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All Journal Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Ilmiah Kursor Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan JIEET (Journal of Information Engineering and Educational Technology) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal of Information System, Applied, Management, Accounting and Research Jurnal Mantik Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi bit-Tech ILKOMNIKA: Journal of Computer Science and Applied Informatics JATI (Jurnal Mahasiswa Teknik Informatika) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Bertuah : Jurnal Syariah dan Ekonomi Islam Journal of Applied Data Sciences International Journal Of Computer, Network Security and Information System (IJCONSIST) Jurnal Informatika Teknologi dan Sains (Jinteks) Journal of Vocational Education and Information Technology (JVEIT) Jurnal Penelitian Sistem Informasi ILTEK : Jurnal Teknologi Jurnal Informatika Polinema (JIP) Horizon: Indonesian Journal of Multidisciplinary Repeater: Publikasi Teknik Informatika dan Jaringan Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Jurnal Informatika Dan Tekonologi Komputer Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Achmad Junaidi
Universitas Pembangunan Nasional Veteran Jawa Timur
Religion Agriculture, Biological Sciences & Forestry 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Public Health Social Sciences Other

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Comparative Analysis of LSTM and GRU Algorithms for Inflation Rate Forecasting Moh. Angga Ardiyansyah; Muhammad Muharrom Al Haromainy; Achmad Junaidi
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3370

Abstract

Inflation is a critical economic indicator that directly affects price stability, purchasing power, and the formulation of fiscal and monetary policies. In East Java, inflation has demonstrated considerable year-to-year volatility, creating significant challenges for policymakers in maintaining regional economic stability. This situation highlights the need for forecasting models that are both accurate and capable of adapting to complex economic data patterns. This study presents a comparative analysis of two deep learning algorithms Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) for forecasting year-on-year (YoY) inflation in East Java using data from January 2005 to December 2024. The dataset was processed using Min–Max normalization and a 12-month sliding window to capture long-term dependencies and seasonal variations. Model performance was evaluated using RMSE, MAE, and MAPE. The findings demonstrate that no single model performs best across all metrics. The LSTM4 model with a [128,128] architecture achieved the lowest MAE and MAPE values, indicating superior average predictive accuracy and stronger capability in learning complex long-term inflation patterns. In contrast, the GRU1 [64,64] model produced the lowest RMSE and the shortest training time, highlighting its efficiency in minimizing extreme prediction errors and reducing computational cost. These results offer valuable insights for policymakers in East Java: LSTM is more suitable for applications requiring high prediction accuracy, whereas GRU is preferable for real-time or resource-efficient forecasting systems, especially in fast-changing economic environments.
Aplikasi OMR untuk Pemeriksaan Lembar Jawaban menggunakan DexiNed Kus Dwi Prastyo; Achmad Junaidi; Firza Prima Aditiawan
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3425

Abstract

Digital image processing is a field of computer science that focuses on analyzing and interpreting digital images to extract meaningful information. One of its applications is Optical Mark Recognition (OMR), a technology used to detect marks on documents. OMR is commonly utilized for evaluating answer sheets. However, conventional OMR systems typically rely on specialized scanners that are expensive and lack flexibility. Although Computer-Based Testing (CBT) offers the convenience of automated scoring, its implementation heavily depends on the availability of technological infrastructure such as computers, internet connectivity, and a stable power supply. This study develops a real-time Optical Mark Recognition (OMR) application capable of performing answer sheet assessment directly on the client side. The system utilizes the DexiNed method for edge detection of the answer areas. The application is web-based and built using JavaScript and OpenCV.js to process images directly from the user's device camera. Testing was carried out under various scenarios, including different lighting intensities, scanner positions, pencil types, and shading quality. The results show that the application can detect marked answers with an accuracy up to 100%, although some limitations were observed under certain technical conditions. Weaknesses were found in low lighting conditions using a 5 watt lamp at a distance of 3 meters, light reflections, and the camera angle was not aligned with the answer sheet. Overall, the application provides an efficient and flexible alternative for answer sheet assessment without requiring dedicated scanning devices, making it suitable for educational institutions with limited infrastructure.
Design of Thesis Topic Recommendation System Using TF-IDF and Cosine Similarity Muhammad Baihaqi Arrisalah; Muhammad Muharrom Al Haromainy; Achmad Junaidi
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3579

