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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Teknik Hidro AGREGAT Jurnal Ilmiah Ecosystem Bandar: Journal of Civil Engineering Jurnal Algoritma, Logika dan Komputasi Buletin Sistem Informasi dan Teknologi Islam Jurnal Informatika Progres Kohesi: Jurnal Sains dan Teknologi Jurnal INFOTEL ARUS JURNAL SAINS DAN TEKNOLOGI Cosmic Jurnal Teknik Journal of Green Complex Engineering Journal of Muhammadiyah’s Application Technology Journal Techno Entrepreneur Acta
Muhammad Syafaat S. Kuba
Universitas Muhammmadiyah Makassar
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Social Sciences Transportation Other

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IMPLEMENTASI SISTEM DETEKSI PRODUK BOIKOT BERBASIS WEBSITE REAL-TIME MENGGUNAKAN METODE YOLOv10 Ahmad Nur Rahman; Emil Agusalim Habi Talib; Fahrim Irhamna Rachman; Rizki Yusliana Bakti; Muhammad Faisal; Muhammad Syafaat S.Kuba
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

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Abstract

Manual identification ofboycott products remains a challenge for the public due to limited access to information and the complexity of brand affiliations. This study aims to develop a real-time, website-based boycott product detection system using the You Only Look Once version 10 (YOLOv10) algorithm. The dataset consists of images of food and beverage product packaging collected from various online sources, annotated using the bounding box method, and classified into five categories. The model was trained and tested using separate test data, while performance evaluation was conducted using a confusion matrix with precision, recall, and f1-score metrics. In addition, functional testing of the system was performed using the Black Box Testing method. The result indicate that the YOLOv10 model is capable of detecting boycott product with good performance and can be effectively integrated into a real-time web-based system. The proposed system is expected to assist users in identifying boycott products more quickly and accurately.
KLASIFIKASI TANAMAN OBAT TRADISIONAL BERBASIS CITRA BUAH DAN DAUN Nurul Kusumawardani; Chyquitha Danuputri; Darniati; Muhammad Faisal; Muhyiddin A.M Hayat; Muhammad Syafaat S.Kuba; Desi Anggreani
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

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Abstract

Indonesia is a megabiodiversity country with extensive use of traditional medicinal plants; however, plant identification in natural environments remains largely manual and error-prone. Recent advances in deep learning, particularly Vision Transformer (ViT), provide a promising solution by effectively capturing global spatial features for image classification. This study applies a ViT-Base/16 model to automatically classify fruit and leaf images of Indonesian medicinal plants. The dataset comprises 1,000 field-collected images from Galung Village, West Sulawesi, covering 20 classes (10 medicinal and 10 non-medicinal plants). The model was fine-tuned using the AdamW optimizer with a learning rate of 2×10⁻⁵ and trained for 30 epochs with cosine annealing. The proposed approach achieved high performance, with 99.33% accuracy, 99.41% precision, 99.33% recall, and a 99.33% F1-score, while binary classification between medicinal and non-medicinal plants reached 100% accuracy. The system was deployed as a Flask-based web application, demonstrating reliable functionality and practical response times. Overall, the results confirm the effectiveness of Vision Transformer for medicinal plant classification under natural conditions and highlight its potential to support digital documentation, education, and the preservation of local ethnobotanical knowledge.
PENERAPAN MODEL ESRGAN UNTUK UPSCALING CITRA DAN VIDEO DIGITAL Syahrul Suhardi; Emil Agusalim Habi Talib; Fahrim Irhamna Rachman; Titin Wahyuni; Muhammad Faisal; Muhammad Syafaat S.Kuba
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

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Low-resolution images and videos remain a common problem in various digital applications due to limited visual quality. Conventional interpolation-based upscaling methods often produce blurry results and lead to the loss of important texture details. This study aims to apply the Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) to improve the resolution of digital images and videos. The dataset used consists of low-resolution images and videos that are processed through preprocessing, model training, and testing stages using the Google Colab environment. The ESRGAN model is trained to generate high-resolution images while preserving visual details and structural information. Model performance is evaluated using the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and visual comparison between images before and after the upscaling process. The results show that ESRGAN significantly improves the quality of images and videos compared to conventional interpolation methods, both quantitatively and qualitatively. Therefore, the application of ESRGAN is considered effective for enhancing the resolution of digital images and videos and can be utilized in applications that require high visual quality.
MONITORING DAN NOTIFIKASI REAL-TIME PERUBAHAN FILE PADA WEB SERVER MENGGUNAKAN WATCHDOG DAN TELEGRAM BOT SEBAGAI SISTEM PERINGATAN DINI Syahrul Hasbir; Emil Agusalim Habi Talib; Fahrim Irhamna Rachman; Titin Wahyuni; Muhammad Faisal; Muhammad Syafaat S.Kuba
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

