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All Journal ComEngApp : Computer Engineering and Applications Journal Jupiter JSI: Jurnal Sistem Informasi (E-Journal) Jurnas Nasional Teknologi dan Sistem Informasi Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknik Informatika (JUTIF) The Indonesian Journal of Computer Science
Iman Saladin B. Azhar
Fakultas Ilmu Komputer, Universitas Sriwijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Other

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Fake News Detection Using Optimized Convolutional Neural Network and Bidirectional Long Short-Term Memory Sari, Winda Kurnia; Azhar, Iman Saladin B.; Yamani, Zaqqi; Florensia, Yesinta
Computer Engineering and Applications Journal (ComEngApp) Vol. 13 No. 3 (2024)
Publisher : Universitas Sriwijaya

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Abstract

The spread of fake news in the digital age threatens the integrity of online information, influences public opinion, and creates confusion. This study developed and tested a fake news detection model using an enhanced CNN-BiLSTM architecture with GloVe word embedding techniques. The WELFake dataset comprising 72,000 samples was used, with training and testing data ratios of 90:10, 80:20, and 70:30. Preprocessing involved GloVe 100-dimensional word embedding, tokenization, and stopword removal. The CNN-BiLSTM model was optimized with hyperparameter tuning, achieving an accuracy of 96%. A larger training data ratio demonstrated better performance. Results indicate the effectiveness of this model in distinguishing fake news from real news. This study shows that the CNN-BiLSTM architecture with GloVe embedding can achieve high accuracy in fake news detection, with recommendations for further research to explore preprocessing techniques and alternative model architectures for further improvement.
Security and Performance Evaluation of PPTP-Based VPN with AES Encryption in Enterprise Network Environments Heryanto, Ahmad; Setiawan, Deris; Audrey, Berby Febriana; Hermansyah, Adi; Afifah, Nurul; Azhar, Iman Saladin B.; Idris, Mohd Yazid Bin; Budiarto, Rahmat
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4818

Abstract

In the context of the current digital era, Virtual Private Networks (VPNs) serve a critical function in ensuring the confidentiality and integrity of data transmitted across public networks, particularly within corporate environments. This study presents a comprehensive analysis of VPN security and performance, with a specific focus on the Point-to-Point Tunneling Protocol (PPTP) and the implementation of encryption algorithms such as AES-128 and AES-256. Despite the widespread adoption of PPTP due to its simplicity and broad compatibility, it exhibits significant security vulnerabilities, primarily stemming from its reliance on the outdated RC4-based Microsoft Point-to-Point Encryption (MPPE) and the susceptible MS-CHAP authentication protocol, which is highly vulnerable to brute-force and dictionary attacks. Empirical findings indicate that, although AES-128 and AES-256 introduce minor performance trade-offs compared to unencrypted configurations, AES-256 demonstrates markedly enhanced security, achieving a 98.9% authentication success rate and a threat detection time of 122 milliseconds. Nevertheless, increased user load adversely impacts network performance, with throughput declining from 95 Mbps to 40 Mbps as the user count rises from 5 to 50, accompanied by elevated latency and packet loss. Comparative analysis across three encryption scenarios AES-128, AES-256, and MPPE-PPTP reveals a consistent degradation in network performance as user load increases, with AES-256 offering the strongest security at the cost of slightly reduced throughput and increased latency under high-load conditions. MPPE-PPTP, while providing better throughput, lacks adequate security, making it unsuitable for high-risk environments. Based on these observations, this study recommends the implementation of AES-256 encryption in enterprise networks requiring high security, supported by continuous performance monitoring and strategic capacity planning. Furthermore, the adoption of a secure site-to-site VPN architecture is proposed to facilitate reliable and secure communication between geographically distributed office locations.
Mapping the Distribution of Covid-19 Information using a Web-based Information System Ibrahim, Ali; Okllilas, Ahmad Fali; Azhar, Iman Saladin B.; Utama, Yadi; Zahran, Ahmad Hafizh
Sistemasi: Jurnal Sistem Informasi Vol 13, No 2 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i2.3773

Abstract

Based on information from several official government websites and national television media, at the beginning of November 2021, there was a decrease in the spread of the COVID-19 virus. At the end of November 2022, a new type of virus was discovered, namely SARS-CoV-2, also known as the Omicron variant, resulting in additional cases. Therefore, researchers conducted research with the aim of providing information about the spread of the virus with a mapping system down to the RT level, so that the public gets detailed and real-time information about the area based on mapping. The urgency of this research is that, with the results of this research, the public can take better care of and be able to provide self-awareness regarding health protocols. The public can have access to detailed information and mapping about the spread of the virus. This research adopts changes in the design science research methodology proposed by Hevner. The results of the research are an Information System for Mapping the Distribution of COVID-19 Cases and Their Danger Level with 5 calculation categories, namely class I with a range of 66–80 has very high danger level criteria, class II with a range of 51–65 has high danger level criteria, class III with a range of 36–50 has medium level criteria, class IV with a range of 36–50 has criteria for a low level of danger, and class V with a range of 5–20 has a very low level of danger.
Co-Authors Adi Hermansyah, Adi Aditya Putra Perdana Prasetyo Ahmad Fali Okilas Ahmad Fali Oklilas Ahmad Heryanto, Ahmad Ali Bardadi Ali Ibrahim Arif Tumpal Leonardo Sianturi Audrey, Berby Febriana Dian Palupi Rini Florensia, Yesinta Ghufron - Mubaroq Gumay, Naretha Kawadha Pasemah Habibi, Ismail Huda - Ubaya Huda Ubaya Idris, Mohd Yazid Bin Kharisma Kharisma Kharisma Maulida, Mutia Nadra Muhammad Afif Muhammad Hidayat Muhammad Hidayat Okllilas, Ahmad Fali Purwita Sari Rahmat Budiarto Reza Firsandaya Malik Rossi Passarella Setiawan, Deris Sri Desy Siswanti Winda Kurnia Sari Yadi Utama Yamani, Zaqqi Zahran, Ahmad Hafizh