Journal : Jurnal Ilmiah Informatika dan Komputer Frequency : June and December DOI : 10.69533 (Crossref) E-ISSN : 3047-4752 Editor In Chief : Rizal Furqan Ramadhan, S.Kom., M.T Publisher : Rumah Jurnal Rizania Media Pratama Indexing : DOAJ | Google Scholar | Crossref | Garuda | Dimension Jurnal Ilmiah Informatika dan Komputer (E-ISSN : 3047-4752) is a national journal with open access that publishes research articles in the fields of Informatics Engineering and Computer Science. The scope of the journal includes Artificial Intelligence, Information Systems, Robotics, Computer Networks, Image Processing, Mobile Applications, Data Mining and other fields of informatics. The Jurnal Ilmiah Informatika dan Komputer journal is managed and published by Rumah Jurnal RIZANIA MEDIA PRATAMA. This journal is published as a means and forum for lecturers, scientists, researchers and experts in the fields of Informatics Engineering and Computer Science to publish their research results to support the Tri Dharma of Higher Education Tasks and Programs in general. The Jurnal Ilmiah Informatika dan Komputer journal is published twice a year in June and December. The journal is managed by Rumah Jurnal Rizania Media Pratama under the auspices of CV.RIZANIA MEDIA PRATAMA, legally proven by the decree of the Ministry of Law and Human Rights with the number AHU-0012457-AH.01.14 of 2024.
Implementation of Edge Detection Using the Sobel Operator on Papaya Leaf Images
Recent advances in digital image processing and computer vision have enhanced feature extraction techniques for plant identification based on leaf morphology. Edge detection is a fundamental operation that highlights intensity discontinuities corresponding to object boundaries. This study implements the Sobel operator to perform edge detection on tropical leaf images using an experimental–computational approach. The workflow involves grayscale conversion, horizontal and vertical Sobel filtering, and gradient magnitude computation implemented in Python using the OpenCV library. Experimental evaluation demonstrates that the Sobel operator effectively delineates primary leaf contours and preserves morphological consistency, despite reduced performance under non-uniform illumination and noisy conditions. These results confirm that the Sobel operator remains a reliable preprocessing technique for leaf-based feature extraction and classification, offering a computationally efficient baseline for future integration with machine learning-based plant recognition systems.
Copyright (c) 2025 Yuda Apriansyah, Nouval Khairi, Haikal Habibi Siregar, Supiyandi, Aidil Halim Lubis (Author) https://creativecommons.org/licenses/by-sa/4.0
Classification of Organic and Non-Organic Waste Using Convolutional Neural Network (CNN)
The increase in waste volume in Indonesia, which reached emergency levels in 2024, requires technological solutions that can assist in the sorting process quickly and accurately. Previous research on CNN-based waste classification generally focused on recyclable waste categories with many classes and used structured datasets, which did not adequately represent real-world waste conditions, especially organic waste, which has more varied shapes and conditions. Based on this gap, this study proposes a Convolutional Neural Network (CNN) model for classifying two main categories—organic and inorganic—using 25,077 images and direct testing on field samples. The model was trained using the Adam optimizer and categorical crossentropy loss. The results show high accuracy for inorganic waste (96%), but lower accuracy for organic waste (62%) due to the complexity of texture and natural damage. This study contributes to the field of informatics through the application of more applicable and realistic deep learning for automatic waste sorting systems, as well as opening up opportunities for the development of model architectures that are more adaptive to waste conditions in the actual environment.
Copyright (c) 2025 Muhammad Farhan, Mhd Farhan Aditiya, Dafa Ikhwanu Shafa, Supiyandi, Aidil Halim Lubis (Author) https://creativecommons.org/licenses/by-sa/4.0
Real-Time Driver Microsleep Detection Using Lightweight MobileViT and Haar Cascade
Microsleep is a brief and involuntary loss of awareness that increases the risk of driving accidents. This study proposes a real-time microsleep detection system using Haar Cascade for eye localization and the lightweight MobileViT-XXS model for eye-state classification. The model was trained on a public dataset and achieved a training accuracy of 99.49%, a test accuracy of 98%, and a real-time accuracy of 90–94%. A microsleep event is detected when the eyes remain closed for ≥ 2 seconds. While the method performs well under controlled conditions, real-time testing revealed technical limitations such as sensitivity to lighting variation, non-frontal head pose, and motion, which affect detection stability and represent common robust-vision challenges. Despite these limitations, the system runs efficiently on CPU-only hardware and demonstrates strong potential as a lightweight early-warning system to support driving safety. Future research may explore expanding dataset diversity, improving environmental adaptation, and deploying the system on embedded or mobile platforms to enhance robustness and scalability.
