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JISA (Jurnal Informatika dan Sains)
Published by Universitas Trilogi
ISSN : 27763234     EISSN : 26148404     DOI : https://doi.org/10.31326/jisa
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
JISA (Jurnal Informatika dan Sains) is an electronic publication media which publishes research articles in the field of Informatics and Sciences, which encompasses software engineering, Multimedia, Networking, and soft computing. Journal published by Program Studi Teknik Informatika Universitas Trilogi aims to give knowledge that can be used as a reference for researchers and can be useful for society. Accredited “SINTA 4” by The Ministry of Research-Technology and Higher Education Republic of Indonesia, Free of Charge (Submission,Publishing). JISA (Jurnal Informatika dan Sains) is scheduled for publication in June and December (2 issue a year) This Journal accepts research articles in these following fields: Software Engineering: Web Development, Mobile Apps Development, Database Management System Multimedia: Augmented Reality, Virtual Reality, Game Development Networking: Cloud Computing, Internet of Things, Wireless Sensor Network, Mobile Computing Soft Computing: Data Mining, Data Warehouse, Data Science, Artificial Intelligence, Decision Support System
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 187 Documents
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Design and Development of an Android-Based Merchandise Management Application for K-pop Consignment Services Cahyani, Nilam Putri; Sutarman, Sutarman
JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i2.2107

Abstract

The rapid development of technology has increased various societal needs, especially in the e-commerce sector, including the delivery service of K-pop merchandise. The global popularity of K-pop has led to high demand for related merchandise such as albums, lightsticks, and exclusive clothing and accessories, often difficult to source internationally. This demand creates challenges for businesses in managing product data, inventory, and transactions effectively. Zena.id, as a business providing K-pop merchandise delivery services, faces specific issues with ensuring accurate transaction recording and real-time inventory monitoring. An efficient system is needed to reduce human error, prevent inventory discrepancies, and meet customer expectations for product availability. This research aims to develop an Android-based application to automate transaction recording and inventory monitoring at Zena.id. The application is designed to improve operational efficiency through an integrated system for accurate stock monitoring and transaction processing. Developed using the Kotlin programming language and an Agile approach, this method allows for flexible, iterative improvements. Testing results showed a 83.33% accuracy rate in transaction processing and inventory updates, significantly simplifying management tasks and reducing potential errors. Additionally, the user-friendly interface enhances satisfaction for both business managers and customers. This application serves as an optimal solution to address the unique challenges faced by K-pop merchandise delivery services in the digital era.
Vehicular Ad-Hoc Networks for Intelligent Transportation System: A Brief Review of Protocols, Challenges, and Future Research Bintoro, Ketut Bayu Yogha
JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i2.2112

Abstract

Vehicular Ad Hoc Networks (VANET) play an essential role in the advancement of intelligent transportation systems, facilitating real-time communication between vehicles (V2V), infrastructure (V2I), and surrounding environments (V2X). This systematic review analyzes a range of VANET routing protocols, highlighting the strengths and weaknesses of topology-based, position-based, cluster-based, and hybrid methods. Additionally, this review explores core challenges in VANET, including high mobility, data security, Quality of Service (QoS) requirements, and connectivity issues in dynamic and high-density traffic environments. The paper also provides insights into simulation tools and performance metrics employed in VANET research alongside practical applications in modern transportation systems, such as autonomous driving, traffic management, and safety-related communication. Furthermore, this review emphasizes the need for ongoing research to address the identified challenges and optimize VANET performance. Integrating emerging technologies, including 5G, artificial intelligence (AI), and edge computing, offers promising avenues for enhancing system efficiency and sustainability. This review establishes a comprehensive foundation for further advancements in VANET by highlighting key findings and research gaps. Ultimately, the effective implementation of VANET has the potential to significantly improve transportation safety, efficiency, and sustainability, contributing to the realization of smart city initiatives and innovative mobility solutions. This work aims to guide future research directions, ensuring that VANET continues to evolve in alignment with the demands of modern transportation systems and the broader context of intelligent mobility.
Development of Mobile GIS Based Digital Map Location Marking Application for Navigation Purposes Ghifari, Alif; Sutarman, Sutarman
JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i2.2108

