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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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Rancang Bangun Website Pemesanan Alat Tulis Kantor Dengan Mengimplementasikan Waterfall Pada Toko Bokir Semarang Azis, Dimas Luthfi; Utomo, Agus Prasetyo
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 1 (2025): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i1.860

Abstract

Toko Bokir Semarang, located on Jalan Lebdosari Raya, West Semarang, provides office and school stationery, as well as photocopying services. Currently, stock management, transaction recording, and payment are still done using conventional methods. This research aims to design and develop a web system for selling office stationery using the CodeIgniter 3 Framework with the Waterfall method. The development process includes requirements analysis, system design, implementation, testing, and maintenance. Data was collected through observations and interviews to understand the workflow. The result of the research is a website with features of product management, ordering, payment, delivery, and reports. With this website, it is expected that the quality of service can improve and the operational efficiency of Toko Bokir Semarang can be well supported.
Enhancing UAV Communication Security: Multi-Label Anomaly Detection Using Machine Learning in Imbalanced Data Environments Airlangga, Gregorius; Sihombing, Denny Jean Cross; Nugroho, Oskar Ika Adi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 1 (2025): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i1.883

Abstract

Unmanned Aerial Vehicle (UAV) communication networks are increasingly vulnerable to cyber threats, including spoofing, jamming, malware, and distributed denial-of-service (DDoS) attacks. Effective anomaly detection is crucial to maintaining network integrity and operational security. This study evaluates multiple machines learning models, including Support Vector Machines, Logistic Regression, XGBoost, Gradient Boosting, and Random Forest, to detect anomalies in UAV communication networks. A real-world dataset containing 44,016 instances of network telemetry and security indicators was utilized, with each instance labeled for multiple potential anomalies. Experimental results reveal a significant class imbalance, where models achieve high accuracy (92%) but fail to detect minority class anomalies, yielding near-zero recall scores for critical cyber threats. The study highlights the limitations of traditional classifiers in imbalanced multi-label classification tasks and emphasizes the need for advanced techniques such as Synthetic Minority Over-sampling (SMOTE), cost-sensitive learning, and deep learning-based anomaly detection. The findings suggest that conventional machine learning approaches alone are insufficient for reliable anomaly detection in UAV networks, necessitating hybrid solutions that integrate multiple detection paradigms. Future work should explore adaptive ensemble learning methods and deep anomaly detection frameworks to improve recall and precision for rare cybersecurity threats.
Analisis Tingkat Pemahaman Pengguna Facebook Dalam Melindungi Data Privasi Berdasarkan Gender Di Kota Surabaya Rohman, Muhammad Kholilur; Izzuddin, Muhammad Andik; Kunaefi, Anang
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 1 (2025): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i1.851

Abstract

Social media users in Indonesia have reached 191.4 million, with Facebook accounting for 81.3% of the total. However, only 50% of users understand the security aspects that Facebook offers, despite the platform reporting 600,000 hacking attempts every day. This study aims to determine the level of understanding of Facebook users in Surabaya City in maintaining data privacy, as well as analyzing differences in user behavior based on gender. The questions in this study were designed based on the Data Detox Kit (DDK). The findings show that the factors “Control Your Smartphone Data” and “Escape The Defaults” influence data privacy concerns. Meanwhile, Surabaya people already tend to utilize Facebook's security features wisely. In the aspect of “Shift Your Settings,” Surabaya respondents showed disagreement that password negligence was the cause of data theft. Results also show that the difference in behavior between male and female users is not significant.
Analysis Digital Transformation in SMEs: Insights into Adoption Process, Employees Digital Proficiency and Concerns from Managerial Perspective Leslie, Kellie; Deu, Indasari; Eryc, E
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 1 (2025): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i1.874

