to understand and improved their knowledge.
COMPARISON OF THE PERFORMANCE OF REGRESSION-SPECIFIC AND MULTI-PURPOSE ALGORITHMS Usman, Nasir; Darniati, Darniati; Rosnani, Rosnani; Musdalifa Thamrin; Nurahmad, Nurahmad; Nurdiansyah, Nurdiansyah; Faisal, Muhammad
Nusantara Hasana Journal Vol. 4 No. 8 (2025): Nusantara Hasana Journal, January 2025
Publisher : Yayasan Nusantara Hasana Berdikari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59003/nhj.v4i8.1274

Abstract

Regression is a data science method for evaluating the relationship between independent and dependent variables. This study compares the performance of various regression algorithms using the Boston Housing Dataset, which consists of 506 samples divided into 80% for training and 20% for testing. Performance evaluation was conducted using metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and the Coefficient of Determination (R²). All algorithms were implemented with default hyperparameter settings provided by the Scikit-learn library to ensure fair comparison. The results showed that versatile algorithms, particularly Gradient Boosting Machines (GBM) and Random Forest, achieved the best performance with R² values of 0.92 and 0.89, respectively, and lower errors. Conversely, regression-specific algorithms, such as Linear Regression and Ridge Regression, recorded R² values of approximately 0.67, while the k-Nearest Neighbors algorithm had the lowest performance with an R² of 0.65. Versatile algorithms proved to be more effective for datasets with complex non-linear patterns, while regression-specific algorithms were better suited for linear data patterns. These findings provide guidance for practitioners in selecting algorithms based on data characteristics and analysis objectives.
Utilization of Artificial Intelligence to Support Technology Development at PT. Aplikanusa Lintasarta – Makassar Faisal, Muhammad; Usman, Nasir; Mulyadi, Ida; Rosnani, Rosnani; Darniati, Darniati; Thamrin, Musdalifa; Mardiah, Mardiah; Watratan, Alvina Felicia
I-Com: Indonesian Community Journal Vol 5 No 2 (2025): I-Com: Indonesian Community Journal (Juni 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/icom.v5i2.6945

Abstract

This community service activity aimed to enhance the understanding of Machine Learning (ML) and Deep Learning (DL) technologies among employees of PT. Aplikanusa Lintasarta, as an academic contribution to supporting the company’s digital transformation acceleration. Conducted in a hybrid format (offline and online) on April 21, 2025, the program featured expert speakers and employed an interactive outreach approach combined with applicable case studies. To assess its effectiveness, pre-test and post-test instruments were utilized, revealing an average increase of 45% in participants’ comprehension. Participants' responses were highly positive, as demonstrated by their enthusiasm during discussions and interest in implementing ML/DL within the workplace. This activity not only strengthened internal technological literacy but also supported the development of the national AI ecosystem, in alignment with the launch of GPU Merdeka by Lintasarta.
Machine learning for global trade analysis: a hybrid clustering approach using DBSCAN, elbow, and SOM Thamrin, Musdalifa; Mulyadi, Ida; Made Widia, I Dewa; Faisal, Muhammad; Hi Baharuddin, Suardi; Prihatmono, Medy Wismu; Nurdiansyah, Nurdiansyah; Usman, Nasir
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i4.pp3033-3046

Abstract

Global trade constitutes a highly complex and interdependent system influenced by diverse economic, geographic, and political factors. This study proposes a hybrid clustering framework that integrates density-based spatial clustering of applications with noise (DBSCAN), elbow, and self-organizing maps (SOM) methods to uncover latent structures in international trade patterns. Utilizing averaged trade data from 25 countries spanning the period from 2013 to 2023, the framework identifies distinct clusters based on export-import characteristics. The DBSCAN is employed to detect dense trade hubs and outlier behaviors, the elbow method determines the optimal number of clusters, and SOM facilitates the visualization of non-linear, high-dimensional trade relationships. The analysis reveals three prominent trade clusters: Global Trade Leaders, Emerging Trade Powers, and Niche Exporters, each reflecting varying degrees of trade diversification and dependency. These empirical findings align with established economic theories, including the Heckscher Ohlin model and dependency theory, and provide actionable insights for policymakers seeking to enhance trade competitiveness and regional integration strategies.
Co-Authors Alvina Felicia Watratan Andi Harmin Darniati Darniati Dikwan Moeis Hi Baharuddin, Suardi Ida Mulyadi Ida Mulyadi, Ida Made Widia, I Dewa Medy Wisnu Prihatmono Muhammad Faisal Mulyadi, Ida Musdalifa Thamrin Musdalifa Thamrin Nurdiansyah Nurdiansyah Rosnani Rosnani Rosnani Rosnani