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Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika)
Published by Sekolah Tinggi Ilmu Komputer Tunas Bangsa
ISSN : 25275771     EISSN : 25497839     DOI : 10.30645
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
JURASIK adalah jurnal yang diterbitkan oleh LPPM STIKOM Tunas Bangsa Pematangsiantar yang bertujuan untuk mewadahi penelitian di bidang Sistem Informasi dan Teknik Informatika. JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika) adalah jurnal ilmiah dalam ilmu komputer dan informasi yang mengandung literatur ilmiah pada studi murni dan penelitian terapan dalam ilmu komputer dan informasi dan ulasan publik pengembangan teori, metode dan ilmu terapan yang berkaitan dengan subjek. Jurnal ini pertama kali mendapat ISSN dengan nomor 2527-5771 pada tahun 2016 untuk terbitan cetak dan mulai 2017 beralih ke terbitan elektronik dengan nomor ISSN 2549-7839. Pengiriman artikel tidak dipungut biaya, kemudian artikel yang diterima akan diterbitkan secara online dan dapat diakses secara gratis. JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika) adalah sebuah jurnal peer-review secara online yang diterbitkan bertujuan sebagai sebuah forum penerbitan tingkat nasional di Indonesia bagi para peneliti, profesionaldan praktisi dari industri dalam bidang Ilmu Kecerdasan Buatan. JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika) menerbitkan hasil karya asli dari penelitian terunggul dan termaju pada semua topik yang berkaitan dengan ilmu komputer. JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika) terbit 1 (satu) nomor dalam setahun. Artikel yang telah dinyatakan diterima akan diterbitkan dalam nomor In-Press sebelum nomor regular terbit. JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika) telah terindeks Google Scholar, Garuda, Crossref dan terus akan diupdate mengikuti perkembangan. Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) telah melakukan perubahan jumlah terbitan dari 1 x setahun (Juli) menjadi 2 x setahun (Februari dan Agustus) dan telah melakukan perubahan data administrasi pada laman LIPI dengan url: http://u.lipi.go.id/1480905139. Topik dari jurasik adalah sebagai berikut (namun tidak terbatas pada topik berikut) : Artificial Intelligence, Digital Signal Processing, Human-Computer Interaction, IT Governance, Networking Technology, Optical Communication Technology, New Media Technology, Information Search Engine, Multimedia, Computer Vision, Information System, Business Intelligence, Information Retrieval, Intelligent System, Distributed Computing System, Mobile Processing, Computer Network Security, Natural Language Processing, Business Process, Cognitive Systems, Software Engineering, Programming Methodology and Paradigm, Data Engineering, Information Management, Knowledge-Based Management System, Game Technology.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 403 Documents
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Klasifikasi Stunting Pada Balita dengan Algoritma Random forest dan Support Vector machine Panigoro, Buyung; Barata, Mula Agung; Mahmudah, Nur
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.904

Abstract

Stunting is a health problem in the world, many factors cause stunting in toddlers, this study aims to compare the performance of the Random forest algorithm and Support Vector machine using a private dataset with a total of 618 toddler data in the Sumberharjo area in February, August 2023-2024. Adding a combination of smote techniques to handle unbalanced data and k-fold Cross-validation. The results showed the Random forest algorithm with a stable accuracy of 95.41% after reaching 94.35%. For the Support Vector machine algorithm, it achieved an accuracy of 81.45% after being smote to 83.06% and the recal decreased to 51.16%. Random forest is more recommended for classifying stunting in toddlers with stable results compared to Support Vector machines.
Dampak Penerapan ODOO ERP Terhadap Kinerja Supply Chain Management Pada PT Anugrah Jaya Group Amsa, Femas Galang Samudra; Prihati, Yani; Wahyuni, Ana
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.927

Abstract

Companies in the digital era need to integrate business processes to improve efficiency and competitiveness. Odoo is an open-source Enterprise Resource Planning (ERP) platform that provides integrated solutions for managing diverse operational functions, including Supply Chain Management (SCM). The implementation of Odoo ERP at PT Anugrah Jaya Group, a company engaged in the sale of gadget accessories, has proven to enhance inventory management efficiency, accelerate order processing, and improve reporting accuracy. The system also reduces the risk of supply delays and strengthens coordination among departments within the supply chain. This system design utilizes Unified Modeling Language (UML) to visualize business process flows and ensure optimal integration. Therefore, Odoo ERP contributes positively to improving SCM performance and serves as a strategy that supports the sustainability of business processes at PT Anugrah Jaya Group.
Peningkatan Akurasi Deteksi Intrusi Jaringan dengan Model Hybrid Convolutional Neural Network dan Long Short-Term Memory Pratama, Ficho Pranandasya Andrian; Sulistyo, Danang Arbian; Mukti, Fransiska Sisilia
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.895

