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Jurnal Informatika: Jurnal Pengembangan IT
Published by Politeknik Harapan Bersama Tegal
ISSN : 24775126     EISSN : 25489356     DOI : https://doi.org/10.30591
Core Subject : Science,
Computer Science & IT
The scope encompasses the Informatics Engineering, Computer Engineering and information Systems., but not limited to, the following scope: 1. Information Systems Information management e-Government E-business and e-Commerce Spatial Information Systems Geographical Information Systems IT Governance and Audits IT Service Management IT Project Management Information System Development Research Methods of Information Systems Software Quality Assurance 2. Computer Engineering Intelligent Systems Network Protocol and Management Robotic Computer Security Information Security and Privacy Information Forensics Network Security Protection Systems 3. Informatics Engineering Software Engineering Soft Computing Data Mining Information Retrieval Multimedia Technology Mobile Computing Artificial Intelligence Games Programming Computer Vision Image Processing, Embedded System Augmented/ Virtual Reality Image Processing Speech Recognition
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 24 Documents
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Search results for , issue "Vol 10, No 1 (2025)" : 24 Documents clear
Klasifikasi Pengucapan Huruf Hijaiyah Berbasis Android Menggunakan CNN dengan Fitur Mel-Spectrogram Muqsith, Fawwaz Ijlal; Supriyati, Endang; Listyorini, Tri
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.8145

Abstract

Mastery of Hijaiyah letters is a fundamental basis in learning the Qur'an, but data from the IIQ Community Service Institute 2021/2022 shows that 72.25% of the 3,111 Muslims tested have not been able to read the Qur'an properly. This research aims to develop an Android-based Hijaiyah letter pronunciation classification system using Convolutional Neural Network (CNN) with mel-spectrogram features. The research methodology includes collecting 8,904 voice samples from 53 participants at Pondok Tahfidz Yanbu'ul Qur'an Menawan, preprocessing data using MFCC techniques, developing CNN models, and implementing the system in the form of mobile applications with MVVM architecture. The test results showed promising performance with some classes achieving 100% accuracy and an average overall accuracy of 83.80%, although there were challenges in some classes such as “alif_dommah” and “ghaiin_dommah” which had an accuracy below 40%. The developed system successfully provides an interactive learning platform through the integration of mobile applications with the Flask API, but still requires further development, especially in expanding the dataset to overcome overfitting problems and improve the generalization ability of the model.
Analysis of Information Security Management System Implementation at BSN Arianty, Kiki Puspo
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.8211

Abstract

SNI ISO/IEC 27001:2013, adopted by the National Standardization Agency of Indonesia (BSN), is a national standard derived from the international ISO/IEC 27001 published by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). This study evaluates the effectiveness of BSN's Information Security Management System (ISMS) implementation, focusing on compliance with international standards, risk management strategies, and organizational commitment to safeguarding information. Employing qualitative descriptive methods, data were collected through interviews, document analysis, and observations. The findings highlight the critical roles of leadership commitment, comprehensive risk assessments, and regular system evaluations in achieving ISMS objectives. Despite significant achievements, including obtaining Integrated Management System certification in 2023, challenges persist in optimizing resources and adapting to emerging security threats. Recommendations include enhancing staff capabilities, investing in advanced technologies, and transitioning to the updated SNI ISO/IEC 27001:2022 standard. This study reinforces the importance of ISMS in protecting sensitive information, fostering trust, and aligning with global best practices.
Optimasi Bobot Kelas LSTM untuk Deteksi URL Phishing pada Dataset Tidak Berimbang Handoyo, Tri Ferli; Putra, Muhammad Pajar Kharisma
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.8128

Abstract

Phishing URL detection is one of the main challenges in cybersecurity, considering the ever-increasing threats affecting internet users globally. This research aims to develop a Long Short-Term Memory (LSTM) based deep learning model to detect phishing URLs with high accuracy. The dataset used consists of 651,191 URLs, which are divided into four categories: benign, defacement, phishing, and malware. The dataset is processed through preprocessing stages, including URL cleaning and feature extraction. The LSTM model is applied with optimized hyperparameter configurations to learn patterns from the dataset. The results showed that the model was able to achieve significant accuracy during the training and validation process. Evaluation on external datasets shows that the model performs well in the benign and defacement categories, with relatively high precision and recall. However, challenges were identified in the malware and phishing categories, where recall was low due to dataset imbalance and lack of feature representation. Further analysis showed a model bias towards the majority class, as well as difficulty in detecting URLs in the minority class. This research shows the potential of using LSTM-based deep learning in phishing URL detection, but also emphasizes the importance of further optimization, such as adjusting class weights, oversampling, or using additional features. It is hoped that the resulting model can be an initial solution in improving cyber security, especially in detecting phishing threats in real-time.
Analysis of Electronic Wallet User Sentiment on Twitter (x) Social Media Using the Naïve Bayes Classifier Algorithm basir, azhar
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.8180

