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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 431 Documents
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Identifikasi Hukum Tajwid pada Citra Teks Al Quran menggunakan SSD MobileNet v2 Kurniawardhani, Arrie; Fathurrahman, Ihya
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i3.7713

Abstract

Tajweed contains a set of rules for reciting the Qur'an correctly. These rules must be complied with to ensure each letter is pronounced accurately. Arabic script and language compose the Qur'an, yet not all readers are fluent in Arabic. Tajweed serves as a guide to prevent readers from making mistakes when reciting the Qur'an that could alter the meaning. However, Tajweed rules are quite numerous and diverse, causing readers to struggle in memorizing these rules. To address this issue, a preliminary development of a Quran reading assistance system will be established, focusing on detecting Tajweed rules in images of Quranic text. SSD MobileNet v2, a Deep Learning technique for object detection, will be utilized for detecting Tajweed rules. The development of the Tajweed rule identification model begins with the data collection stage by capturing screens of the Al-Quran text pages from the Kemenag Qur'an Application. A total of 520 collected data were divided into 80:10:10 for training, validation, and test data, respectively. All data were subsequently annotated and enclosed in bounding boxes using the tool labelImg. The pre-trained model, SSD MobileNet V2 FPNLite 320x320, was used as the initial weight configuration of the model. Then the identification model was constructed during the training stage using training and validation data. The reliability of the constructed model was tested using test data. The test results indicated that the model could successfully recognize two Tajwid rules, Mad Aridlisukun and Mad Layyin, achieving the minimum loss around 0.15 and the maximum precision around 0.96.
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.
Perancangan Model Deteksi Potensi Siswa Putus Sekolah Menggunakan Metode Logistic Regression Dan Decision Tree Ermillian, Ade; Nugroho, Kristiawan
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i3.8007

Abstract

The phenomenon of student dropouts is one of the main challenges in education, influenced by various factors such as absenteeism, economic pressures on families, low academic performance, and lack of motivation. This issue not only affects the personal development of students but also tarnishes the reputation of educational institutions. Therefore, an innovative technology-based approach, such as data mining, is needed to detect students at risk of dropping out early. This study aims to design a model for detecting the potential of school dropout students using Logistic Regression and Decision Tree methods based on student data from SMA N 4 Tegal. The variables used in the analysis include demographic, academic, and social information such as absenteeism, average semester grades, parental income, and transportation type. The dataset is processed using one-hot encoding and label encoding techniques to convert categorical data into numeric values. The results indicate that both methods have their respective advantages. The Decision Tree model achieves high precision, especially in predicting students who continue their education, with a precision of 0.99 for the "Continue School" class. However, recall for the "Dropout" class remains low (0.60), indicating the need for improvements in detecting students at risk of dropping out. On the other hand, the Logistic Regression model shows better balance in detecting both classes, with more balanced accuracy and recall. This study concludes that both models can be used to monitor the potential of school dropouts and provide data-driven recommendations for more accurate educational decision-making.
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.
Analisis Spam Komentar Instagram menggunakan Support Vector Machine dengan Variasi Hyperparameter Haqimi, Nur Azizul; Roshinta, Trisna Ari
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Instagram (IG) is a web and mobile-based social media application where users can share photos or videos with the available features. These features include captions, tagging, adding locations where photos or videos were taken, editing and filtering photos or videos before they are uploaded from the smartphone application and certain tags so that the photos can be seen by many people. Instagram as social media is not only a medium for communication but also for developing brands and selling products. Spam that often appears in spam comments is a barrier to getting appropriate information. When identifying spam and non-spam comments, a challenging problem is that the number of spam comments is less than non-spam comments, thus causing an imbalanced dataset problem. Imbalanced data sets can affect the performance of classification algorithms. Support Vector Machine (SVM) to classify comments between two classes (spam or nonspam) which is the maximum distance between the hyperplane and the closest item from both classes. Analysis of related research that has been carried out with feature variations states that the addition of 90 different features to the data used to increase classification accuracy on imbalanced data.  Other related research discusses Complementary Naïve Bayes which can be used to balance dataset classes. This research describes the selection of Support Vector Machine hyperparameters, especially for unbalanced data where the level of similarity is almost the same, so hyperparameter experiments are needed for the best accuracy
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.
Teknologi Computer Vision untuk melakukan Deteksi dan Penentuan Kualitas Bibit Ayam Day Old Chicks Syaddam, Syaddam; Soeksin, Sasando Dewi; Nizar, Raihan
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i3.7923

