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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
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.
Random Under Sampling for Performance Improvement in Attack Detection on Internet of Vehicles Using Machine Learning Anargya, Muhammad Alden Nayef; Ghozi, Wildanil; Rafrastara, Fauzi Adi
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.v10i1.8034

Abstract

The Internet of Vehicles (IoV) technology is one of the advancements derived from the Internet of Things (IoT) in the transportation sector, benefiting its users. However, the development of this technology cannot be separated from various security threats, particularly Denial of Service (DoS) and spoofing attacks. Given these threats, it is crucial to continuously develop methods used for detecting attacks on IoV systems. Several researchers have conducted research related to attacks and threats on IoV systems, and one such study resulted in a dataset called CICIoV2024. This dataset has an imbalanced class distribution. This study aims to examine the implementation of Random Under-Sampling to improve the performance of classification algorithms in detecting attacks on IoV systems. The algorithms used in this study include Decision Tree, K-Nearest Neighbors (KNN), and Random Forest. The test results show that the Random Forest algorithm achieved the best results with an accuracy of 98.5% and an F1-Score of 98.5%.
Implementation of Radio Frequency Identification in Student Presence Applications with Multi Social Media Notification Nishom, M.; Wibowo, Dega Surono; Bakti, Very Kurnia; Rais, Rais
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.v10i1.8341

Abstract

Radio-Frequency Identification or commonly called RFID is a technology that can be integrated into various softwares to increase operational efficiency and effectiveness. In an educational unit, one of the services that needs to be repaired or improved is recording student attendance. However, recording and monitoring student attendance in almost all educational units in Indonesia, and especially in Tegal City is still carried out conventionally, so that educational units cannot provide feedback to parents about their children's attendance in real time. This condition is the main basis for conducting this research. In this research, RFID technology was implemented into an desktop based application with the aim of making it easier for educational units to record student attendance automatically, and assisting schools in providing feedback about student attendance to parents through social media services (whatsapp or telegram) and increasing enthusiasm students in taking attendance. The method chosen for development is the waterfall method, this method ensures that all stages are carried out sequentially. The research application has been tested using the black box testing method, the test results indicate that the application functionality is running well.
Analisis Sentimen Aplikasi Get Contact di APP Store Menggunakan Metode SVM (Support Vector Machine) Aulia, Narisa; Sari, S N; Wakhidah, N
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.v10i1.8057

Abstract

Current technological developments have led to a variety of new innovations to create applications that make it easier for users to manage phone calls, one of which is the Get Contact application. By managing phone calls, it is hoped that it will help users to minimize the occurrence of fraud or the like. The goal is to analyze user sentiment towards the Get Contact application by classifying user reviews into positive and negative categories through sentiment analysis. The Support Vector Machine method is used in this analysis process with a linear kernel approach to determine the accuracy of the Get Contact application review classification. The stages used in this research include data collection, preprocessing, labeling, split data, SVM model training, and model evaluation. This study shows that the Support Vector Machine (SVM) method classification of sentiment analysis of Get Contact application reviews on the App Store produces an accuracy value of 95.50%, negative precision 0.96, positive precision 0.95, negative recall 0.95, positive recall 0.96, positive and negative f-1 scores are the same, amounting to 0.95. As for the results of the most reviews are negative reviews with a negative review percentage of 94.8%, while for positive reviews it is 5.2%.
Utilization of Mobile Applications for Digital Marketing of MSMEs: Challenges and Opportunities in Central Lampung Ferdiansyah, Muhammad; Mariya, Lika; Widyastuti, Widyastuti
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.v10i1.8202

Abstract

This study aims to identify and recommend the development of a digital marketing application for MSMEs in Central Lampung, with a focus on addressing operational challenges and limited market access. Using the Systems Development Life Cycle (SDLC) approach with the Waterfall method, this research examines the necessary features to improve operational efficiency, expand market reach, and support data-driven decision-making. The key features recommended include a digital product catalog, payment integration, customer notifications, order tracking, and an analytics dashboard. This application is expected to reduce reliance on costly traditional promotional methods, while enhancing product visibility and customer interaction. However, challenges such as low digital literacy and limited internet infrastructure in some areas remain barriers that must be addressed through training, infrastructure improvement, and incentive strategies. The study suggests further research to evaluate the long-term impact and the potential application of advanced technologies to support more personalized and effective marketing strategies for MSMEs.
Sistem Manajemen Pengungsi Guna Meningkatkan Efektivitas Operasional BPBD Kota Batu Dalam Pendataan Dan Pemantauan Pengungsi Ardiansyah, Muhammad Rizqi; Rosiani, Ulla Delfana; Yunhasnawa, Yoppy
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.v10i1.7488

Abstract

Batu City is a region known for its natural beauty but also faces high risks of natural disasters such as landslides, earthquakes, and floods. The primary challenge faced by the Regional Disaster Management Agency (BPBD) of Batu City is the manual processing of refugee data. In emergency situations, such as post-disaster scenarios, time is crucial, and manual data collection, processing, and reporting can hinder the rapid response needed to assist refugees. Additionally, data mismatches and inaccuracies in logistics and kitchen needs pose serious problems. Therefore, there is a need for a refugee management information system to enhance the operational effectiveness of BPBD Batu City in data processing, real-time data monitoring, and ensuring the accuracy of logistics and kitchen needs data. This study employs a combination of design thinking and the spiral method for system development. Based on testing the impact of the application on BPBD's response showed an increase in response speed by 87.1%. This proves that the implemented system effectively enhances BPBD Batu's operational efficiency in refugee data collection and monitoring.
Rancang Bangun Sistem Informasi Psikoedukasi Berbasis Web Cintadiri.id: Pencegahan dan Penanganan Self-harm Arsad, Bambang Riono; Syihab, Aisyah; Faradiba, Andi Tenri
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.v10i1.6596

