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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Media Infotama MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Syntax Jurnal Informatika Indonesian Journal of Artificial Intelligence and Data Mining JMM (Jurnal Masyarakat Mandiri) SINTECH (Science and Information Technology) Journal Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Sistem Informasi Kaputama (JSIK) Majalah Ilmiah Kaputama Journal of Information Systems and Informatics Jurnal Sistem Informasi dan Informatika (SIMIKA) JISA (Jurnal Informatika dan Sains) International Journal of Advances in Data and Information Systems Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurnal Pengabdian Masyarakat Nusantara Journal of Artificial Intelligence and Engineering Applications (JAIEA) IT For Society : Journal of Information Technology Journal of Comprehensive Science Eduvest - Journal of Universal Studies Jurnal Hasil Penelitian dan Pengembangan (JHPP) Journal of Data Science, Technology, and Artificial Intelligence
Fahmi, Hasanul
Unknown Affiliation
Aerospace Engineering Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Neuroscience Social Sciences Transportation Other

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Research and Implementation of University Student Union Management System Driven by Informatization and Automation FUYU, FUYU; GUFANG, GUFANG; Fahmi, Hasanul
IT for Society Vol 9, No 2 (2024)
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/itfs.v9i2.5742

Abstract

Taking this paper makes a detailed analysis and research on the student workflow based on SSM. First, from the point of view of software engineering, combined with the characteristics of software systems, software engineering analysis and design. Then, based on the introduction of SSM architecture, combined with Java technology and related development tools, the system implementation process is described in detail. Experimental results show that the system has high efficiency and quality. Firstly, the requirements of the system are analyzed, and the main functions and implementation process are determined. On this basis, the overall structure of the system is proposed, and the functions of each module are divided and processed. Then, the database management system based on MySQL is applied to backstage database, and the system is programmed by IDEA development tool. After the system design is completed, the system is tested in detail. The experiment proves that the system can realize the automation and management of students' working process effectively.
Design And Build Web-Base Application Library Management System Tengfei, Li; Jie, Zhang; Fahmi, Hasanul
IT for Society Vol 9, No 2 (2024)
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/itfs.v9i2.5743

Abstract

At present, most of China's higher education institutions have completed the computerization of library management, and library management is more scientific and efficient. However, many university library management systems have some problems, such as outdated functions, aging systems and unstable operation. In this paper, the authors designed a library management system. Under the Javaweb environment, the whole system is built using SpringMVC framework, MySQL database as the data storage support of the system, Windows 10 as the operating system, and Tomcat 8.0 as the web server. With the help of this technology stack, the problem of unstable operation of the previous system is solved, and a more efficient and stable library management information system is constructed, which not only reduces the workload of librarians, but also provides students with a more convenient book borrowing and lending experience, so that the library can play the most useful role in the campus life.
BISINDO (Bahasa Isyarat Indonesia) Sign Language Recognition Using Deep Learning Setiawan, Ricky; Yunita, Yustina; Rahman, Fajri Fathur; Fahmi, Hasanul
IT for Society Vol 9, No 1 (2024): Vol 9, No 1
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/itfs.v9i1.5076

Abstract

Sign language recognition plays a crucial role infacilitating communication for individuals with hearingimpairments. This paper presents a deep learning-basedapproach for recognizing Bahasa Isyarat Indonesia (BISINDO),the sign language used in Indonesia. The proposed systememploys convolutional neural networks (CNNs) and recurrentneural networks (RNNs) to automatically extract features fromsign language gestures and classify them into correspondinglinguistic units. The dataset used for training and evaluationconsists of annotated BISINDO sign language videos.Preprocessing techniques such as normalization andaugmentation are applied to enhance the robustness of themodel. Experimental results demonstrate the effectiveness of theproposed approach in accurately recognizing BISINDO signlanguage gestures, achieving state-of-the-art performancecompared to existing methods. The developed system showspromising potential for real-world applications in enhancingcommunication accessibility for the hearing-impairedcommunity in Indonesia.
Tomato Pest and Disease Identification Based on Improved Deep Residual Network and Transfer Learning Linli, Peng; Sen, Tjong Wan; Fahmi, Hasanul; Roestam, Rusdianto
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 1 (2025): March 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i1.34038