Copyright (c) 2025 Syahada Mawarda Hutagalung, Muhammad Alfariz Rasyid, Supiyandi, Aidil Halim Lubis (Author) https://creativecommons.org/licenses/by-sa/4.0
Optimization of Employee Task Assignments Using the Hungarian Method and POM-QM at Serupa Cafe
This study aims to optimize employee task assignments at Serupa Café, which faces issues of workload imbalance and inefficient task completion times. The research gap lies in the limited application of algorithm-based optimization methods within human resource management in the food and beverage service sector. To address this, the study applies the Hungarian Method, an algorithmic approach with a time complexity of O(n³), to determine the most efficient pairing between employees and tasks. The computation and validation processes were carried out using the POM-QM for Windows software as a quantitative analysis tool. The results indicate that the optimal assignment configuration achieved a total completion time of 85 minutes, with complete consistency between manual and software-generated results. System testing demonstrated high computational efficiency and no logical errors during data processing. Therefore, this study concludes that integrating the Hungarian Method with POM-QM significantly enhances operational performance and contributes to the application of informatics techniques for optimizing human resource management within the service industry.
Copyright (c) 2025 Tirsa Ninia Lina, Matheus Supriyanto Rumetna, Jeni Karay, Charliany Hetharia, Jalmijn Tindage (Author) https://creativecommons.org/licenses/by-sa/4.0
Optimization of the Internal Quality Audit Process Through the Development of an Integrated Information System
The Internal Quality Audit (IQA) process is a crucial element for maintaining the quality of higher education. However, its implementation at STIMIK Tunas Bangsa Banjarnegara faces challenges, particularly with manual documentation. The use of paper-based forms, decentralized recording of findings, and separate reports often cause delays, data duplication, and difficulty in tracking follow-up actions. This research aims to develop an integrated information system to optimize the IQA process and improve the ease of documentation up to the findings report stage. This study uses a qualitative approach with a case study design. Data was collected through observation to understand the manual workflow and interviews with relevant parties to gather system requirements. The system was developed using the Prototype method and built with the PHP programming language and a MySQL database. The research resulted in a system named SIMATIKA (Sistem Audit Mutu Internal Kampus), all of whose features function well based on BlackBox Testing. These features include audit period management, indicator management, user configuration, and audit assignment. The system also received a score of 86% from a user questionnaire, indicating very good feasibility and acceptance. Thus, SIMATIKA successfully optimizes the IQA process at the campus.
Copyright (c) 2025 Febri Sarif Hidayat, Khalimaturofi’ah, Heni Rahmawati (Author) https://creativecommons.org/licenses/by-sa/4.0
Implementation Of A Website-Based Recording And Reporting System For Mosque Construction Donations
Managing donation funds requires transparency and accountability to maintain trust and ensure proper use of funds. This study aims to implement a web-based fund recording and reporting information system to assist in the efficient and transparent financial management of the Al-Ikhlas Mosque. The problems faced by the Al-Ikhlas Mosque management include manual recording that is prone to loss, miscalculations, and a lack of transparency to residents. To address these issues, a "Website-Based Recording and Reporting System for Development Donations at the Al-Ikhlas Mosque" was developed. The system development method used is the Waterfall method, with stages of analysis, design, implementation, testing, and maintenance. Based on the results of the system trial using Black Box Testing and Likert Scale calculations, the manager received a score of 81.31%, while the community test yielded a score of 81.63%. This information system facilitates management in managing donation funds and facilitates public access to financial reports. Therefore, this information system can be implemented to accelerate and improve the efficiency of the donation fund management process at the Al-Ikhlas Wirasari Mosque.
Copyright (c) 2025 Rurianto, Yuniar Laeli Nur Faizah, Purwanto (Author) https://creativecommons.org/licenses/by-sa/4.0
Web-Based Student Learning Activities and Development Information System Using Pieces Analysis at OSI Tutoring Center
Tutoring (BIMBEL) is a form of non-formal education that plays a role in improving students' academic achievements. Oemah Sinau Indonesia (OSI) in Banjarnegara still uses Excel and physical reports to record learning activities and student development, making the process of searching and distributing data less efficient. This study aims to build a web-based information system for learning activities and student development using the PIECES analysis as a system evaluation method at OSI tutoring. The system development uses the Waterfall method with PHP programming language, Laravel framework, and data storage based on Firebase Realtime Database. System testing is conducted using Black-box testing to ensure the system functions according to user needs, and all 10 test scenarios were successfully executed with a "successful" status. System feasibility evaluation uses PIECES analysis (Performance, Information, Economy, Control, Efficiency, Service) was conducted through the distribution of questionnaires to 11 respondents consisting of admins, mentors, and student guardians. The evaluation results showed an average feasibility score of 95%, categorized as very feasible. Specifically, the Performance and Efficiency aspects received the highest scores of 97%, indicating an improvement in the speed and ease of administrative processes as well as real-time access to information. Based on the testing and analysis results, this system is considered effective in replacing manual record-keeping, improving data accuracy, strengthening access control, and facilitating communication between the tutoring center and student guardians. Thus, this information system is proven feasible to be used as a solution for digitalizing learning administration at OSI.