Abstract

The evolving cyber threats demand more sophisticated and accurate intrusion detection systems (IDS). This research develops a hybrid CNN-LSTM model with comprehensive data preprocessing techniques to enhance network attack detection accuracy. The UNSW-NB15 dataset consisting of nine attack categories and 49 features was used as research data. The methodology begins with data preprocessing including data cleaning, categorical transformation using categorical codes, class balancing with upsampling, StandardScaler normalization, and 80:20 data splitting. The hybrid model architecture combines three CNN blocks for spatial feature extraction with two LSTM layers for modeling temporal dependencies. The model was compiled using Adam optimizer with 0.0005 learning rate and equipped with EarlyStopping, ReduceLROnPlateau, and ModelCheckpoint callbacks. Evaluation results show the CNN-LSTM model achieves 99% accuracy, precision, recall, and F1-score, significantly outperforming the standard CNN model which only reaches 96%. Learning curves demonstrate rapid convergence without overfitting indication. This research proves that the combination of CNN's spatial feature extraction capability and LSTM's temporal dependency modeling is highly effective for anomaly detection in complex sequential data such as network traffic.
Perancangan dan Implementasi Sistem Inventory Berbasis Web pada Usaha Ritel Bangunan TB Lancar Maron Belly, Desidarius Eduardo Djee; Yasin, Verdi; Sianipar, Anton Zulkarnain
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.918

Abstract

This study aims to design and implement a web-based inventory information system at TB Lancar Maron to replace the previously manual system used for managing stock records. The previous system faced several issues, including data entry errors, delayed reporting, and stock inconsistencies, which hindered efficiency and effectiveness in inventory management. The system development process followed the Scrum approach within the Agile methodology, starting from sprint planning, user requirement gathering, system design, to implementation and evaluation stages. The technologies employed included Laravel framework for backend development, MySQL for database management, and a responsive web interface for accessibility. The implementation results show that the system is capable of recording incoming and outgoing goods in real time, generating automated reports, and allowing the store owner to monitor stock levels from any internet-connected device. System performance was evaluated through direct testing by administrators and staff, and the outcomes indicated improved work efficiency, stock data accuracy, and ease of reporting. Furthermore, the new system successfully minimized common errors that occurred with the manual method. With this new solution, TB Lancar Maron benefits from a professional and integrated digital inventory management system. This study is expected to serve as a reference for the application of inventory information systems in small and medium-sized retail businesses.
Comparison of VGG16 and Resnet50 Architecture using GLCM Feature Extraction In Detecting Monkeypox Yusrizal, Najla Qurrata Aini Putri; Hanif, Isa Faqihuddin
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.909

Abstract

The increasing number of monkeypox cases has become a global health issue that de-mands rapid and accurate diagnosis. In Indonesia, monkeypox cases reached 88 victims as of August, 2024. The complex symptoms of monkeypox, which often resemble those of other diseases, require advanced technology to distinguish them in a short amount of time. The purpose of this research is to enhance the accuracy and efficiency of the model in identifying monkeypox skin lesions automatically and quickly, thereby supporting the medical diagnosis process more effectively. This study proposes an innovative approach by combining Gray Level Co-occurrence Matrix (GLCM) feature extraction with deep learning architectures ResNet50 and VGG16 for detecting monkeypox in skin lesion im-ages The results show a significant improvement in classification accuracy for both Res-Net50 and VGG16. The GLCM-VGG16 model achieved an accuracy of 95.75%, an im-provement of 18.57% from its original 77.18% without GLCM features. The GLCM-ResNet50 model reached an accuracy of 98.07%, marking a 44.82% increase from the initial 53.25%. The training time of models with GLCM features was also faster compared to models without GLCM. The integration of GLCM successfully captured unique texture characteristics in monkeypox lesions, thereby enhancing the model's ability to distinguish them from other skin diseases. These findings indicate that the combination of GLCM with CNN architectures can be an effective approach for accurately and efficiently detect-ing skin diseases.
Integrasi Sistem Reward dan Penilaian Kinerja Berbasis KPI dalam Mendukung Knowledge Management pada Layanan Pelanggan Digital Edwinsyah, Muhammad; Hermawan, Fairuz Fernanda; Dinayatullah, Ledi; Lubis, Muharman
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.900

Abstract

In the digital service era, the role of Knowledge Management (KM) becomes increasingly critical in ensuring efficient, responsive, and high-quality customer interactions. However, the effectiveness of KM implementation is not only determined by technological infrastructure, but also by the motivation and active participation of service agents. This study examines the integration of reward systems and Key Performance Indicator (KPI)-based performance appraisal in supporting KM practices within digital customer service environments. Using a Systematic Literature Review (SLR) method and a reflective case study of the live chat service unit of a leading Indonesian e-commerce company (Bukalapak), this research reveals how reward mechanisms and KPI structures influence knowledge sharing behaviors, agent performance, and service quality. The findings indicate that hybrid KPI systems combining quantitative metrics (such as response time and CSAT) and qualitative assessments (such as communication quality) alongside tiered reward schemes, significantly enhance agent engagement and knowledge utilization. Additionally, continuous feedback from the Quality Assurance team strengthens organizational learning and service innovation. This study offers theoretical and practical contributions in designing integrated strategies to reinforce KM through performance measurement and motivation systems in digital service sectors.
Implementasi Machine Learning Dalam Sistem Keamanan Rumah Pintar Berbasis Iot Dengan Deteksi Gerakan dan Pengenalan Wajah Amirullah, Alfian Nur; Faizin, Arif
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.923