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Abstract

Web servers are critical infrastructures for delivering digital services and are highly vulnerable to unauthorized file changes that may threaten system security and service availability. However, many conventional monitoring systems still rely on periodic checking mechanisms, which often fail to provide timely detection of security incidents. This study aims to design and implement a real-time file change monitoring system on a web server using the Watchdog library and a Telegram Bot as an early warning mechanism. The research adopts an applied research method with an experimental approach. The system is developed using the Python programming language and evaluated in a local XAMPP-based web server environment, with the uploads directory selected as the monitoring target. Experimental results demonstrate that the proposed system is capable of detecting various file change events, including file creation, deletion, content modification, and file renaming, in real time without event loss. Notifications delivered via the Telegram Bot provide clear, timely, and actionable information to administrators. These findings indicate that the proposed event-driven monitoring system is effective and efficient in enhancing web server security and improving incident response capabilities.
Co-Authors . Darniati Abdul Rakhim Nanda Ade Irfan Agus, Fauziah Agusalim, Agusalim Ahmad Nur Rahman Ahmad Syafi'i Zulmi Akbar, Syahril Akrar Syah Al Imran, Hamzah Ali, Muhammad Yunus Amal, Citra Amalia AMRI, MUH ULIL Amrullah Anas, Andi Bunga Tongeng Andi Bunga Tongeng Anas ANDI MAWADDA TAIBA MAWADDA TAIBA Andi Rahmat Anis Dandi Juandani Antaria, Sukmasari Arman, Muayyanah Arsyad, Zulfikar Asnita Virlayani, Asnita Bakti, Rizki Yusliana Berni Satria Gemilang Chyquitha Danuputri Danuputri, Chyquitha Danuputri, Chyquitha Darniati Dayang Aisyah Desi Anggreani Djunur, Lutfi Hair Emil Agus Salim Habi Talib Emil Agusalim H. T Emil Agusalim H. T Fachrim Irhamna Rachman Faeruddin, Muhammad Asygar Fahrim I. Rahman Fausiah Latief Fauzan Hamdi Fithriyah Arief Wangsa Gaffar, Farida Gemilang, Berni Satria Hamzah Al Imran Hasanuddin, Novianingsih Hasbir, Syahrul Irma Suryana Irwan Irwan, Muhammad Ahlil Khairi Juandani, Anis Dandi Juliandro, Juliandro Karim, Nenny Kasmawati Kato, Muh Alvin Achmad Kusumawardani, Nurul Lantara, Andi Bintang Latief, Fausiah Lisnawati Lisnawati LUKMAN ANAS Lukman Lukman Lukman, Lukman Lutfi Hair Djunur M Agusalim Ma'rupah, Ma'rupah Mahmud, Rajib Mahmuddin Mahmuddin Mahmuddin Mohamad Munawir Muh Alvin Achmad Kato Muh Ilham Akbar Muhammad Aminuddin, Muhammad Muhammad Faisal Muhammad Hasraddin Hasnan Muhyiddin A.M Hayat Mujidah, Jihan Izzathul Munawir, Mohamad Nenny Nenny Nenny Nenny, Nenny Nini Apriani Rumata Nur Alam Nur Rahman, Ahmad Nurdiansah, Nurdiansah Nurdiansyah Nurdiansyah Nurnawaty Nurul Kusumawardani Panguriseng, Darwis Pawara, Ismail Putri, Adriani Rahmasari, St. Rajib Mahmud Risman, Andi Muh. Riswal Karamma Riswal Karamma Rizky Yusliana Bakti Sahril Sandi, Andi Muhammad Sari, Reski Anugrah Sarina Siba, Ikhsan Suhardi, Syahrul Suriani Suriani Swa Lee Lee Syadiah Nor Wan Shamsuddin Syah, Akrar Syahrul Hasbir Syahrul Suhardi Syahrul, Syahrulrahman Syamsuri, Andi Makbul Syamsuri, Andi Maqbul Syarifuddin, Nur Annisa T Karim, Nenny Taufiq, Muh Titik Khawa Abd Rahman Titik Khawa Abdul Rahman Titin Wahyuni Toha Andi Lala Try Gustaf Said Usman, Sucipto Wangsa, Fithriyah Arief Zulfikar Arsyad Zulhaidir DJ, Muhammad Zulmi, Ahmad Syafi'i