Abstract

 Electronic wallets are one of the most popular payment methods in Indonesia with the number of users increasing significantly in recent years, including DANA, GoPay, and LinkAja. Along with the increasing number of users, the need to analyze user opinions and comments on social media, especially on Twitter (X) is also increasing. This study uses an experimental method with data collection from Twitter (X) using data crawling techniques. The dataset used is 1,500 data with 1 attribute. This study aims to analyze user sentiment towards electronic wallets using the Naive Bayes Classifier algorithm with the Python programming language. The results of the study showed that DANA had a negative sentiment of 16.6%, a neutral sentiment of 9.0%, and a positive sentiment of 74.4%. Followed by GoPay with a negative sentiment of 9.4%, a neutral sentiment of 11.4%, and a positive sentiment of 79.2%. Meanwhile, LinkAja had the lowest negative sentiment of 8%, with a neutral sentiment of 12.2% and a positive sentiment of 79.8%. The implementation of the Naive Bayes Classifier algorithm achieved an accuracy rate of 72% for DANA, 88% for GoPay, and 88%, for LinkAja.
Analisis Sentimen Pembangunan IKN pada Media Sosial X Menggunakan Algoritma SVM, Logistic Regression dan Naïve Bayes Hadi, Nur; Sugiarto, Dedy
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.7106

Abstract

social media X or formerly more familiar with Twitter is one of the familiar social media and has many users in the world whis is a platform for accesing some information and commenting both suggestions and criticsm related to the development of the Capital City of the Archipelago (IKN) which is the center of smart government in East Kalimantan. There are indormation, suggestions and criticisms addressed to the @ikn_id account directly addressed to the Indonesia government as well as public opinions related to IKN by using the IKN hashtag. Public sentiment on the issue is in the form of text on IKN Development. This research aims to analyze public opinion on the government's decision to build the Capital City of Nusatara (IKN) conveyed through X social media using appropriate data analysis methods by comparing the performance of support vector machine, logistic regression, and naïve bayes algorithms and identifying the most effective algorithm in sentiment analysis. The method used in this research to analyze sentiment are support vector machine, logistic regression and naïve bayes. The use of these three algorithms is also to compare the accuracy that is better than other algorithms. The results obtained using the Support Vector Machine algorithm is 80% while using the Logistic Regression and naïve bayes algorithms are 79%.
Perancangan Visualisasi Elektronik Pencegahan Jantung Koroner Berbasis Teknologi Augmented Reality Adrian, Qadhli Jafar; Styawati, Styawati; Prastowo, Agung Tri; Kuswara, Muhammad Shidiq; Anggita, Rizki Devi
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.8137

Abstract

Augmented reality (AR) merupakan teknologi yang memungkinkan benda maya yang dimasukan secara real time di dalam dunia nyata. Teknologi augmented reality sangat menarik dan mudah untuk diterapkan dan digunakan bagi penggunanya. Pemanfaatan teknologi augmented reality pada saat ini telah meluas ke berbagai aspek termasuk kesehatan. Di dunia kesehatan, penyakit jantung koroner masih menjadi ancaman di Indonesia bahkan di dunia. Penyakit jantung koroner adalah gangguan fungsi jantung, akibat otot jantung kekurangan nutrisi dan oksigen karena adanya penyempitan pada pembuluh darah koroner, namun masyarakat masih sering menilai bahwa penyakit jantung merupakan penyakit yang dapat sembuh dengan sekali pengobatan. Maka di butuhkan suatu media informasi yang kuat, yang dapat meningkatkan pengetahuan masyarakat mengenai penyakit jantung khususnya penyakit jantung koroner karena penyakit jantung jenis ini yang paling populer di masyarakat. Penelitian ini bertujuan untuk mengembangkan sebuah aplikasi berbasis augmented reality (AR) pada platform Android yang dapat digunakan sebagai media visualisasi penyakit jantung, khususnya penyakit jantung coroner. Hal ini untuk meningkatkan pengetahuan masyarakat mengenai penyakit jantung khususnya penyakit jantung coroner. Dalam membangun aplikasi ini, metode yang digunakan adalah metode Multimedia Development Life Cycle (MDLC). Dari hasil pengujian yang dilakukan dengan metode Alpha dan Beta, dapat disimpulkan bahwa aplikasi ini dinilai layak untuk digunakan sebagai media edukasi interaktif tentang penyakit jantung koroner, hal ini dibuktikan dengan hasil pengujian beta test yang telah dilakukan dan menghasilkan nilai rata-rata tingkat persetujuan usability aplikasi secara keseluruhan sebesar 89,3 %.
Implementasi Website K-Etik untuk Digitalisasi Manajemen Etik Penelitian di Universitas YARSI Putra, Rio Griya; Herlyansyah, Hafidz Putra; Windriyani, Paramaresthi; RS, Qomariah
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.8055