Abstract

Selecting a thesis topic is a critical stage in a student’s academic journey and frequently poses substantial cognitive and procedural challenges. This study reports the design and implementation of the Computer Science Thesis Recommendation System (SRSIK Hub), a web-based decision-support platform aimed at improving the efficiency and accuracy of thesis topic selection. The primary novelty of this research lies in the systematic integration of Term Frequency–Inverse Document Frequency (TF-IDF) and Cosine Similarity within a large-scale academic corpus to model fine-grained semantic relevance between student interests and prior thesis documents, enabling more precise and transparent recommendations than conventional keyword-based searches. The system adopts a content-based filtering approach and processes approximately 4,000 thesis records collected from multiple university repositories. Textual data are preprocessed and transformed using TF-IDF vectorization, while Cosine Similarity is employed to rank candidate topics according to relevance. System effectiveness was evaluated using the WebUse Framework involving 75 student respondents. The evaluation yielded an overall score of 4.44 out of 5, indicating high usability, strong information quality, and reliable system functionality. This performance score demonstrates that the proposed recommendation model is not only technically sound but also practically applicable in real academic settings, where it can significantly reduce topic selection time and uncertainty for students. The results confirm that SRSIK Hub effectively supports students in identifying research topics aligned with their academic interests and competencies. Beyond local deployment, the system is transferable to other institutions for scalable thesis recommendation support.
Evaluating Web Application Security Using OWASP Top 10 and NIST SP 800-115 Farrel Tiuraka Vierino; Henni Endah Wahanani; Achmad Junaidi
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3702

Abstract

Cybersecurity assurance for public-facing government websites remains critical amid accelerating digital transformation. This study adopts an exploratory–evaluative research design to systematically examine and validate the security posture of the Surabaya Public Slaughterhouse (RPH Surabaya) website through an integrated application of OWASP Top 10 (2021) as a vulnerability taxonomy and NIST SP 800-115 as a procedural testing framework. The methodology follows structured planning, discovery, attack, and reporting phases. Discovery combined reconnaissance tools (Nslookup, Whois, Nmap, Dirsearch, Wappalyzer, and Google Dorking) with OWASP ZAP scanning, while attack validation employed Burp Suite, SQLMap, and browser-based developer analysis within a controlled Kali Linux environment. Thirteen potential vulnerabilities were detected, of which ten were empirically confirmed after manual verification. Confirmed weaknesses were predominantly categorized as Security Misconfiguration, including missing Anti-CSRF protections, directory browsing exposure, absent Content Security Policy and anti-clickjacking headers, outdated JavaScript libraries, insecure cookie attributes (missing HttpOnly and SameSite), lack of Strict-Transport-Security and X-Content-Type-Options headers, and user-controllable HTML attributes. The contribution lies in demonstrating a reproducible dual-framework validation pipeline that distinguishes scanner alerts from confirmed exploitability, thereby strengthening methodological rigor in public-sector web security assessment. These findings indicate systemic configuration-level risk exposure that may elevate susceptibility to XSS, CSRF, clickjacking, and injection-related threats relative to comparable public-institution websites. However, the assessment is limited to a single institutional website and an unauthenticated testing scope, constraining generalizability and deeper application-layer analysis.
Uncovering Hidden Security Risks in Government Web Portals Using Penetration Testing and Attack Modeling Belia Putri Salsabila; Henni Endah Wahanani; Achmad Junaidi
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3776

Abstract

Government web portals that consolidate public services and process personally identifiable data are prime targets for cyber adversaries. However, many existing assessments rely on single-framework methodologies that provide limited adversarial context and insufficient prioritization guidance. This study evaluates the security posture of System X, a public-facing government portal in Indonesia, using a grey-box penetration testing approach that integrates OWASP Top 10:2021, CVSS v3.1, and MITRE ATT&CK. Automated scanning using OWASP ZAP and Nessus identified 12 potential vulnerabilities, which were subsequently validated through manual testing using Burp Suite, cURL, SQLmap, and browser developer tools. The validation process confirmed nine True Positives and three False Positives, resulting in a 25% false positive rate, consistent with prior studies on government web applications. The identified vulnerabilities fall within Broken Access Control, Security Misconfiguration, and Identification and Authentication Failures, with CVSS Base Scores ranging from 4.2 to 6.1. Unlike traditional severity-based assessments, the integration of MITRE ATT&CK enables adversarial behavior mapping and reveals dependency relationships between vulnerabilities. For example, a single Content Security Policy (CSP) misconfiguration was found to enable multiple attack techniques (T1059.007), demonstrating that addressing one root cause can mitigate several related vulnerabilities simultaneously. This integrated approach enhances vulnerability prioritization by providing both severity and attacker-context insights, offering more actionable remediation strategies compared to single-framework methods. The findings contribute to improving practical security assessment methodologies for government systems and support evidence-based cybersecurity decision-making.
OTOMATISASI MANAJEMEN BANDWIDTH INTERNET DENGAN INTEGRASI METODE HTB DAN PCQ DI DESA BARON KABUPATEN GRESIK Mohammad Syarifuz Zaim; Henni Endah Wahanani; Achmad Junaidi
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5802