Abstract

Batam City has recognized the benefits of digital transformation and has actively adopted digital technology. However, it is a misconception to view digital transformation as merely the adoption of new technologies. To digitally transform a business, SMEs need to acquire managerial capabilities and digital proficiency of employee. The need to ensure that managers and employees are equipped with the digital knowledge is essential. Delays in addressing these issues could result in a broader digital gap, putting Batam's SMEs at a disadvantage in both local and global markets. The study employs a qualitative approach through in-depth interviews with SME owners or managers. The findings show that while digital transformation improves operational efficiency, market reach, innovation, and reducing fraud, SMEs face challenges such as limited capabilities, skills gaps, and emerging market demands. The study shows that managerial skills and employee readiness are key in ensuring a successful digital transformation. This research provides a practical overview for entrepreneurs or managers to help them navigate digitalization in a dynamic environment.
Analisys of Trends And Patterns of Hololive ID Vtubers on Content Variation for Monetization Optimization Using Multiple Linear Regression Algorithm Aulia, Ananda; Iqbal, Muhammad; Khairul, K
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 1 (2025): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i1.885

Abstract

YouTube, as a new form of mass media in the advancement of increasingly sophisticated technology, caters to a diverse audience seeking daily information. Many YouTube users leverage this platform as a medium for creativity and income generation, such as through video blogs, educational videos, gaming videos, and various other content. Not all YouTubers can express themselves directly or through livestreaming; some use virtual 2D or 3D characters created with computer software, utilizing technologies such as Face Tracking and Hand Tracking. Hololive Production is a Japanese VTuber agency owned by the Japanese technology company Cover Corporation. Hololive Indonesia (Hololive ID) was established to produce Indonesian-language VTuber content and has garnered significant attention from fans in Indonesia and worldwide. VTuber content primarily revolves around video game topics, indicating a strong interest among VTuber fans in gaming-related content. Moreover, the analysis results show that multiplayer games enabling interaction among VTubers or even with viewers are highly favored, further supporting the popularity of gaming topics among VTuber enthusiasts. The Multiple Linear Regression algorithm has been widely used for sales predictions related to buyer patterns and trends. The performance measurement is influenced by the amount of data and the number of attributes.
Optimasi JST Backpropagation dengan Adaptive Learning Rate Dalam Memprediksi Hasil Panen Padi Prihandoko, P; Alkhairi, Putrama
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 1 (2025): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i1.887

Abstract

Artificial Neural Networks (ANN) with the Backpropagation algorithm have been widely applied across various domains, including data prediction tasks. However, one of the primary challenges in implementing Backpropagation is the selection of an optimal learning rate. A learning rate that is too high can lead to unstable convergence, while one that is too low can significantly slow down the training process. To address this issue, this study proposes an optimization of Backpropagation using an Adaptive Learning Rate through the implementation of the Adam optimizer. The objective of this research is to analyze the performance comparison between Standard Backpropagation and Backpropagation with the Adam optimizer in predicting rice harvest yields based on rainfall, temperature, and humidity variables. The dataset consists of 100 synthetic samples generated based on a normal distribution to resemble real-world data. The results show that the use of the Adam optimizer improves the performance of the ANN model compared to the Standard Backpropagation method. Model accuracy increased from 92.04% to 92.99%, while the values of loss, Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) decreased significantly, indicating that the model optimized with Adam is more stable and yields lower prediction errors. Therefore, Adaptive Learning Rate optimization using the Adam optimizer is proven to be effective in enhancing both the accuracy and efficiency of ANN in data prediction tasks.
Analisis Sentimen Menggunakan Metode Naive Bayes Pada Komentar Penonton YouTube Windah Basudara Berlin, Adam Putra; Febriandirza, Arafat
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.v10i2.899