Abstract

The K-Etik Website was developed by Universitas YARSI as a solution to inefficiencies in research ethics management, which had previously been conducted manually, often leading to delays, inefficiencies, and a lack of transparency. This study aims to create a digital application capable of accelerating the review process and enhancing transparency in the management of ethics documents. The Scrum methodology was applied to facilitate collaboration between developers and users, integrating modern technologies such as React.js for the user interface, Node.js for the server, and MongoDB for database management. The application evaluation was conducted through black-box testing, indicating that the application meets the specified requirements, including user authentication, document submission workflows, and real-time progress tracking. System Usability Scale (SUS) testing yielded an average score of 81.1, classified as “Excellent,” signifying the application's high usability and readiness to support ethics management in research. Through digitalization via the K-Etik application, research ethics management at Universitas YARSI has become more efficient and transparent, strengthening accountability and responsiveness in the ethics document review process. The study concludes that this application provides a comprehensive digital platform to support a structured and accountable research environment at Universitas YARSI.
Sistem Pengelompokan Jenis Sampah Rumah Tangga untuk Optimalisasi Pengolahan Ishlakhuddin, Fauzan; Muhamad, Fachrul Pralienka Bani; Ismantohadi, Eka
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.8173

Abstract

The increasing volume of household waste in Indonesia has raised the need for efficient waste management solutions. This study developed an Internet of Things (IoT)-based waste classification system aimed at optimizing waste processing. The system integrates digital scales, ESP32 microcontrollers, and cloud-based servers to collect, monitor, and manage waste data in real-time. Using the Prototype Software Development Life Cycle (SDLC) method, the system was designed, implemented, and evaluated iteratively to meet user needs effectively. The system allows users to input waste type, verifies the data with a PIN, and transmits it to a server for centralized management. Testing results demonstrated high accuracy in weight measurements, consistency between devices, and seamless data integration into the system. The IoT-based system not only reduces operational workload but also supports efficient recycling by categorizing waste with economic value. Further research is recommended to expand the system's application to larger communities and explore its integration into broader waste management platforms.
Peningkatan Keberagaman Data untuk Klasifikasi Penyakit Diabetes Berbasis Stacking Ensemble Learning majid, nur kholis; Supriyanto, Catur; Marjuni, Aris
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.7375

Abstract

Diabetes cases are becoming more common in the late years. Diabetes attacks not only parents, but also children. The development of diabetes is not far from the lifestyle and diet that we live on a daily basis. Therefore, early detection of diabetes is essential because the earlier the disease is detected, the easier it is to treat. In the process of detecting disease based on factors, the cause can be predicted with data mining. The aim of this research is to increase data diversity so that it can be processed to the maximum in data mining. In the process of data upgrading, we used the imbalance learning method SMOTE-ENN combined with the method Stacking Ensemble Learning. In the search for a powerful stacking model, seven classification algorithms were involved in the experiments carried out on this study, namely: Random Forest, Decision Tree, Gradient Boosting, Naïve Bayes, Extreme Gradiant Boost, Logistic Regression, and k-Nearest Neighbor. Four algorithms were used to be classifiers level 0 (base model), namely kNN, Gradient Boosting, decision tree, and random forest, while Random Forest was used again to be classifier level 1. (meta model). With these combinations, the accuracy obtained is 97.3%. These are the highest results when compared to individual algorithms.
Model Perilaku Pasien Pada Aplikasi Berbasis Kesehatan Menggunakan Metode Design Thinking Adrian, Qodhli Jafar; Styawati, Styawati; Rifai, Jefri Andri
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.8138

Abstract

The COVID-19 pandemic has had a significant impact on health, economy, and society in Indonesia. In dealing with the pandemic, the term New Normal emerged, namely a change in behavior to continue normal activities by implementing health protocols. One of the innovations that has developed in this digital era is a health-based application designed to increase the accessibility of health services, such as online consultations, health monitoring, medication reminders, and health education. However, the success of this application depends not only on technology, but also on a deep understanding of patient behavior as users. Understanding patient needs, preferences, and challenges is important to create an optimal user experience. Without this, health applications are at risk of not being widely adopted. This study uses the Design Thinking method to understand patient behavior and design relevant solutions. With stages such as empathy, problem definition, ideation, prototyping, and testing, this study aims to design a patient behavior model in health-based applications. This approach is expected to provide a comprehensive picture of the factors that influence patient behavior, as well as help developers create applications that are more intuitive, effective, and in accordance with user needs in the era of the pandemic and new habits.

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