Copyright (c) 2025 Anugrah Septiani, Heni Rahmawati, Luthfi Nur Azizah (Author) https://creativecommons.org/licenses/by-sa/4.0
Application of the Hungarian Algorithm for Workforce Task Optimization in Mobile Device Repair Operations
An imbalance in task assignments within a business unit can decrease efficiency and extend job completion time. To address this issue, an optimization approach is required to allocate tasks effectively and minimize total working time. This study analyzes the application of the Hungarian Method to optimize employee assignments at Konter Bintang Sorong, aiming to achieve the most efficient mobile phone repair time. A quantitative approach was employed using the Hungarian algorithm implemented through POM-QM for Windows version 5. Data were collected through observation, interviews, and documentation related to repair durations for each task type. The findings show that the Hungarian Method produced the most efficient task allocation: employee Willi repaired connectors in 25 minutes, Aksa handled software issues in 60 minutes, and Fadli repaired LCD components in 10 minutes. These results indicate that the Hungarian Method effectively reduces average repair time and increases the number of devices serviced within a given period. Thus, it serves as an effective optimization tool for improving task distribution, operational efficiency, and customer satisfaction.
Copyright (c) 2025 Matheus Supriyanto Rumetna, Tirsa Ninia Lina, Jeni Karay, Agustinus Budi Santoso, Wiesje Ferdinandus (Author) https://creativecommons.org/licenses/by-sa/4.0
Android Based Activity Information Application in Surabaya
Surabaya is the capital of East Java which also became the second metropolitan city after Jakarta. As one of the largest cities in Indonesia, Surabaya often holds major events. During the past year counted already dozens or even hundreds of activities held in Surabaya. Usually events are held in order to commemorate the anniversary of the city and other celebrate. The usual events include cultural fairs, culinary festivals, and job fair. Android is an open source operating system that allows software to be freely modified and distributed by device makers and app developers. Therefore the author has the idea to utilize android technology as one of the media information by creating an application. This application is made to publish an events to be held in Surabaya, which is titled "Application Information of Events in Surabaya Based Android".
Copyright (c) 2025 Tommy Nuril Huda, Pamudi, David Hermansyah (Author) https://creativecommons.org/licenses/by-sa/4.0
Property Product Recommendation System as a Marketing Strategy at PT Java Abadi Sejahtera
This study addresses the challenges faced by PT. Java Abadi Sejahtera in matching customer needs with available property products and the frequent data loss caused by manual recording processes. A web-based recommendation system was developed using the Profile Matching method, where criteria such as property type, location, size, price, payment method, and facilities are weighted according to their importance and processed using GAP calculations to determine the suitability between customer requirements and product data. Black box and white box testing results indicate that the system functions correctly and is able to process product data, customer member data, and follow-up data accurately. The system generates ranked product recommendations based on suitability calculations. The findings demonstrate that the recommendation system effectively supports marketing decision-making, improves the efficiency of the matching process, and enhances the overall quality of marketing strategies implemented by the company.
Copyright (c) 2025 Siti Munawaroh, Achmad Choiron, Ratna Nur Tiara Shanty (Author) https://creativecommons.org/licenses/by-sa/4.0
Decision Support System For Scholarship Candidate Selection
System used by the university. Soetomo surabaya for the selection of prospective students who are eligible to receive a scholarship is still using the manual way. Given the enormous number of submissions by scholarship recipients will make it difficult for universities in selecting students who are eligible to receive scholarships. Therefore it is necessary that there is a system that can be used as supporting decision-making to determine the students who are eligible to get a scholarship at the University Dr Soetomo Surabaya in order to facilitate the University. The problem that occurs is the absence of a system used for the selection process of scholarship recipients at Dr. University. Soetomo Surabaya. This selection is done using Analytical Hierarcy Process (AHP) method, it will simplify the way the system to perform the selection, the work concept of Analytical Hierarcy Process (AHP) is able to determine the best alternative choice in determining a goal. Analytical Hierarcy Process (AHP) will determine the right student to get a scholarship viewed from several attributes that exist. With this decision support system, it will facilitate the University's work to determine the students who are eligible for a scholarship in terms of some existing attributes. The result of this decision support system is the obtaining of scholarship recommendation data in the form of value with percent form where this value which will be the management consideration to determine the scholarship recipient.
Copyright (c) 2025 Emilyati Lailatul Qodriyah, Dwi Cahyono, Ratna Nur Tiara Shanty (Author) https://creativecommons.org/licenses/by-sa/4.0
Adaptive Ensemble Learning for Real-Time Anomaly Detection in 5G Networks
5G networks enable ultra-high speed, low latency, and massive connectivity for critical applications such as IoT, autonomous vehicles, and digital healthcare. However, the complexity and high traffic volume in 5G architectures increase the risk of anomalies that threaten service quality and security. This study addresses the problem by proposing a real-time anomaly detection framework based on streaming data and ensemble learning algorithms. Network traffic is processed through a stream processing platform, while ensemble models such as Random Forest, Gradient Boosting, and Voting Classifier are applied to improve detection accuracy. Experimental results show that the proposed system achieves high accuracy and low latency in detecting anomalies, including Distributed Denial of Service (DDoS) attacks and technical failures. This research contributes a scalable and effective solution to enhance 5G network security and reliability, advancing the field of cybersecurity and network analytics.