Abstract

The development of social media has provided users with a space to express their opinions through comments, including on the YouTube platform. One content creator who has a large fanbase and active comment section is Windah Basudara. This study aims to analyze the sentiment of viewer comments on one of Windah Basudara’s videos using the Naive Bayes algorithm. This method was chosen due to its effectiveness in text classification and sentiment analysis. The data used consists of comments from the video titled "Mencoba NAMATIN game Keju Joget", which were collected randomly and cleaned through text preprocessing steps such as case folding, tokenizing, stopword removal, and stemming. The comments were classified into two sentiment categories: positive and negative. The analysis results show that the majority of comments carry a positive sentiment, reflecting a favorable response from viewers toward the presented content. The model evaluation demonstrates satisfactory classification results. This study is expected to contribute to understanding audience perception of YouTube content and serve as a reference for further analysis on social media platforms.
Performance Analysis of a Construction Supply Chain using Agent-Based Simulation Sihombing, Denny JC
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.v10i2.922

Abstract

Complex supply chains in the construction industry are prone to inefficiencies, including material shortages, project delays, and cost overruns, necessitating robust analytical tools. This study presents an ABM developed to simulate and analyze the performance of a three-echelon CMSSC comprising producer, distributor, and contractor agents. The model captures these entities’ dynamic interactions and autonomous behaviors, providing a nuanced understanding of system-wide performance. Key performance metrics, including total supply chain cost, average project completion time, and late penalties, were evaluated through simulation over 100 time steps.Under the defined parameters, the supply chain efficiently facilitates project completion, achieving an average completion time of 13.80 steps and incurring zero accumulated late penalties. The total supply chain cost accumulated to 205,838.00, primarily reflecting operational expenses. These findings offer practical implications for resource allocation and planning in construction supply chain management. Future work will focus on incorporating more complex agent behaviors, external uncertainties, and empirical validation to enhance the model’s realism and applicability.
E-Recrutment Sistem Pendukung Keputusan Penerimaan Pegawai BMT NU Cabang Gayam dengan Metode Simple Additive Weighting Anam, Khairul; Susanto, Adi; Baijuri, Achmad
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.v10i2.890

Abstract

In today's digital era, the employee recruitment process which is still carried out manually and subjectively is a challenge for companies, including Islamic microfinance institutions such as BMT NU Gayam Branch. A personal approach in employee selection often results in decisions that are less precise and not based on measurable criteria. To overcome this problem, this study aims to design a web-based Decision Support System (DSS) that can help the selection process for new prospective employees objectively and efficiently. This system utilizes the Simple Additive Weighting (SAW) method combined with criteria weighting using the Analytical Hierarchy Process (AHP) method. The research process was carried out using a qualitative approach, through observation, interviews, and documentation studies. Meanwhile, the system development method used is the Waterfall model, which consists of the stages of needs analysis, design, implementation, testing, and maintenance. The results of this study indicate that the application of DSS with the SAW-AHP method can improve selection accuracy, accelerate decision, making, and reduce the influence of subjectivity in the assessment of prospective employees. With this system, BMT NU Gayam Branch is expected to obtain human resources that are more in line with the needs of the organization.
Implementasi Metode Balanced Scorecard dalam Pengembangan Sistem Monitoring Pencapaian Key Performance Indicator di Astra Honda Authorized Service Station (AHASS) 01403 Kautsar, Almila Aulia; Purnama, Adi
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.v10i2.913

Abstract

This study develops a web-based monitoring system to evaluate the achievement of Key Performance Indicators (KPIs) for mechanics at Astra Honda Authorized Service Station 01403. The main objective is to provide an objective, measurable, and transparent performance assessment method. The system is designed using the Balanced Scorecard (BSC) framework with four perspectives: financial, customer, internal business process, and learning and growth. Indicator prioritization is carried out using the Urgency, Seriousness, and Growth (USG) method, ensuring each KPI aligns with the company’s strategic needs. The application was developed using the Waterfall model. The results show that the application can calculate KPI achievement scores, automatically recap performance data, and present visual dashboards that assist management in evaluating performance. The use of this system has proven to reduce manual input errors and accelerate data-driven decision-making. This system provides benefits in the form of more systematic and objective performance monitoring, and supports continuous improvement at AHASS 01403.

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