Abstract

This research is motivated by the importance of chicken animal protein for child growth, development, immunity, intelligence, and the prevention of stunting. This research aims to design and implement an object detection system using a series of 4 nodes, namely Raspberry Pi, ESP32-CAM, Arduino, and ESP32, to identify chickens based on their physical characteristics. This research utilizes computer vision and artificial intelligence methodology, particularly the Convolutional Neural Network approach, to detect characteristics of DOC chickens, such as feathers, eyes, and legs. The implementation results show that the object detection system built using these four nodes can detect objects according to the existing labels. This system can identify DOC chickens with characteristics such as clean feathers, bright eyes, and bright and undamaged legs. Testing was conducted under various movement conditions of the detection objects, and the results show that the system can work well in recognizing the target objects. In the trial section, the objects used were chickens that fit the DOC characteristic category. The trial results show that the built object detection system can detect DOC chickens with suitable physical characteristics. This can assist farmers in selecting and cultivating quality chickens. Five trial tests were conducted, which showed varying detection performance.
Analisis Sentimen Twitter Terhadap Pemindahan Ibu Kota Negara Menggunakan Support Vector Machine Saputri, Gita Aprinda; Alita, Debby
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i3.6612

Abstract

The Indonesian government announced plans to move the capital from Jakarta to East Kalimantan due to the high population burden and economic contribution on the island of Java. Statistical data shows that the island of Java has a large population, reaching 151.59 million people or around 56.10% of the total population of Indonesia, and will provide a large participation in national GDP in 2021. Moving the capital city is seen as a step. . for the sake of equal distribution of population and economy throughout Indonesia. Rapid urbanization on the island of Java, especially in the buffer areas of the capital city of Jakarta, is one of the main reasons behind this decision. This research uses data from the social media platform Twitter to analyze sentiment using 2 categories, namely positive and negative sentiment regarding the relocation of the National Capital, analyzed using the Support Vector Machine method. In this study, the SVM kernel type was used, namely a linear kernel with an accuracy of 92.70%, then improved with Stratified k-Fold Cross Validation, getting 100% accuracy in iterations 1 and 5. The classification results using the Support Vector Machine method are statedthat the linear kernel has better accuracy. This sentiment analysis provides insight into the public's views on the proposed measure. This research can be used as material for consideration of future government policy regarding relocating the capital city.
Sistem Informasi Kesatuan Pengelolaan Hutan Yogyakarta Berbasis Web Hidayat, Rochmad; Pratomo, Dinar Nugroho; Santoso, Probo; Oktalina, Silvi Nur
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.v10i1.6262

Abstract

The Forest Management Unit Information System (SIKPH) is a platform that integrates information technology to improve the efficiency and effectiveness of forest management. This research aims to develop a web-based SIKPH as a modern solution for the Forest Management Unit in Yogyakarta. The system development method uses the scrum methodology, which consists of requirements analysis, system design, implementation, and evaluation. Requirements analysis was conducted by understanding the demands and challenges faced by the Yogyakarta Forest Management Unit. Based on this analysis, the system design includes web architecture, user interface, database, and functionality that supports forest management processes. System implementation using the Laravel framework with performance testing shows an average response time of 1.2 seconds for 20 simultaneous users and 2.0 seconds for 30 users. User acceptance evaluation involved 30 respondents with beta testing results showing an average satisfaction level of 4.4 out of 5 for aspects of ease of use (4.3), feature compatibility (4.5), and system benefits (4.6). The system includes modules for forest sustainability monitoring, inventory management, and reporting with a 96% implementation success rate based on functional testing. The results of this research provide a positive contribution to forest management in Yogyakarta by improving process efficiency by 40% compared to the previous manual system.

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