Abstract

Tomatoes are a vital global crop, but their yield can be severely impacted by various diseases like leaf mold and spotted wilt. Early and accurate diagnosis of these diseases is crucial for implementing timely treatments, thereby reducing crop loss. Traditional manual diagnosis often suffers from low accuracy, high costs, and time consumption. To address these issues, this study introduces a method for identifying tomato pests and diseases using an improved residual network and transfer learning. A dataset comprising images of seven common tomato diseases and healthy leaves was created. This study introduces an improved residual network and transfer learning method to accurately identify tomato pests and diseases. The enhanced ResNet50 model, with an attention mechanism and focal loss, achieved 98.10% recognition accuracy. This research not only facilitates early disease detection, reducing crop loss but also minimizes pesticide use, thereby enhancing environmental sustainability and agricultural productivity worldwide.
Deblurring Photos with Lucy-Richardson and Wiener Filter Algorithm in RGBA Color Rustam, Michiavelly; Brotokuncoro, Agung; Utomo, Wiranto Herry; Fahmi, Hasanul
Jurnal Media Infotama Vol 21 No 1 (2025): April 2025
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v21i1.6709

Abstract

Photographers and social media influencers encounter challenges with hand tremors during photo capture, leading to unintended blurriness in their posts, reducing visual impact and audience engagement. To mitigate this problem, the authors aim to effectively reduce the blurring caused by instability in handling, producing sharper and noise-free photos. The methodology involves implementing the Lucy-Richardson and Wiener Filter algorithms into a Python-based web application optimized for RGBA photo processing. Data requirements include sample photos affected by hand tremors to validate the efficacy of the solution. The outcome successfully eliminates blur in captured photos affected by hand tremors in RGBA color format.
Meningkatkan Pemahaman Siswa SMA Don Bosco 3 Cikarang Mengenai Internet Sehat, Gamifikasi Dan Pergaulan Lawan Jenis di Era Digital Rosalina, Rosalina; Sahuri, Genta; Mandala, Rila; Fahmi, Hasanul
Jurnal Pengabdian Masyarakat Nusantara (JPMN) Vol. 3 No. 2 (2023): Agustus 2023 - Januari 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v3i2.1679

Abstract

In today's digital age, high school students have to survive a dynamic and interconnected online environment. Promoting responsible digital citizenship and cultivating pleasant contacts, particularly those with the opposite sex, is critical as kids develop both intellectually and socially. The goal of this activity is to: (1) educate high school students about the responsible and ethical use of the internet, emphasizing the importance of online safety, privacy, and respect for others; (2) encourage students to develop healthy internet usage habits by providing them with the knowledge and tools to navigate the digital world responsibly; and (3) use gamification principles to engage and motivate high school students to adopt responsible online behavior. The activity was held at SMA Don Bosco 3 Cikarang and was attended by students as well as teachers.
Feature Importance and Binary Classification using PyCaret Naswir, Ahmad Fadhil; Williem; Hasanul Fahmi
Journal of Data Science, Technology, and Artificial Intelligence Vol. 1 No. 1 (2024): July 2024
Publisher : CV. ADMITECH SOLUTIONS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63703/ditech.v1i1.16

Abstract

The rapid advancement of machine learning (ML) techniques has facilitated the development of robust models for various classification tasks. This study explores the application of PyCaret, an open-source, low-code machine learning library, to perform feature importance analysis and binary classification using the Titanic dataset from Kaggle. The dataset underwent preprocessing to convert categorical features into numerical values and to remove irrelevant columns. Multiple classification models were compared, with the Gradient Boosting Classifier achieving the highest performance, marked by an average accuracy of 81.52%. Detailed evaluation metrics, including precision, recall, F1 score, and AUC, further validated the model's effectiveness. Feature importance analysis identified gender (sex), fare, and age as the most significant predictors of survival, aligning with historical accounts. The results demonstrate PyCaret's capability to streamline the ML workflow, providing valuable insights and enabling rapid experimentation. This study highlights the potential of binary classification and feature importance analysis in handling large-scale datasets, where the identified important features can serve as a baseline for implementing advanced algorithms such as deep learning.
Artificial intelligence multilingual image-to-speech for accessibility and text recognition Rosalina, Rosalina; Fahmi, Hasanul; Sahuri, Genta
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i3.pp1743-1751

