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All Journal Jurnal Teknologi dan Informasi Prosiding National Conference for Community Service Project JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Jurnal E-Komtek JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JITU : Journal Informatic Technology And Communication Journal of Innovation Information Technology and Application (JINITA) Telcomatics Journal of Information System and Technology (JOINT) STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Conference on Management, Business, Innovation, Education and Social Sciences (CoMBInES) Conference on Business, Social Sciences and Technology (CoNeScINTech) Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Nusantara Journal of Multidisciplinary Science Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
Gautama Wijaya
Universitas Internasional Batam
Religion Aerospace Engineering Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Ketersediaan Tinggi Website menggunakan Penskalaan Otomatis dan Penyeimbang Beban AWS Haeruddin, Haeruddin; Andik Yulianto; Stefanus Eko Prasetyo; Gautama Wijaya; Dominggo Givarel
Telcomatics Vol. 10 No. 1 (2025)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v10i1.10951

Abstract

The rapid development of information technology requires digital service systems to have high performance and optimal availability. One of the main challenges in managing web-based services is the system's ability to deal with an unpredictable surge in the number of users. If not anticipated, this can cause a decrease in performance and even detrimental downtime. This study aims to analyze and implement the concept of auto scaling and load balancing in an effort to improve the performance and availability of web-based services. Auto scaling functions to automatically adjust the number of server resources according to workload needs, while load balancing plays a role in distributing network traffic evenly to several servers. The research method used is an experiment, by implementing and testing service performance before and after the implementation of auto scaling and load balancing. The test results show that the combination of the two technologies is able to increase the speed of service response, reduce server load, and maintain optimal service availability. This research is expected to be a reference in the development of reliable and efficient cloud-based systems.
Comparison of DES, AES, IDEA RC4 and Blowfish Aglorithms in Data Encryption and Decryption Stefanus Eko Prasetyo; Gautama Wijaya; Felix
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2259

Abstract

The advancement of information technology has had a significant impact, one of which is as a medium for transmitting information from one place to another, making information access easier for many people. However, the ease of access to communication media also poses challenges for information security, as information becomes more vulnerable to being accessed, stolen, or manipulated by irresponsible parties. To protect the confidentiality of information, specific methods are needed, one of which is cryptography. In cryptography, there are various algorithms, including DES, AES, IDEA, Blowfish, Twofish, and RC4. This research aims to compare the performance of several cryptographic algorithms in the data encryption and decryption processes, focusing on processing speed and the size of the encrypted file. The results of the research show differences in processing time and file size of encrypted and decrypted data for each algorithm. Keywords: Aglorithms, Decryption, Encryption.
Rancangan Jaringan Highly Available PT Pundi Mas Berjaya (PMB) Prasetyo, Stefanus Eko; Wijaya, Gautama; Hasanah, Nafisatul; Jemmy, Jemmy; Syahfira, Putri
Telcomatics Vol. 8 No. 1 (2023)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v8i1.7359

Abstract

In the digital age, networks are an important factor for implementing communication and exchanging information. Campus networks, which are private networks specifically designed for a particular institution, are essential for the institution because they provide access to the necessary information and services. However, campus networks are also vulnerable to security threats such as cybercrime and malware attacks. Firewall implementation can minimize these threats by controlling access to network services. Pundi Mas Berjaya (PMB), a company that provides software solutions to the global market, requires a highly available and redundant campus network. This research uses Cisco Packet Tracer to design and configure the network required by PMB. Implementing a highly available and redundant campus network with a hierarchical network model will improve the performance of the PMB campus network connectivity and security.
The Development of a Deep Learning-Based Chatbot for Stock Keeping Unit (SKU) Management Julianto, Hendra; Wijaya, Gautama; Haeruddin, Haeruddin
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 7 No. 2 (2024)
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Digital communications platforms, one of the revolutionary breakthroughs brought by rapid technological development. Such breakthroughs include technology in chatbots, which has now become a mighty tool, especially within the commercial sectors. This research hence focuses on the evolution of a chatbot in solving SKU management problems through deep learning technologies, such as the Multilayer Perceptron neural networks. The chatbot's goal is to deliver precise and effective information on SKU codes, stock levels, and product characteristics. The chatbot showed a high accuracy rate of 98% in answering questions about the given dataset after extensive testing. The findings demonstrate the potential of chatbots with deep learning to improve customer service and operational effectiveness in companies
Website Security Analysis Using Vulnerability Assessment Method : Case Study: Universitas Internasional Batam Haeruddin; Gautama Wijaya; Hendra Winata; Sukma Aji; Muhammad Nur Faiz
Journal of Innovation Information Technology and Application (JINITA) Vol 6 No 2 (2024): JINITA, December 2024
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v6i2.2476