Copyright (c) 2025 Agus Dendi Rachmatsyah, Benny Wijaya, Syafrul Irawadi, Ari Amir Al-Kodri, lili Indah Sari (Author) https://creativecommons.org/licenses/by-sa/4.0
Generating Unimodular Matrix in Python for Solving Systems of Linear Equations
Linear equation systems with integer solutions are widely used in modern computing fields such as cryptography and optimization, but conventional methods often produce inaccurate decimal solutions. To address this issue, this research developed a Python program based on NumPy that can efficiently generate unimodular matrices. The method involves three main stages: initializing an upper triangular matrix with diagonal elements of ±1, filling non-diagonal elements with random integers, and transforming the matrix through elementary row operations. Test results show that the program successfully generates unimodular matrices of sizes 4×4 to 9×9 with perfect accuracy (determinant exactly ±1), an average computation time of 0.5 seconds for a 4×4 matrix, and efficient memory usage (under 20 MB). The solutions to the linear equations are always exact integers, meeting the requirements for high-precision computation. This implementation not only provides a practical solution for integer linear equation systems but also opens up opportunities for applications in cryptographic algorithm development and optimization techniques that require absolute precision. The findings of this research confirm that numerical computation approaches can produce both accurate and efficient mathematical solutions.
Copyright (c) 2025 Muhammad Irfan Mustakim, Diny Syarifah Sany (Author) https://creativecommons.org/licenses/by-sa/4.0
Matrix-Based Computation in Informatics: A Conceptual Review of Linear Algebra Applications
Linear algebra and matrices play a critical role in informatics, especially in understanding multidimensional data and computational processes. This study aims to explore the fundamental concepts and practical applications of linear algebra and matrices using a descriptive qualitative method with a literature review approach. Data sources include textbooks, international journals, and recent academic articles. The findings reveal that concepts such as vector spaces, determinants, eigenvalues, and matrix transformations are widely applied in machine learning, image processing, and modern data analysis. Techniques like Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) are proven effective for dimensionality reduction and feature extraction. The study concludes that linear algebra acts as a bridge between mathematical theory and informatics applications, serving as a foundation for developing intelligent systems and algorithms. This research is expected to serve as a conceptual reference for students and scholars in the field of information technology.
Copyright (c) 2025 Muhammad Nazar Aufa Nazar, Diny Syarifah Sany Diny (Author) https://creativecommons.org/licenses/by-sa/4.0
Matrix in Linear Algebra for Modern Computational Solutions
This study aims to examine the basic concepts of matrix in linear algebra through conceptual and computational approaches. Matrix are understood not only as computational tools, but also as representations of linear transformations and relationships in vector spaces. The method used is a combination of theoretical analysis and numerical experiments using NumPy and SymPy. A case study was conducted by constructing a distance matrix between 20 districts in Cianjur in the form of a 20x20 symmetric matrix. The results show that the determinant of the matrix reflects the stability of the spatial system, while the inverse is useful for solving systems of linear equations. Eigenvalue and eigenvector analysis identified the most strategically located districts within the network. Additionally, the farthest distance between districts was successfully determined and can be utilized for more efficient transportation route planning. In conclusion, a conceptual and computational understanding of matrix structure is crucial, not only in linear algebra theory but also in practical applications such as regional planning and transportation network management.
Copyright (c) 2025 Miral Setiawan, Diny Syarifah Sany (Author) https://creativecommons.org/licenses/by-sa/4.0
Development of an Integrated Information System for Monitoring and Validation of Health Workers Practice Licenses (STR) in Healthcare Facilities
The management of Health Workers ' Registration Certificates (STR) in Indonesia faces challenges such as manual processing, data fragmentation, and the risk of expired or fake STR, which can endanger patient safety and hinder supervision by health facilities and authorities. This study developed a web-based information system using the Waterfall approach, through the stages of needs analysis, design, implementation, testing (Black Box and User Acceptance Testing), and deployment on Anwar Medika University servers, with centralized database features, automatic notifications, QR code verification, and compliance reports. As a result, the system improved efficiency, accuracy, and transparency, with 87% of respondents rating the intuitive interface and service satisfactory, 89% felt the time efficiency, and 95% considered the system easy to use. The system is recommended to be widely implemented, integrated with the national e-Health, with regular maintenance and training of users to support the management of accountable and qualified health personnel.
Copyright (c) 2025 Rony Kriswibowo, Agung Budi Setyawan, Rusina Widha Febriana (Author) https://creativecommons.org/licenses/by-sa/4.0
Matrix: Basic Concepts And Practical Applications In Daily Life
Matrix, as a fundamental mathematical concept, have crucial applications in computer science. This study analyzes: the basic structure of matrices (definition, types, addition-multiplication-inverse operations), and their implementation in computational fields, including: digital image processing (pixel representation, image transformation), intelligent systems (matrix-based neural networks), data security (matrix encryption), and network optimization (routing algorithms). A combination of literature review and case analysis reveals that understanding matrices is the backbone of modern computing, particularly in the development of machine learning and computer vision. Findings indicate a gap between conventional matrix theory and the demands of large-scale computing in industry. This study recommends integrating examples of computer science applications into matrix education to prepare digital talent.
