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All Journal Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Jurnal INSYPRO (Information System and Processing) Ainet : Jurnal Informatika Madaniya Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Informatika Progres Jurnal Intelek Dan Cendikiawan Nusantara ARUS JURNAL SAINS DAN TEKNOLOGI Journal of Muhammadiyah’s Application Technology
Fachrim Irhamna Rachman
Universitas Muhammadiyah Makassar
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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PENERAPAN MODEL ESRGAN UNTUK UPSCALING CITRA DAN VIDEO DIGITAL Suhardi, Syahrul; Habi Talib, Emil Agusalim; Rachman, Fahrim Irhamna; Wahyuni, Titin; Faisal, Muhammad; S.Kuba, Muhammad Syafaat
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v18i1.539

Abstract

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 Hasbir, Syahrul; Habi Talib, Emil Agusalim; Rachman, Fahrim Irhamna; Wahyuni, Titin; Faisal, Muhammad; S.Kuba, Muhammad Syafaat
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v18i1.540

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.
Klasifikasi Status Gizi Balita Menggunakan Algoritma Light Gradient Boosting Machine di Puskesmas Balibo Auliyah, Afifah; Chyquithadanuputri; Rachman, Fahrim Irhamna; Aras, Dara Ugi
Arus Jurnal Sains dan Teknologi Vol 4 No 1: April (2026)
Publisher : Arden Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57250/ajst.v4i1.2591

Abstract

Status gizi balita merupakan indikator penting dalam menentukan tingkat kesehatan dan perkembangan anak. Penentuan status gizi secara konvensional sering kali membutuhkan waktu yang lama dan berpotensi menimbulkan kesalahan dalam proses identifikasi. Penelitian ini bertujuan untuk mengklasifikasikan status gizi balita menggunakan algoritma Light Gradient Boosting Machine (LightGBM) sebagai pendekatan machine learning yang cepat dan akurat. Dataset yang digunakan berasal dari Puskesmas Balibo dengan jumlah data sebanyak 860 data balita yang mencakup variabel umur, jenis kelamin, tinggi badan, berat badan, BMI, indikator BB/U, dan TB/U. Tahapan penelitian meliputi pengumpulan data, preprocessing data, pembagian data latih dan data uji, pelatihan model LightGBM, serta evaluasi performa model menggunakan confusion matrix, accuracy, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa algoritma LightGBM mampu menghasilkan performa klasifikasi yang baik dengan tingkat akurasi mencapai 94%. Model ini mampu mengidentifikasi kategori status gizi balita secara efektif dan efisien sehingga dapat membantu tenaga kesehatan dalam mendukung deteksi dini masalah gizi pada balita.
Co-Authors Adrianingsih, Rizka Ahmad Faisal ANDIKA SAPUTRA Aras, Dara Ugi ardi24, ardiansyah_01 Aritmawijaya, Suandi Auliyah, Afifah Bakti, Rizki Yusliana Budi Setiawan Chyquitha, Chyquitha Danu Putri Chyquithadanuputri Dika, Andika Saputra Emil Agusalim Habi Talib Ferdiansyah H, chalidah_azzahra00 Hasbir, Syahrul Hermanto, Chalidah Azzahrah Indriani, Lis Iskandar, Aryansyah Kamal, Safutri Kotte, Erick Yusuf La Ode Taufik Ismail La Ode Taufik Ismail LUKMAN ANAS Lukman Lukman Muhammad Faisal Muhyiddin A.M Hayat Mujadilah, Siti Mustakim Mustakim Nur Alam Nur Rahman, Ahmad Nur, Makmur Jaya Reski Awalia S. Kuba, Muhammad Syafa'at Salam, Abd Setiawan, Tommy Reynaldy Sri Hastati suandi_17, suandi_aritmawijaya Suhardi, Syahrul Tahir, Gempar Perkasa Titin Wahyuni Uddin , Ardiansyah Virgiawan, David Arian Wibawa. Ar, Arya Yanti, Wilda