Abstract

In today’s digital era, ensuring website security is crucial, especially in the education sector which is frequently targeted by cyber attacks. This research aims to test security of the Universitas Internasional Batam (UIB) website using OWASP ZAP and Nessus. The method will be used in this research was vulnerability assessment. It will involve gathering information with the tools such as, Nmap, whois and nslookup. OWASP ZAP detected 11 vulnerabilities, categorized into 6 medium level and 5 low level, including Content Security Policies (CSP) and anti-clickjacking headers. Otherwise, Nessus only detected one medium level vulnerability, the absence of HTTP Strict Transport Security (HSTS). The difference in detection results from the tools that OWASP ZAP is better at finding web application weakness that are consistent with the OWASP Top Ten 2021, while Nessus specifically targets server and network configuration. For educational institutions, these results emphasize the importance of conducting regular vulnerability assessment to protect sensitive data. Recommended action include implementing CSP to prevent Cross-site scripting (XSS) and other injection attacks, enforcing HSTS to secure communication, and its recommend to updating software to mitigate the unknown vulnerabilities. By adopting these measures, institutions can reduce their exposure to cyber attacks, its also can maintain user trust, and strengthen overall security. This research provides a pratical framework for stregthening the security of educational websites against evolving threats. These findings highlight that the importance of using multiple tools can provide a more comprehensive view of security gaps.
Integrasi Feature Engineering dan SMOTE pada Algoritma Random Forest untuk Prediksi Kerusakan Chip RFID di Industri Sel Surya Haeruddin, Haeruddin; Winata, Franklin; Tresnawan, Muhammad Ilham Ashiddiq; Wijaya, Gautama; Wijayanto Aripradono, Heru
Journal of Information System Research (JOSH) Vol 7 No 2 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i2.9038

Abstract

The electronics industry, particularly solar cell manufacturing, demands production processes that are fast, precise, and supported by high data integrity. One critical component in the production flow is the chip embedded in the flower basket, which functions to store and transmit data through an RFID system. Damage to the chip can lead to information loss, tag reading failures, and disruptions in production efficiency and continuity. This study aims to predict chip status, classified as either normal or damaged, based on various process parameters, including immersion temperature, ambient humidity, process pressure, machine vibration, drying speed, heating and cooling duration, firing temperature, usage frequency, and RFID reading conditions. A feature engineering approach is applied to construct more representative derived features, while SMOTE is utilized to address class imbalance in the dataset. This study focuses on developing a predictive model using the Random Forest method to identify the most influential process variables related to chip damage risk. The data used in this study are obtained from historical production process records of a solar cell manufacturing plant. The results indicate that combinations of multiple process parameters significantly contribute to the potential risk of chip damage, and the Random Forest model demonstrates good predictive performance in classifying chip conditions. These findings suggest that the proposed model can serve as an early warning system to detect chip damage risks before they impact production processes. With proper implementation, the predictive model is expected to support preventive actions, enhance data integrity, and minimize disruptions in the solar cell manufacturing workflow.
Klasifikasi Kematangan Buah Pisang Menggunakan YOLOv12 Berbasis Deep Learning Prasetyo, Stefanus Eko; Wijaya, Gautama; Kwan, Allan
STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Vol. 5 No. 1 (2026): Februari
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/storage.v5i1.7557

Abstract

Sebagai komoditas hortikultura dengan permintaan pasar yang tinggi dan nilai jual strategis, pisang memerlukan penanganan pascapanen yang tepat, khususnya dalam penentuan fase kematangan. Selama ini, proses penyortiran kematangan buah umumnya dilakukan secara konvensional melalui inspeksi visual manual, yang bersifat subjektif dan berpotensi menghasilkan penilaian yang tidak konsisten. Oleh karena itu, penelitian ini berfokus pada perancangan sistem otomatis berbasis deep learning untuk menghasilkan klasifikasi kematangan yang lebih objektif dan terstandar. Algoritma YOLOv12 digunakan sebagai metode utama untuk mendeteksi serta mengklasifikasikan citra buah ke dalam tiga fase, yaitu mentah, matang, dan lewat matang. Data latih dikembangkan melalui proses anotasi serta augmentasi citra untuk meningkatkan variasi visual dan mencegah overfitting. Hasil evaluasi menunjukkan bahwa model mencapai Mean Average Precision (mAP@0.5) sebesar 95,2% dengan waktu deteksi di bawah 50 ms per gambar. Temuan ini menunjukkan potensi penerapan sistem secara real-time pada lingkungan industri penyortiran buah.
Co-Authors ., Kennedi Aboagye, Osei Enoch Andy Chia Aripradono, Heru Wijayanto Avian Avian Benhans, Devina Deven Lee Dominggo Givarel Elvin Lee Evander, Owen Febrianto Febrianto, Febrianto Felix Franky Viky Franklyn Haeruddin Haeruddin Haeruddin Haeruddin, . Hasanah, Nafisatul Hendi Hendi Hendra Julianto, Hendra Hendra Winata Husnul Khatimah Ika Oktaviani Yusuf Jemmy Jemmy Jemmy, Jemmy Jenny Erika Putri Jessy Ng Joanne Joanne Jong, Ricky Jowie Lim Kelvin Kelvin Kwan, Allan Leo Leo Leo Muhammad Arif Guntara Muhammad Nur Faiz Nafisatul Hasanah Nafisatul Hasanah Nandana Rizqi Andhika Fatkhurrahman Ningsih, Vivian Febri Novita Nelvi Pradino Kusumo Prasetyo, Stefanus Eko Putri Syahfira Raymond Gautama Putra Sama, Hendi Santi Santi Sopiyan Sopiyan, Sopiyan Stefanus Eko Prasetyoi Sukma Aji Sun Pho Syahfira, Putri Tony Jack Tan Ding Tony Wibowo, Tony Tresnawan, Muhammad Ilham Ashiddiq Victor Fernando Winata, Franklin Yulianto, Andik