Copyright (c) 2025 Muhamad Dimas Aprijal, Diny Syarifah (Author) https://creativecommons.org/licenses/by-sa/4.0
Linear Algebra for Modern Statistics: Efficiency and Interpretability Challenges in Regression and PCA
The development of modern statistics faces the challenge of high-dimensional data complexity, which requires an efficient yet interpretable approach. Linear algebra offers a solution through matrix representation, but its limitations in non-linear contexts and high-dimensional interpretation need to be examined in greater depth. This study analyzes algebraic methods through case studies of linear regression (normal equation solutions) and PCA (eigen decomposition), tested on synthetic datasets and MNIST. The results show: (1) a 40% computational acceleration in matrix-based regression, (2) PCA successfully reduces the MNIST dimension to 3 main components (retaining 85% of the variance), but a survey reveals that 73% of practitioners have difficulty interpreting high-dimensional components. Despite its efficiency advantages, algebraic methods require further development through hybrid approaches (kernel PCA) and interpretable techniques to address limitations in linearity and high-dimensional complexity.
Copyright (c) 2025 Khoerul Rahman, Diny Syarifah Sany (Author) https://creativecommons.org/licenses/by-sa/4.0
Linear Algebra in Geometric Transformations
This study aims to deeply examine the role of Linear Algebra in geometric transformation through a combined qualitative-quantitative approach. By combining systematic literature studies, content analysis, GeoGebra-based virtual laboratory experiments, and field case studies, this study found that transformation matrices, vector spaces, and orthogonal projections are the main foundations in representing and manipulating geometric objects precisely. The results show that a deep understanding of Linear Algebra improves students' spatial visualization abilities by 34% and the efficiency of Augmented Reality (AR) application design by up to 27%.Startup NextVision AR Lab (Jl. Gegerkalong Hilir, Bandung) – cloud-based AR specialist for manufacturing & education. Problem Rendering high-detail 3D objects (>100k vertices) on a Snapdragon XR2 headset frequently drops frames. Hypothesis Optimizing the matrix transformation algorithms (model-view-projection, normal, pose) can reduce GPU load by up to 30% without compromising visual fidelity.
Copyright (c) 2025 Raihan Faisal Dzikra, Diny Syarifah (Author) https://creativecommons.org/licenses/by-sa/4.0
The Utilization of Exam Browser Application as Assessment Media at Madrasah Tsanawiyah Islamiyah Trimoharjo
This study aims to measure the level of effectiveness of the Exam Browser application as a tool in the learning evaluation process in Islamiyah Trimoharjo. This research was conducted using a quantitative descriptive method. The subjects in this study are students of MTs Islamiyah Trmoharjo. The data in this study is in the form of answers from questionnaires. The results of the study show that most of the students from MTs Islamiyah Trimoharjo consider this application to provide convenience in the implementation of the exam. They see that the application can increase focus and help improve discipline and honesty in working on problems. While most students can overcome difficulties in accessing the app, technical constraints such as errors, lag, and performance are still concerns. The exambro application used for exams is accepted by both teachers and students because it facilitates the implementation of exams with user-friendly features, question randomization and real-time monitoring, obstacles that occur during the use of this application by teachers and students only on technical issues such as unstable internet connections and device compatibility, and positive perceptions from teachers and students regarding the use of the application.
Copyright (c) 2025 Dwi Prayitno, Femas Adi Prakasa, Nirma, Thoha Firdaus (Author) https://creativecommons.org/licenses/by-sa/4.0
Al-Istiqomah Islamic Boarding School Academic Information System Based on the Waterfall Model
This article discusses the development of a web-based Academic Information System (AIS) for Istiqomah Islamic Boarding School using the Laravel framework. The main objective of this study is to create an integrated and efficient system to manage student academic data, including grades, report cards, attendance, and information about both instructors and students at Al-Istiqomah Islamic Boarding School. The research method used is Research and Development (R&D) with a waterfall approach, starting from requirements analysis, system design, implementation, and testing. Data collection was carried out through interviews with pesantren administrative staff and observation of ongoing academic processes. The findings of the study show that the AIS developed successfully facilitates the digital management of academic data, reducing reliance on manual note-taking, which is prone to errors and slow. The system provides essential modules such as student data management, grade input, attendance recapitulation, student financial reports, and class schedules. System testing using the black box testing method shows that all functions are operating well and meeting the needs of the user. Thus, this system is expected to increase efficiency and accuracy in the management of academic information, as well as support better decision-making at the Istiqomah Islamic Boarding School.