Abstract

PT Persada Data Multimedia is an Internet Service Provider (ISP) company that focuses on dedicated network management. Operating in Laren District, Lamongan Regency, PT Persada Data Multimedia expands its services and supports the development of information technology in East Java, including Baron Village, Gresik Regency. In Baron Village, PT Persada Data Multimedia serves about 90 customers. Along with the increase in the number of customers, the complexity of network traffic increases, so effective and efficient network management is required. The use of proper bandwidth management is very necessary, one of which is often used, namely the HTB (Hierarchical Token Bucket) and PCQ (Per Connection Queue) methods. Quality of Service (QoS) is used as a benchmark to define the characteristics of a network service related to the quality of the service by calculating the value of QoS parameters, namely: throughput, packet loss, delay, and jitter. The purpose of this research is to determine the QoS value generated by integrating both HTB and PCQ methods adaptively based on the bandwidth distributed in Baron Village, Gresik Regency. Based on the tests that have been carried out, the QoS analysis results indicate that integrating the HTB and PCQ methods produces satisfactory results, with an index value of 3.375 increasing from the previous value of 3.5 with a value difference of 0.125. This result is based on the average results of test results on 4 QoS parameters: throughput, packet loss, delay, and jitter.
Analisis Kerentanan Keamanan Sistem Enterprise Resource Planning Menggunakan PTES dan Owasp Zap Ekamartha, Ken Narendra; Wahanani, Henni Endah; Junaidi, Achmad
HORIZON: Indonesian Journal of Multidisciplinary Vol. 4 No. 4 (2026): HORIZON: Indonesian Journal of Multidisciplinary
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/hijm.v4i4.7179

Abstract

This study aims to identify and analyze security vulnerabilities in the XYZ ERP system using the Penetration Testing Execution Standard (PTES) approach. The study was conducted through pre-engagement interactions, intelligence gathering, threat modeling, vulnerability analysis, exploitation, and reporting, utilizing OWASP ZAP as the primary testing tool. Vulnerabilities were classified based on the Common Weakness Enumeration (CWE), while their severity was assessed using the Common Vulnerability Scoring System (CVSS) version 3.1. The study identified four main vulnerabilities: SQL Injection (CVSS 8.3; High), Brute Force Login Page (CVSS 8.2; High), Cross-Site Scripting (CVSS 5.4; Medium), and the risk of active session abuse (CVSS 4.2; Medium). These vulnerabilities have the potential to threaten data confidentiality, integrity, and availability through unauthorized access, data manipulation, account takeover, and user session abuse. This research provides technical recommendations for improving ERP system security and serves as a reference for organizations in systematically evaluating and mitigating web application vulnerabilities.
Robustness Evaluation of Gradient Boosting Models Against Unseen Attacks on the ToN-IoT Dataset Hakim, Albi Akhsanul; Aditiawan, Firza Prima; Junaidi, Achmad
ILKOMNIKA Vol 8 No 2 (2026): Volume 8, Number 2, August 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v8i2.886

Abstract

Machine learning-based Intrusion Detection Systems (IDS) often achieve strong performance on known attack distributions but may degrade when encountering unseen attacks. This study evaluates the robustness of two gradient boosting models, XGBoost and LightGBM, under unseen attack distribution shifts using the ToN-IoT dataset. A controlled attack-exclusion strategy was applied, where selected attack types were excluded from training and evaluated only during testing. Unlike conventional unseen-attack evaluations that primarily report performance degradation, this study further investigates attack-specific degradation through feature-level distribution similarity analysis. Feature importance analysis was used to identify key traffic features, while Jensen-Shannon Divergence (JS Divergence) quantified distribution similarity between attack and normal traffic. Model robustness was assessed using Recall, Macro-F1, PR-AUC, False Negatives (FN), and False Negative Rate (FNR) across five random seeds. The results show that performance degradation varied substantially across attack types. Both models maintained near-baseline performance for unseen Scanning attacks, whereas unseen DDoS and especially MITM attacks produced larger increases in FNR and greater performance degradation. Correlation analysis indicated that the proto feature exhibited the strongest relationship between distribution similarity and detection errors, with lower JS Divergence generally associated with higher FNR. These findings suggest that robustness degradation depends not only on attack novelty but also on the similarity between attack and normal traffic distributions, providing additional insight into attack-specific robustness behavior in IDS models.
Pengembangan FS-CPSM (Feedback System-Based Creative Problem Solving Metaverse) Menggunakan Game Edukasi Mitigasi Banjir Berbasis Roblox Studio Mochammad Afdal Susilo Aji; Achmad Junaidi
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4469

