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Penerapan Metode Vulnerability Assessment untuk Identifikasi Keamanan Website berdasarkan OWASP ID Tahun 2021 Darmawan, Candra; Naibaho, Julius Panda Putra; Kweldju , Alex De
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25834

Abstract

Universities, as educational institutions, are potential targets of cyber attacks. This is inevitable problem, one of which  the University of Papua (UNIPA). The purpose this research is to find the security gaps the UNIPA website based on OWASP ID in 2021 and implement mitigation. Type of research is quantitative research with Vulnerability Assessment and Penetration Testing Life Cycle (VAPT) method. The VAPT method in research goes through five stages, namely scope, information gathering, vulnerability assessment, risk assessment, and reporting. The object of research is UNIPA website. Data collection uses primary data, the results of scanning the Zed Attack Proxy (ZAP) application. Data obtained from alerts ID, alerts, risk, and OWASP ID as information on vulnerability of UNIPA website. Research data analysis using OWASP ID. The results our findings, the vulnerability of UNIPA website is influenced by two factors, website security weaknesses and user negligence. Vulnerabilities with alerts ID A1, A2, A3, A4 A5, and A6 are a group website security weaknesses. The solution, vulnerabilities need utilize special systems such as anti-CSRF, CSP, CDN, Strict-Transport-Security Header, and timestamp checking so that the website is proportional. Meanwhile, the vulnerability with alerts ID A7 is a classification of user negligence. The solution is users must use the latest version of the browser. Browsers with latest version have X-Content-Type-Options: nosniff security mechanism to prevent sniffing attacks.
Sistem Absensi Guru Berbasis Web dengan Teknologi Qr Code (Kasus TKIT Insan Mulia Manokwari) Mahmud, Nurul Ahdiati; Kweldju, Alex De; Naibaho, Julius Panda Putra
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 1 (2025): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i1.868

Abstract

The rapid development of information technology has given birth to online attendance innovations using Quick Response Code (QR Code), utilizing technology to facilitate fast and responsive information exchange. Attendance systems play an important role in monitoring staff attendance and measuring productivity. Currently, the attendance system for TKIT Insan Mulia Manokwari educators still uses a fingerprint machine, so fingerprint identification is slow and attendance is recorded manually. To overcome this, a new QR Code-based attendance system is needed. This research uses the Rapid Application Development (RAD) method which includes requirements planning, system design, development and implementation. The resulting web-based QR Code attendance system simplifies teacher attendance and provides automatic recap reports, increasing data accuracy and reducing manual errors. This system effectively increases the efficiency of school administration. This research can be a reference for developing attendance systems in other educational institutions.
The Analisis Celah Keamanan Website Poltekkes Kemenkes Sorong Menggunakan Metode Penetration Testing Jayanto, Gunawan Yudi; Naibaho, Julius Panda Putra; Kweldju, Alex De
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 01 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i01.1549

Abstract

Currently, information technology is very necessary, in the digital era cybersecurity is one of the main factors for an institution to survive and be recognized for its credibility, including educational institutions, the Poltekkes Sorong Website is used as the main portal or media to disseminate academic information, interaction between students and the public, However, the existence of security gaps is something that allows cyber attacks to be carried out which can endanger data confidentiality. This study aims to analyze the security gaps in the Poltekkes Kemenkes Sorong website, the testing carried out using the penetration testing method which has several stages including collecting scanning information, vulnerability analysis. So that this study can provide guidance and practice for information system managers at Poltekkes Kemenkes Sorong to reduce the risk of cyber attacks and protect sensitive data held by the institution.
Real time weather forcasting with conditional CNN and TCN-BiLSTM Ensamble at Manokwari Lie, Ilham Tatayo; Naibaho, Julius Panda Putra; Kweldju, Alex De
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 2 (2026): Article Research April, 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i2.15999

Abstract

Short-term weather forecasting is fundamentally critical for disaster mitigation in dynamic tropical maritime regions. However, conventional numerical approaches suffer from high computational latency, and spatial deep learning models frequently experience severe performance degradation during nocturnal conditions due to the absence of illumination. This study aims to develop an adaptive, real-time multimodal weather nowcasting system that effectively prevents nocturnal predictive failure through a dynamic conditional ensemble architecture. The proposed framework integrates a Convolutional Neural Network (CNN) to extract optical features from a dataset of 2,515 localized sky images with a Temporal Convolutional Network and Bidirectional Long Short-Term Memory (TCN-BiLSTM) pipeline to process 15,111 corresponding meteorological time-series records from BMKG. To address visual ambiguity, the system strictly employs a day-night gating mechanism, deactivating the CNN at night to rely solely on thermodynamic data. Finally, the optimized model was deployed via TensorFlow.js for decentralized client-side browser inference. Experimental evaluations explicitly demonstrate that the conditional ensemble significantly outperformed all standalone models, achieving a peak accuracy of 92.49% and a Macro F1-score of 0.913 while successfully preserving a robust recall rate for precipitation events. Furthermore, the browser-based deployment completely eliminated server transmission bottlenecks, achieving sub-second warm-start inference latency across heterogeneous consumer devices. Ultimately, the conditional day-night modality gating mechanism effectively mitigates nocturnal visual degradation, proving that implementing this integrated architecture as a client-side web application is highly feasible for delivering instantaneous public weather warnings.