Copyright (c) 2025 Thoha Firdaus, Muhammad Iksannudin, Muhammad Naufal Jamil Al Basyari Sutoyo, Deri Feriyansah (Author) https://creativecommons.org/licenses/by-sa/4.0
Development Digital Payment Application Using Next.js and Xendit with Prototyping-Agile Approach
This research presents the development of a comprehensive digital payment application for PT. Fortuna Sada Nioga using the Next.js framework and Xendit payment gateway. The primary objective was to develop an automated digital system that supports multiple payment methods and provides real-time transaction monitoring to replace manual payment processes. The research employed a hybrid methodology that combines a Prototyping approach for concept validation with Agile Scrum methodology for systematic development. The main outcomes demonstrate the successful implementation of AES-256-GCM encryption, rate limiting mechanisms, input validation, and webhook integration with comprehensive security testing validation. Performance testing showed optimal response times with an average load time of less than 2 seconds for website browsing and the capability to handle up to 100 concurrent users without performance degradation. The system includes customer order management, multi-payment gateway integration, an admin dashboard with role-based access control, and real-time order tracking features. The conclusions indicate that combining Next.js with Xendit provides a robust, secure, and scalable foundation for digital payment systems, while the hybrid Prototyping-Agile methodology proves effective for complex system development within constrained timeframes.
Copyright (c) 2025 Angga Rakhmansyah, Abdul Jabbar, Muhammad Ramzy, Wasis Haryono (Author) https://creativecommons.org/licenses/by-sa/4.0
AI and Blockchain in Cybersecurity: A Sustainable Approach to Protecting Digital Assets
The integration of Artificial Intelligence (AI) and Blockchain technology is revolutionizing cybersecurity by providing innovative, data-driven, and decentralized solutions. AI, through machine learning and deep learning, enables rapid and accurate detection of cyber threats such as malware, phishing, and zero-day attacks. Meanwhile, Blockchain ensures data integrity through its decentralized and tamper-resistant architecture, making it effective in securing sensitive information in sectors like healthcare, finance, and defense. This study explores how the convergence of AI and Blockchain can enhance cybersecurity and proposes sustainable strategies for a secure digital future. Real-world applications, such as the collaboration between the UK's National Health Service (NHS) and Google DeepMind, demonstrate the practical benefits of this integration. However, challenges remain, including data privacy concerns, infrastructure limitations, a shortage of skilled professionals, and regulatory uncertainties. The study recommends interdisciplinary research, the development of hybrid AI-Blockchain models, implementation in critical infrastructure, and strong public–private partnerships to build a resilient and scalable digital ecosystem.
Copyright (c) 2025 Sheik Mohamed, Nirmala.M, Theerka.N, Evans Dennison.J https://creativecommons.org/licenses/by-sa/4.0/
Implementasi Algoritma Decision Tree Untuk Prediksi Efisiensi Biaya Bensin Kendaraan Bermotor Parenggean Menuju Palangkaraya
Penelitian ini bertujuan untuk menerapkan algoritma Decision Tree dalam memprediksi efisiensi biaya bensin kendaraan bermotor yang melakukan perjalanan dari Parenggean menuju Palangka raya. Dengan meningkatnya kebutuhan transportasi dan pengeluaran bahan bakar, penting untuk memiliki model yang dapat memprediksi dan mengoptimalkan penggunaan bahan bakar, sehingga dapat mengurangi biaya operasional. Algoritma Decision Tree, terutama varian C4.5, telah terbukti efektif dalam klasifikasi dan prediksi berdasarkan data historis. Penelitian ini menggunakan data mengenai jenis kendaraan, jarak tempuh, serta kondisi jalan untuk membangun model prediksi. Metode pengumpulan data dilakukan melalui observasi langsung, di mana data yang dikumpulkan mencakup informasi penting untuk analisis. Hasil penelitian menunjukkan bahwa algoritma ini mampu mencapai tingkat akurasi hingga 90%, yang menandakan efektivitasnya dalam mengidentifikasi pola konsumsi bahan bakar. Visualisasi pohon keputusan memberikan wawasan mendalam mengenai hubungan antara variabel yang mempengaruhi efisiensi biaya bensin. Temuan ini diharapkan dapat menjadi acuan bagi pengemudi dan perusahaan transportasi dalam merencanakan perjalanan dan mengelola biaya bahan bakar secara lebih efisien.
Copyright (c) 2024 Amar Filonga Septaraja, Kevin Joannes, Muhammad Roeyyan Radhi, Jadiaman Parhusip https://creativecommons.org/licenses/by-sa/4.0
Manfaat Penggunaan Metode Statistika dalam Peningkatan Keamanan dan Kerahasiaan Informasi Digital
Era digital telah membawa tantangan baru dalam menjaga keamanan dan kerahasiaan informasi digital. Ancaman seperti peretasan, kebocoran data, dan serangan malware menuntut solusi yang lebih adaptif dan efektif. Penelitian ini mengeksplorasi penerapan metode statistika dalam meningkatkan keamanan informasi digital melalui teknik seperti deteksi anomali, analisis distribusi, dan pembelajaran mesin. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan analisis deskriptif dan inferensial. Hasil penelitian menunjukkan bahwa metode statistika terbukti efektif dalam mengidentifikasi aktivitas mencurigakan, memperkuat algoritma enkripsi, dan memprediksi ancaman siber berdasarkan pola historis. Teknik ini juga meningkatkan kecepatan deteksi dan akurasi sistem keamanan, serta mendukung penilaian risiko yang lebih akurat. Integrasi metode statistika dengan kecerdasan buatan dan pembelajaran mesin diharapkan dapat memperkuat sistem keamanan informasi yang lebih adaptif dan tangguh di masa depan.