Abstract

Innovation in digital-based home security systems. This study aims to design and implement a smart home security system capable of detecting motion and recognizing faces using the Convolutional Neural Network (CNN) model. The system utilizes the ESP32-CAM microcontroller and PIR sensor as main components, where captured face images are sent to a local or cloud server for classification. Test results show that the system can detect motion at an optimal distance of 4–6 meters and recognize household members’ faces with an accuracy of up to 92%. The system is also integrated with the Telegram API to send real-time notifications when unknown faces are detected. This approach proves the system to be responsive, efficient, and capable of enhancing home security automatically and adaptively according to environmental conditions.
Implementasi Naïve Bayes Pada Sistem Klasifikasi Kelayakan Alat Laboratorium Kimia Mulya, Sri; Putri, Yulia Eka; Amir, Firmanul Qadri
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.891

Abstract

The feasibility of laboratory equipment is a crucial factor in ensuring the quality and safety of practical and research activities. At the Faculty of Mathematics and Natural Sciences, Universitas Andalas, the classification of equipment feasibility is still performed manually, leading to inefficiencies and potential assessment errors. This study aims to develop and implement a web-based information system for classifying the feasibility of laboratory equipment using the Naïve Bayes algorithm. The research applies a system development approach following the Waterfall model, starting with requirement analysis, system modeling using Context Diagram, DFD, and ERD, and implementation using PHP and MySQL. The Naïve Bayes algorithm calculates the probability of each feasibility class based on attributes such as procurement year, usage level, damage condition, usage duration, and accessory status. Test results indicate that the system successfully classifies equipment into three categories serviceable, needs repair, and unserviceable with 95% acceptable accuracy. The system generates report-based outputs that support strategic decision-making in equipment maintenance and procurement planning. Thus, this information system is expected to enhance the efficiency and objectivity of laboratory asset management through a data-driven and measurable digital platform.
Implementasi Virtualisasi Proxmox Ve Mengatasi Keterbatasan Sistem Untuk Meningkatkan Efisiensi Layanan Metro Global News Susilo, Zefanya Damar Aristo; Himamunanto, Agustinus Rudatyo; Lase, Kristian Juri Damai
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.914

Abstract

Metro Global News is a media company that, to this day, remains dependent on third-party hosting services as a means to reach its users. This reliance has led to limitations in independently managing server infrastructure, reduced system flexibility, increased operational costs, and minimal control over service configurations. This study aims to implement an internal server infrastructure using virtualization technology based on Proxmox VE as a solution to these challenges. Tools such as Netdata and Portainer were utilized to monitor system performance and resource usage in real-time. The system was built using two virtual machines (VMs), each running separate services within containers, enabling modular management and supervision. Monitoring results through Netdata recorded a total of 4,211 active metrics covering performance indicators such as CPU, RAM, disk I/O, and network usage, with log consumption of only 552 KB at the highest tier. Meanwhile, Portainer reported 4 active containers running application services, 3 storage volumes, and 5 images, with a total RAM allocation of 4.1 GB and the use of 2 CPU cores. All services operated stably under full load conditions without downtime, indicating that the system can function optimally with minimal resources. These findings confirm that Proxmox VE is an effective and cost-efficient solution for building internal IT infrastructure, particularly for medium-scale organizations requiring full control over their systems. This study also opens opportunities for further development through features such as clustering and high availability to enhance service reliability in the future.
Aplikasi Mobile Untuk Pengelolaan Dan Promosi Seni Lokal Dengan Sistem E-Commerce Terintegrasi Bennvenito, Fillan Ivan Luccas; Tashid, T; herwin, H; Zoromi, Fransiskus
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.905

Abstract

Local art is one of the cultural assets that holds high economic value if managed and promoted effectively. However, many local artists face challenges in marketing their work widely due to limited access and the lack of supportive digital platforms. This study aims to design and develop a mobile web application that facilitates the management and promotion of local art by integrating e-commerce features as a solution to these issues. The application enables artists to digitally market their works, such as weaving, batik, handicrafts, carvings, and paintings, while also making it easier for buyers to access local art products. The integrated e-commerce system includes features such as product catalogs, digital payment, stock management, and transaction tracking. Testing results show that the application improves the efficiency of managing local artworks and significantly expands promotional reach. With this application, it is expected that local artists can become more independent in promoting their work and increasing the economic value of local art. This research also contributes to the development of culture-based technology as part of efforts to preserve local art in the digital era.

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