Abstract

The primary challenge for visually impaired and illiterate individuals is accessing and understanding visual content, which hinders their ability to navigate environments and engage with text-based information. This research addresses this problem by implementing an artificial intelligence (AI)-powered multilingual image-to-speech technology that converts text from images into audio descriptions. The system combines optical character recognition (OCR) and text-to-speech (TTS) synthesis, using natural language processing (NLP) and digital signal processing (DSP) to generate spoken outputs in various languages. Tested for accuracy, the system demonstrated high precision, recall, and an average accuracy rate of 0.976, proving its effectiveness in real-world applications. This technology enhances accessibility, significantly improving the quality of life for visually impaired individuals and offering scalable solutions for illiterate populations. The results also provide insights for refining OCR accuracy and expanding multilingual support.
Advancing Internet Cafe Operations and Customer Engagement through the "Game Station" Website Saptona, Albert; Fahmi, Hasanul
IT for Society Vol 10, No 1 (2025)
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/itfs.v10i1.6221

Abstract

The Application of ANN Predicts Students' Understanding of Subjects During Online Learning Using the Backpropagation Algorithm at SMAN 1 Perbaungan rendiarno, rendiarno; Fahmi, Hasanul
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 3 (2022): June 2022
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (534.212 KB) | DOI: 10.59934/jaiea.v1i3.87

Abstract

This study is a study to predict the level of students' understanding of the subjects given by educators at SMAN 1 Perbaungan. This study aims to determine how far the level of understanding of students in understanding lessons, especially during the current covid-19 pandemic, which is a process of teaching and learning activities carried out from their respective homes or using online learning media. The method used is an artificial neural network with Backpropagation algorithm with variables used are knowledge values, skill scores, mid-semester exam results, end-semester exam results, and attitude scores. The five variables are used to support predicting the level of student understanding of the subject using the single layer Backpropagation Algorithm. The architectural model used is 5-2-1 with a success accuracy of 85%. The smaller the error value that is close to 0, the smaller the deviation of the results of the Artificial Neural Network with the desired target.
Co-Authors Ahmad Zaki Fadilla Rangkuti Alifah, Nurli Aprilio, Pajri Arifiandy, Rony Aulia, Afina Nisa Ayu, Desita Puspita BROTOKUNCORO, AGUNG Cexarian, Hafizh ChungKiat, Ong Daniel Happy Putra Felix, Michael FUYU, FUYU Gerhard T, Jonathan Girsang, Rame R GUFANG, GUFANG harianja, turiami Hariyanto, Dian Tri Hastuti, Rani Puji Herry Utomo, Wiranto Lianzhai, Duan Linli, Peng murdani, toynbe Naswir, Ahmad Fadhil natanael, anju mastaurat niar, iinvera Nugraha, Putu Surya Nurul Putri Utami Prabu Wardono Pratama, Andreyanto Pratama, Jaka Yudhi Rahman, Fajri Fathur rendiarno, rendiarno Ricky Setiawan Rila Mandala Rimanti, Dewinda Rosalina Rosalina Rusdianto Roestam Rustam, Michiavelly Sahuri, Genta Sahuri Saptona, Albert Septian Fakhrudin Arianto Siahaan, R. Fanry Sihombing, Darvin Markus Simangunsong, Agustina Simanjorang, R. Mahdalena Sinaga, Anita Sindar RM Sitohang, Rirido Apriyanto sofyan, mhd heri Sulindawaty Tengfei, Li Tjong Wan Sen turnip, hendra nicodemus Wahyuni, Elda Wika Wahyuni Williem Williem, Williem Wiranto Herry Utomo Yunita, Yustina Zhang Jie