Copyright (c) 2024 Nurviani Futri, Jadiaman Parhusip https://creativecommons.org/licenses/by-sa/4.0
Implementasi Komunikasi Peer-to-Peer dengan Mengembangkan Aplikasi Menggambar Kolaboratif
Dengan berkembangnya teknologi dan internet yang semakin pesat, kolaborasi jarak jauh telah menjadi kebutuhan yang sangat penting, terutama dalam bidang seni dan kreativitas. Pengembangan aplikasi yang mendukung kolaborasi secara real time memuungkinkan individu untuk berinteraksi secara efektif meskipun terpisah oleh jarak. Untuk itu, penelitian dilakukan dengan tujuan untuk mengembangkan aplikasi menggambar kolaboratif yang berbasis Peer-to-Peer (P2P). Aplikasi dikembangkan menggunakan bahasa pemrograman Python, dengan modul Tkinter untuk antarmuka grafis yang user-friendly, dan socket programming untuk komunikasi antar pengguna melalui jaringan. Dalam penelitian ini, metodologi yang digunakan mencakup studi literatur, implementasi yang dipelajari dalam pembangunan aplikasi, dan mengevaluasi hasil akhir program. Hasil penelitian menunjukkan bahwa aplikasi berhasil mengimplementasikan komunikasi P2P dengan baik dan memungkinkan pengguna untuk menggambar secara bersama-sama dengan pengguna lainnya secara real time tanpa adanya gangguan seperti tabrakan atau masalah yang signifikan. Namun, terdapat beberapa keterbatasan yang telah diidentifikasi, antara lain seperti proses penemuan peer yang masih dilakukan secara manual dan tantangan terkait skalabilitas pada jaringan ketika jumlah pengguna melebihi dari tiga orang atau pengguna. Meskipun demikian, aplikasi ini memberikan wawasan yang bermanfaat mengenai potensi teknologi P2P dalam aplikasi kolaborasi kreatif, serta membuka peluang untuk pengembangan lebih lanjut untuk meningkatkan performa dan memperluas kapasitas aplikasi agar dapat digunakan oleh lebih banyak pengguna.
Copyright (c) 2024 Verrel Novendra Sulu, David Tulus Halomoan Haryanto, Anantaujas Cipta Adinata, Sibgah Rabbani Kusuma https://creativecommons.org/licenses/by-sa/4.0
Penerapan Kurva Normal Dalam Analisis Tingkat Anak Putus Sekolah di Kalimantan Tengah
Penelitian ini bertujuan untuk menganalisis tingkat anak putus sekolah di Kalimantan Tengah dengan pendekatan distribusi normal, berfokus pada data rata-rata jumlah kasus yang terjadi di wilayah tersebut. Dalam era teknologi informasi, Teknik Informatika memiliki peran penting dalam pengolahan dan analisis data untuk mengungkap pola tersembunyi di balik fenomena sosial. Penelitian ini memanfaatkan teknik statistik dan distribusi normal untuk mengevaluasi penyebaran kasus putus sekolah berdasarkan variabel usia, jenis kelamin, dan faktor sosial ekonomi. Data diperoleh dari sumber pemerintah dan lembaga pendidikan, kemudian dianalisis untuk memahami karakteristik anak-anak yang terdampak. Distribusi normal digunakan untuk mengidentifikasi pola penyebaran dan faktor signifikan yang memengaruhi angka putus sekolah di provinsi tersebut. Hasil penelitian ini diharapkan memberikan gambaran yang lebih jelas mengenai permasalahan putus sekolah serta rekomendasi kebijakan yang tepat. Penelitian ini juga menyoroti kontribusi Teknik Informatika dalam menganalisis isu-isu sosial dan pendidikan di Indonesia.