Abstract

Self-harm is an intentional act of self injury without suicidal intent. In Indonesia, self-harm is becoming an increasingly serious problem, especially among teenagers. Previous studies and surveys conducted by institutions shows quite significant results with relatively high numbers. Considering that the causes of self-harm are quite complex, there is a need for education about self-harm and access to mental health services. Based on aforementioned researches, a web-based information system was developed which the author called Cintadiri.id. Cintadiri.id was designed and developed as an innovative and comprehensive information system to help prevent and deal with self-harm behavior in Indonesia. This system hopes to help people who are struggling with self-harm behavior get the information and resources they need to get help and recover. Cintadiri.id information system was developed using SDLC Waterfall method, supported with PHP programming language, MySQL database and Laravel framework.  Cintadiri.id provides various information and resources that can help people who are struggling with self-harm, including information about self-harm, resources and tools to help people who are struggling with self-harm behavior. It is hoped that Cintadiri.id can be a reference for the information and resources they need to get help.
Modifikasi Gain Ratio Pada Algoritma C4.5 dengan Nilai Koefisien Determinasi untuk Prediksi Kelulusan Mahasiswa (Studi Kasus: Universitas Islam Madura) Muhsi, Muhsi; Suprapto, Suprapto
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.v10i1.5986

Abstract

C4.5 is a decision tree algorithm that can be used for making predictions. The stages start from forming a decision tree through splitting attributes, pruning and extracting rules or knowledge to then be used for prediction. However, one of the weaknesses of the C4.5 algorithm is the occurrence of overfitting and misclassification costs which result in low prediction performance. The development of the C4.5 algorithm has been carried out in terms of split attributes such as the imprecise info-gain ratio (Credal-C4.5) method using Imprecise Probability Theory, bossing gain ratio (C5.0) and average gain. This research applies the termination coefficient value (R2) as a method for modifying the gain ratio in selecting attributes as decision tree nodes which is then implemented to predict student graduation on time using a case study at the Universitas Islam Madura (UIM). Testing of the decision tree model rule for predicting student graduation on time at UIM shows that the performance values of accuracy, precision and recall are 70.49%, 77.14% and 72.97%. This performance is higher compared to the C4.5 algorithm without making modifications to the coefficient of determination, especially in accuracy and recall performance, while the precision is lower but the difference is below 1%. The difference in performance values was 11.48% (positive) for accuracy and 27.03% (positive) for recall. Meanwhile, precision performance has a difference of -0.13% (negative). The application of the Knowledge Model Rule for student graduation on time at SIMAT UIM shows very good results because it displays a prediction results page.
Penerapan Data Mining Dalam Pemberian Kelayakan Kredit Nasabah Pada Badan Usaha Milik Desa Gedong Gincu Dengan Metode Naïve Bayes Hanifatun, Farras; Zahrotun, Lisna
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.v10i1.5939

Abstract

BUMDes Gedong Gincu is a rural business that provides savings and loan services to village communities. BUMDes Gedong Gincu in determining customers is still very simple, namely by looking at where the customer comes from and how close they are to previous customers who have applied for credit, so it is not a guarantee whether or not the new customer is eligible to get a loan at BUMDes Gedong Gincu. Another problem that occurs is the lack of thoroughness by BUMDes administrators in assessing customers.  The aim of this research is to apply the Naïve Bayes method in determining the credit worthiness of customer applications. The method used in this research is Naïve Bayes with testing using a confusion matrix. Research stages include data selection, data cleaning, data transformation, application of the Naïve Bayes method, testing. The result of this research is an application that can facilitate BUMDes Gedong Gincu in evaluating the feasibility of providing credit. The test results using 186 data using the confusion matrix method, an accuracy of 67% was obtained. However, based on SUS testing by users, they got a result of 82.25. This indicates that this application is good and suitable for use by BUMDes Gedong Gincu.
Clustering and Profiling Analysis for FIFA Football Player using K-Means Azzami, Salman Yuris Adila; Hadi, Heru Pramono; Alzami, Farrikh; Irawan, Candra; Nurhindarto, Aris; Sulistyono, MY Teguh
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.v10i1.7897

Abstract

The selection of football players is a complex process involving talent evaluation based on various performance indicators, combining objective measures with subjective assessments by coaches and scouts. This research aims to improve the football player selection process using the K-Means clustering method based on the attributes of transfer price, performance, body specifications, position, and player ability. The dataset used consists of 17.947 players taken from the FIFA 19 edition of the soFIFA.com platform, which includes complete information such as transfer price, performance, body specifications, position, and player ability. The data was processed using principal component analysis (PCA) to reduce the dimensions, followed by the Elbow Method to determine the optimal number of clusters. The clustering results show the distribution of players based on their on-field roles, such as center back, goalkeeper, striker, and left wing back. The profiling of players from each cluster is identified based on position, body type, dominant foot usage, transfer price, and rating. This research provides useful insights for coaches and scouts in selecting players that suit specific roles in the team using better analysis. The findings also highlight the importance of player clustering for data-driven decision-making, which can optimize team composition and overall performance.

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