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All Journal Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Teknimedia: Teknologi Informasi dan Multimedia
Muhamad Azwar
Universitas Bumigora
Computer Science & IT Control & Systems Engineering Engineering

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ANALISIS SENTIMENT KEUANGAN MENGGUNAKAN FINE-TUNED FINBERT Heroe Santoso; Raisul Azhar; Suryati Suryati; Melati Rosanensi; I Made Yadi Dharma; Husain Husain; Ahmat Adil; Muhamad Azwar; I Putu Hariyadi
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 6 No. 2 (2025): Desember 2025
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v6i2.316

Abstract

Financial information is a critical type of data for analysis. However, because much of it is unstructured and widely dispersed, an appropriate analytical method is required, one of which is sentiment analysis. In the financial context, sentiment analysis is employed by the industry to assess public perceptions of companies or market conditions. This study implements a fine-tuned FinBERT model to perform sentiment analysis in the financial sector. The dataset used is a combination of FiQA (Financial Question Answering) and The Financial PhraseBank, consisting of English sentences labeled with negative, neutral, and positive sentiments. The research process involved data preprocessing, tokenization, data splitting, model training, and evaluation using accuracy, precision, recall, F1-score, and confusion matrix metrics. The results show that the model achieved 82% accuracy, with its best performance in the positive class (F1-score 0.88) and the neutral class (F1-score 0.85), but weaker performance in detecting the negative class (F1-score 0.49). These findings indicate that the fine-tuned FinBERT is effective for financial sentiment analysis, particularly for positive and neutral sentiments, though improvements are needed in negative sentiment detection, potentially through expanding training data diversity or applying data augmentation techniques
ANALISIS KERENTANAN SQLi DAN XSS PADA WEBSITE TOP-UP GAME Heri Sumantri; Husain; Muhamad Azwar; Raisul Azhar; Khairan Marzuki
Jurnal Manajemen Informatika dan Sistem Informasi Vol. 9 No. 2 (2026): MISI Juni 2026
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/misi.v9i2.2018

Abstract

Cybersecurity threats in Indonesia continue to rise. The National Cyber and Cryptography Agency (BSSN) has emphasized that attacks on web applications, including SQL injection, remain a key focus in the handling of cybersecurity incidents in Indonesia. SQL Injection and Cross-Site Scripting (XSS) consistently rank as the most critical vulnerabilities in web applications according to the OWASP Top 10 2021, with 94% of web applications at risk of intrusion. This study aims to analyze SQL Injection and XSS vulnerabilities on the LisxDragon website, a game top-up platform, using a white-box penetration testing methodology based on the OWASP Web Security Testing Guide (WSTG). This research consists of six phases: planning, information gathering, vulnerability analysis, exploitation, reporting, and post-patch mitigation and verification. Scanning was performed using a scanner that employs the Depth First Search (DFS) algorithm to crawl endpoints and a sequential-exhaustive injection strategy to maximize endpoint coverage and payload effectiveness. A total of 122 endpoints were identified, with 6 confirmed vulnerabilities across two endpoints: SQL Injection (Error-Based, Time-Based, Boolean-Based, Union-Based) and Reflected XSS. The exploitation assessment evaluated risks related to data, database structure leaks, data leaks or user data extraction, service disruption, and user cookie leaks. All vulnerabilities were addressed using prepared statements and the `htmlspecialchars()` output encoding function.
Co-Authors Ahmat Adil Azhar, Raisul Heri Sumantri Husain Husain I Made Yadi Dharma I Putu Hariyadi Khairan marzuki Melati Rosanensi Santoso, Heroe Suryati Suryati