Abstract

Flooding in Indonesia is becoming increasingly frequent. Data from the National Agency for Disaster Countermeasure (BNPB) records an average of over 3,000 flood events annually over the past decade (BNPB, 2023). Meanwhile, classroom instruction on flood mitigation often relies on lectures and lacks direct student engagement. This study developed FS-CPSM (Feedback System-Based Creative Problem Solving Metaverse), an educational game created in Roblox Studio that integrates the six-stage Creative Problem Solving (CPS) framework into a fictional post-flood village environment. Players are guided through an interactive interface spanning stages from "Mess Finding" to "Acceptance Finding" supported by an automated feedback system that provides validation and hints when answers are incomplete. The study employed a Research and Development (R&D) methodology with functional testing. Results showed that all 12 key features ranging from the CPS interface and the Sumatra flood story panel to the feedback system operated without errors, achieving a 100% system success rate. This research demonstrates that Roblox Studio is a viable platform for educational games based on structured problem-solving.
Identifikasi Citra Penyakit Monkeypox dengan Random Forest Serta Ekstraksi Fitur VGG19: Indonesia Muhammad Azka Zaki; Eka Prakarsa Mandyartha; Achmad Junaidi
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 6 No. 1 (2026): Maret : Jurnal Informatika dan Tekonologi Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v6i1.10132

Abstract

Monkeypox is an infectious disease that can be recognized through images of the patient's skin lesions. A fast and accurate diagnosis method is required to identify Monkeypox. This research aims to identify Monkeypox imagery using the VGG19 feature extraction method, which is then classified using the Random Forest algorithm. The dataset consists of 770 original images, which were expanded to 5,860 images through geometric transformation augmentation. The test results show that the VGG19 feature extraction method with Random Forest classification achieved an accuracy of 95.1%, indicating good performance. This finding suggests the potential of this method as a machine learning approach for detecting Monkeypox and can be further developed with other artificial intelligence approaches.
Co-Authors Achmad Rozy Priambodo Afifudin, Muhammad Agung Mustika Rizki, Agung Mustika Akbar, Refansya Rachmad Akmal, Mohammad Faizal Al Fathoni, Hanif Allan Ruhui Fatmah Sari Andreas Nugroho Sihananto Andreas Nugroho Sihananto Anggraini Puspita Sari Anggraini Puspita Sari Anggraini Puspita Sari Ar Romandhon, Mitzaqon Gholizhan Arif Saifudin, Muhamad Ariq Musyaffah Ghufron, Althaf Bachtiar Riza Pratama Basuki Rahmat Basuki Rahmat Masdi Siduppa Belia Putri Salsabila beni tiyas kristanti Ciptaagung Firjat Ardine Clara Diva Paramitha Dafauzan Bilal Syaifulloh Darmawan, Marcellinus Aditya Vitro Dinda Friska Oktaviana Dunuroi Assuryani Dwi Arman Prasetya Efendi, Ridwan Eka Prakarsa Mandyartha Ekamartha, Ken Narendra Erik evranata Pardede Erik Iman Heri Ujianto Eva Yulia Puspaningrum Eva Yulia Puspaningrum Farrel Tiuraka Vierino Fauzan Novriandy, Muhammad Fetty Tri Anggraeny Firza Prima Aditiawan Galan Ahmad Defanka Galan Ahmad Defanka Hafiyan Fazagi Adnanto Hakim, Albi Akhsanul Henni Endah Wahanani Henni Endah Wahanani I Gede Susrama Mas Diyasa I Gede Susrama Mas Diyasa Isworo, Muhamad Raihan Ramadhani Izzatul Fithriyah Kartini Kartini kristanti, beni tiyas Kus Dwi Prastyo Lesmana, Benedictus Rafael Mandyartha, Eka Prakarsa Maulana, Hendra Mochammad Afdal Susilo Aji Mochammad Afdal Susilo Aji Mochammad Yoga Firnanda Moh. Angga Ardiyansyah Mohammad Haydir Awaludin Waskito Mohammad Syarifuz Zaim Muh. Irsyad Dwi Kurniawan Muhammad Azka Zaki Muhammad Baihaqi Arrisalah Muhammad Muharrom Al Haromainy Muhammad Rafi Muhtaddin Noor Mustika Rizki, Agung Mutiq Anisa Tanjung Muttaqin, Faisal Nugroho Sihananto, Andreas Nurlaili, Afina Lina Pelean Alexander Jonas Sitompul Pratama, Novandi Kevin Prinafsika PW, Benar Setya Rachmadhany Iman Rafie Ishaq Maulana Rafif Ilafi Wahyu Gunawan Rahmanda Putri, Endin Ratantja Kusumajati, Fatwa Rayya Ruwa'im Nafie Ridwan Efendi Riza Satria Putra Rizki, Agung Mustika Royan Fajar Sultoni Ryan Reynickha Fatullah Sajiwo, Achmad Fauzihan Bagus Sebrina, Aida Fitriya Shahab, Muhammad Syaugi Syahbagus Radithya Haryo Santoso Thalita Syahlani Putri Tinambunan, Fernanda Wahyu Melinda Permanasari Wardah Gracillaria Suharyono, Farra William Lijaya Therry, Renaldy