Copyright (c) 2024 Muhamad Ridwan, Alif Mayrossi Berlison, Thomas Re Manuel Putra Sihombing, Jadiaman Parhusip https://creativecommons.org/licenses/by-sa/4.0
Pengembangan Kurikulum Berbasis Informatika untuk Memenuhi Kebutuhan Industri di Era Digital
Penelitian ini bertujuan untuk menganalisis kebutuhan industri di era digital dalam upaya mengembangkan kurikulum yang relevan dengan tuntutan zaman. Penelitian ini menggunakan metode campuran, yakni survei terhadap 50 perusahaan berbasis digital dan wawancara mendalam dengan 10 pakar pendidikan. Survei dirancang untuk mengidentifikasi keterampilan utama yang diperlukan oleh industri, seperti literasi data, penguasaan teknologi, pemecahan masalah kompleks, dan kreativitas, sedangkan wawancara bertujuan menggali tantangan serta peluang dalam implementasi kurikulum berbasis teknologi. Hasil survei menunjukkan bahwa literasi data menjadi prioritas utama dengan persentase 85%, diikuti penguasaan teknologi sebesar 78%, sementara kreativitas dan kolaborasi lintas disiplin meskipun di posisi lebih rendah, tetap dianggap signifikan oleh lebih dari 50% responden. Hasil wawancara mengungkap tiga tantangan utama, yaitu keterbatasan infrastruktur teknologi di daerah terpencil, kurangnya pelatihan bagi tenaga pengajar dalam mengintegrasikan teknologi, dan kesenjangan antara kurikulum yang terlalu teoritis dengan kebutuhan praktis industri. Analisis data menunjukkan bahwa integrasi teknologi digital, pembelajaran berbasis proyek, dan kolaborasi lintas disiplin adalah pendekatan yang diperlukan untuk mencetak lulusan yang kompetitif. Temuan ini relevan dengan literatur terkait keterampilan abad ke-21 dan tuntutan Revolusi Industri 4.0, yang menekankan pentingnya berpikir kritis, kreativitas, dan literasi digital. Penelitian ini menyoroti perlunya sinergi antara institusi pendidikan, pemerintah, dan industri untuk merancang kurikulum adaptif yang mendukung pembelajaran seumur hidup dan meningkatkan daya saing tenaga kerja.
Copyright (c) 2024 Rizqi Fajari, Bayu Saputra, Alif Mayrossi Berlinson, Jadiaman Parhusip https://creativecommons.org/licenses/by-sa/4.0
Proporsi Individu yang Memiliki Telepon Genggam dalam Perspektif Teknologi Informasi dan Komunikasi
Penelitian ini menganalisis proporsi kepemilikan telepon genggam di Pulau Kalimantan dan Jawa selama 2021–2023 dengan pendekatan kuantitatif berbasis data sekunder dari Badan Pusat Statistik. Telepon genggam, khususnya smartphone, semakin esensial dalam mendukung aktivitas sosial, pendidikan, dan komunikasi. Penelitian ini menunjukkan peningkatan signifikan penggunaan telepon genggam di Indonesia, terutama di kalangan mahasiswa, yang mencakup 85% dari total pengguna internet. Namun, permasalahan yang teridentifikasi adalah kurangnya kajian komparatif antardaerah terkait dinamika kepemilikan perangkat ini dalam konteks kesenjangan digital. Hasil penelitian menunjukkan bahwa Kalimantan Timur mencatat persentase tertinggi pada 2023 (81,75%), sementara Kalimantan Selatan mengalami penurunan. Di Jawa, DKI Jakarta mengalami peningkatan signifikan dari 67,82% (2021) menjadi 82,47% (2023). Studi ini memberikan pemahaman tentang ketimpangan akses teknologi serta kontribusinya terhadap pengembangan kebijakan di bidang Teknologi Informasi dan Komunikasi (TIK).
Copyright (c) 2024 Reynaldi Dwi Saputra, Dinda Marsyanadya Putri, Jadiaman Parhusip https://creativecommons.org/licenses/by-sa/4.0
Analisis Penggunaan Teknologi Informasi Sebagai Sumber Belajar
Penggunaan teknologi informasi dalam pendidikan menjadi kebutuhan penting untuk meningkatkan kualitas pembelajaran. Namun, efektivitasnya masih menghadapi tantangan seperti rendahnya literasi digital, kurangnya pelatihan guru, dan keterbatasan infrastruktur. Penelitian ini bertujuan mengevaluasi intensitas penggunaan sumber belajar berbasis teknologi informasi oleh guru PPKn serta hubungannya dengan kompetensi profesional mereka di MGMP Kota Malang. Penelitian menggunakan pendekatan kuantitatif dengan desain deskriptif. Populasi penelitian adalah 46 guru SMA PPKn di MGMP Kota Malang, dengan teknik total sampling. Data dikumpulkan melalui angket tertutup berskala Likert dan dianalisis menggunakan SPSS untuk deskripsi statistik dan korelasi Pearson. Hasil penelitian menunjukkan intensitas penggunaan sumber belajar berbasis teknologi informasi berada pada kategori sedang hingga tinggi. Skor rata-rata mencerminkan pemanfaatan yang cukup baik. Analisis korelasi Pearson menunjukkan hubungan positif yang signifikan antara penggunaan teknologi informasi dan kompetensi profesional guru (r = 0,68, p < 0,05), yang berarti peningkatan pemanfaatan teknologi informasi mendukung peningkatan kompetensi profesional. Penelitian ini menyoroti pentingnya pelatihan teknologi dan peningkatan literasi digital guru untuk pembelajaran berbasis teknologi. Temuan ini memberikan rekomendasi bagi pengambil kebijakan untuk memprioritaskan pengembangan infrastruktur serta program pelatihan guru berbasis teknologi.
Copyright (c) 2024 Claudy Queen Pirera, Meilinda Xanderina, Yulia Patimah, Jadiaman Parhusip https://creativecommons.org/licenses/by-sa/4.0