Abstract

In today's digital era, map and navigation applications have become essential tools for users to find locations, obtain the fastest routes, and explore new places. Google Maps is one of the most popular and comprehensive mapping applications that offers various features, such as navigation. However, despite being highly beneficial, Google Maps has several limitations, particularly regarding map markers, personalized, creating individual routes, and offline map usage on navigation. To address these issues, this research develops an innovative application called StellarPath. StellarPath is a mobile-based digital map location marker application that adopts Location Based Service (LBS) methods for more effective navigation. This application focuses on offline usability as a digital map marker and includes features such as offline maps stored indefinitely, offline navigation, manual route creation, and higher personalization, allowing users to save and manage markers with additional information offline. Test results show a success rate of 92.5%, indicating the application's effectiveness. The conclusion drawn is that the application can download and store maps offline, although it has shortcomings in managing downloaded maps. The offline navigation feature allows users to draw, save, and manage manual routes on the map. Users can create and save location markers with additional information offline. Navigation is flexible, with the option to start navigation by tapping on the map and features that can be enabled or disabled. This research aims to provide a more flexible and personalized navigation solution compared to existing standard map and navigation applications, such as Google Maps.
Development of a Cashier Business Transaction System using the Android Based Agile Method Junanda, David Bagus; Mardhiyyah, Rodhiyah
JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i2.2113

Abstract

The grocery retail sector in Indonesia plays an important role in meeting people's basic needs, with grocery merchants in urban and rural areas serving as the main middlemen in the distribution of staples to end consumers. Grocery merchants in Indonesia often face challenges in improving sales efficiency due to the use of conventional methods that are slow, unstructured, and prone to recording errors. These challenges can potentially lead to loss of customers, financial losses, and hinder business growth. This research aims to develop an Android-based cashier application specifically designed for grocery merchants to improve transaction efficiency and stock management. Using a qualitative approach, in-depth interviews were conducted to understand the needs and constraints faced by merchants in the transaction process. The findings were used to design the main features of the application, such as CRUD-based item management (Create, Read, Update, Delete), barcode scanning with a smartphone camera, digital receipt sending via WhatsApp, and payment support via QRIS E-wallet and cash transactions. This application is assumed to be used on Android devices with adequate internet access. The results show that this application is able to reduce recording errors, speed up transactions, and increase customer satisfaction compared to the manual method. The solution is expected to improve productivity, drive business growth, service quality and customer satisfaction as well as the competitiveness of grocers in the digital era. Future recommendations include the development of analytics features to monitor sales performance and support strategic decision-making
Cloud Computing Technology in Supporting the Implementation of One Data Indonesia Sawitri, Dara
JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i2.2104

Abstract

Cloud computing services provide resources in the form of infrastructure platforms, software, and other hosting to customers. Data provided by digital systems is carried out in a cloud computing model service, providing data access anywhere as long as it is connected to the internet. In today's digital era, cloud computing supports the implementation of One Data Indonesia (SDI) to obtain quality data that is well integrated between local governments and the central government. With One Data Indonesia, it is hoped that data will have consistency so that it can be relied on for analysis and has a good level of security. One Data Indonesia is an idea from the Indonesian government to combine and maximize the use of data generated by government agencies in Indonesia so that it is useful for decision-making, planning, and more optimal public services. In realizing SDI, cloud computing can be utilized for data storage, ease of access, and creating better cooperation between government agencies. Cloud computing can help the Indonesian government optimize public services safely, and reliably, and maximize data potential in various fields to gain competitive advantages in all sectors of government.
Development of Paramadina Roomhub Application As Room Booking System Using Waterfall Method Maulana, Reza Arif; Fatih, Muhamad Adillah; Suto, Lintang Arbi; Darwis, Muhammad
JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i2.2109

Abstract

The manual room booking process at Paramadina University faces several challenges, including inefficiencies, human errors, and communication breakdowns between applicants and facility managers. These issues often result in room booking conflicts and delays, hindering effective facility usage. The need for a more streamlined, user-friendly solution led to the development of the Roomhub Paramadina application, a web-based system designed to facilitate room bookings within the university. The objective of this research is to design and implement a digital room booking system that simplifies the current manual process. The application was developed using the Software Development Life Cycle (SDLC) with the Waterfall framework. This approach ensures structured and systematic development, enabling the team to follow sequential stages from requirements gathering to testing. The Roomhub application allows users to view available rooms, submit booking requests, and receive confirmations directly via an online platform. The system integrates with existing university infrastructure and ensures real-time room availability, reducing errors such as double bookings. Black-box testing was employed to verify the application’s functionality, and the results confirmed that the system meets user needs while significantly improving booking efficiency. By automating room bookings and enhancing communication between the parties involved, this research offers a practical solution that improves operational efficiency, reduces paperwork, and minimizes scheduling conflicts, thereby benefiting the entire academic community at Paramadina University. 
Smart-Working and Hot Desking Application Development using Agile and Extreme Programming Method at Xtra Cowork Nurdin, Daeng Ahmad; Firmansah, Dodik; Hafifi, Akrom; Darwis, Muhammad
JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i2.2105

Abstract

The current condition of working desks often faces challenges such as poor management and inefficiency in space utilization, which complicates the adoption of Smart-Working culture at Xtra Cowork. To address these issues, the writer aims to facilitate the transition for offices adopting Smart-Working culture by designing a hot desking supporting mobile app. Through observation, the research identifies the need for a reliable system to support hot desking practices. To complete this research, the writer uses agile and extreme programming methods. For app designing, the writer uses UML. The main tools used for developing the app are Flutter with Dart language. The developed mobile app successfully fulfills these requirements. The results of the application testing using the black box method has passed 100% of the test cases. It shows that all functions have worked as designed and could be used by the users as intended. Future researchers can build upon this work to address other Smart-Working culture needs.
Donation Raising Application Using Rapid Application Development (RAD) Method Based on Mobile Application Nugraha, Aditya Bagas; Widodo, Tri
JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i2.2111

Abstract

Indonesia is one of the countries that has a high social spirit in doing gotong royong. Its people love to help and build social welfare. There are several activities that prioritize the principle of gotong royong in society, one of which is donation-raising activities. Many institutions still collect donations in a conventional way. This can be an obstacle for donors because not all institutions or communities that collect funds are in the same area and the reach is relatively small. Lack of public trust is also a reason because of the rampant fraud on behalf of institutions and foundations, so that it can hamper the raising of donations. To overcome these problems, a new system is needed that can be applied to the community. A fundraising platform is needed to make it easier for people to donate easily and efficiently. The Rapid Application Development (RAD) method is used in its development. System development uses the Kotlin programming language and uses a realtime Firebase database to manage the data. With this system, the mobile application can facilitate and provide access to the community in making donations online without collecting manually, raising donations can also provide a wider range of donations.
Implementation Of Forward Chaining In Intelligent Systems For Automatic Car Engine Fault Detection Siregar, Juarni; Hartana, Hartana; Wijayanti, Diah; Herryansyah, Herryansyah
JISA(Jurnal Informatika dan Sains) Vol 8, No 2 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i2.2551

Abstract

Intelligent systems are one application of artificial intelligence technology that can assist in automatic decision-making based on a knowledge base. In this study, a smart system based on the Forward Chaining method was designed and implemented to detect damage to petrol-powered car engines. This system employs the Forward Chaining method, which systematically matches the user-inputted symptoms with the rules in the knowledge base to determine the most likely cause of the damage. The knowledge base was developed through in-depth interviews with three expert technicians from official repair shops and validated by a head supervisor, resulting in 28 specific diagnostic rules. Diagnostic data, including symptoms and corresponding damage, was collected from service records of 50 cases involving Toyota Avanza and Honda cars manufactured between 2019 and 2022. This system is capable of detecting various symptoms, such as sudden engine failure, difficulty starting, excessive vibration, abnormal exhaust smoke colour, and unusual engine noise. The system development process used a waterfall approach that included needs analysis, knowledge base design, interface creation, and system testing. The test results showed that the system was able to detect 94% of damage types with high accuracy based on the combination of symptoms provided by the user. Thus, this system can be an effective tool in engine maintenance activities and improve production process efficiency in industrial environments.
Improved Lung Disease Classification Using Bagging and Averaged Ensemble Models Tayib, Hana Ali; Salih, Azar Abid
JISA(Jurnal Informatika dan Sains) Vol 8, No 2 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i2.2440

Abstract

One of the essential medical imaging tasks for early diagnosis and treatment planning is categorizing lung diseases from chest X-ray (CXR) images. This work constructs a strong ensemble learning platform on a variety of deep models for boosting diagnosis performance to detect and identify lung disease. Three prtrianed CNN models InceptionV3, ResNet50, and EfficientNetV2M were trained on a CXR dataset, motivated by the complementary architectural features and the success demonstrated in medical imaging problems, such as chest X-rays. These three networks belong to different families of the CNNs and therefore make different contributions for diversity and stability in the ensemble. The models were then ensembled in two methods: averaging (soft voting) and bagging with hard voting (maximum bootstrap aggregation) in the first method. Various sets of pre-trained models were experimented with for the averaged ensemble. According to experimental results, the soft voting (averaged) ensemble between EfficientNetV2M and InceptionV3 performed better than the other models' combinations and achieved the highest accuracy of 93.00% in classification. This was followed by the combination of EfficientNetV2M and ResNet50 with an accuracy of 92.09%, then InceptionV3 and ResNet50 with a value of 91.75%, and the complete ensemble of the three models with an accuracy of 92.14%.The bagging hard voting strategy was somewhat with lower accuracy, but the InceptionV3 based bagging ensemble attained 90.56%, EfficientNetV2M attained 91.00%, and ResNet50 attained 88.00%. It is evident from the results that soft voting strategy, InceptionV3 and EfficientNetV2M ensemble provides the best optimal and stable classification performance among all the configurations that were attempted. The study proves that ensemble learning improves the accuracy of lung disease classification models, and choosing the right architectures is essential, with EfficientNetV2M and InceptionV3 showing improved performance, resulting in early diagnosis and improved patient outcomes.

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