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All Journal Jurnal Pseudocode Jurnal Sistem Informasi dan Sains Teknologi International Journal of Engineering, Science and Information Technology Journal of Social Science
Riza Adrianti Supono, Riza Adrianti
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Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Analisis Kualitas Aplikasi E-Court Menggunakan Model ISO/IEC 25010:2011 (Studi Kasus Pengadilan Agama Bekasi) Baros, Cuzaintra; Supono, Riza Adrianti
Jurnal Pseudocode Vol 12 No 1 (2025): Volume 12 Nomor 1 Februari 2025
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.12.1.12-20

Abstract

E-Court is a system designed to digitize and accelerate the process of case administration and trials in court. Given the importance of the quality of this application to support the performance of judicial administration, a comprehensive evaluation of various aspects of quality is crucial. This study aims to assess the quality level of the E-Court application used in the Bekasi Religious Court based on the ISO/IEC 25010:2011 standard with eight characteristics, namely: functional suitability, performance efficiency, compatibility, usability, reliability, security, maintainability, and portability. The study was conducted by collecting data by distributing questionnaires to service users, and the results of the study showed that the quality of the e-court application in the Bekasi Religious Court was considered Very Good, making the E-Court application in the Bekasi Religious Court easy to use and accessible to all levels of society. This study concludes that the E-Court application at the Bekasi Religious Court has met most of the quality criteria according to ISO/IEC 25010:2011, with the highest percentage obtained in the compatibility indicator with a value of 89%, followed by portability 88%, functional suitability 87%, security 87%, maintainability 87%, usability 85%, and performance efficiency 84%. The indicator with the lowest percentage is reliability, which is 83%. Keywords: E-Court Application, ISO/IEC 25010:2011 Method, Bekasi Religious Court
Implementation of Intrusion Detection System Using Snort and Log Visualization Using ELK Stack Robbani, Fatih Dien; Haryatmi, Emy; Riyadi, Tri Agus; Supono, Riza Adrianti; Bima Kurniawan, Ary; Rosdiana, Rosdiana
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.901

Abstract

Cyber threats like malware, ransomware, and DDoS attacks demand fast and integrated detection systems. Traditional network monitoring tools often struggle to identify complex real-time attack patterns. This study evaluates the integration of Snort, an Intrusion Detection System (IDS), with the ELK Stack (Elasticsearch, Logstash, Kibana) to detect and visualize cyberattacks effectively. The system was tested against three attack scenarios: a Windows ping flood, port scanning using Zenmap, and SSH brute force attacks via Nmap Scripting Engine (NSE). Wireshark was employed as a supporting tool to monitor raw network traffic. The results indicate that Snort detected all simulated attacks in real time, and the ELK Stack efficiently processed and visualized the alert data. However, limitations in Kibana's dashboard refresh rate slightly hindered real-time monitoring capabilities. Overall, the integration of Snort and the ELK Stack proves effective for network threat detection and analysis, with room for future improvements in visualization performance and automated response mechanisms.
ANALISIS WEBSITE DIGITAL MARKETING DAN PENGARUHNYA TERHADAP MINAT BELI LAYANAN Arrizky, Regista; Supono, Riza Adrianti
Jurnal Sistem Informasi dan Sains Teknologi Vol 7, No 2 (2025): Jurnal Sistem Informasi dan Sains Teknologi
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/sistek.v7i2.2416

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh elemen website digital marketing terhadap minat beli layanan digital. Fokus utama penelitian ini adalah untuk mengetahui bagaimana kecepatan loading, efektivitas Call-to-Action (CTA), dan kemudahan navigasi memengaruhi pengalaman pengguna dan keputusan pembelian. Penelitian ini menggunakan metode kuantitatif dengan menyebarkan survei kepada 100 responden berusia 17–44 tahun yang telah terpapar konten organik dari sebuah digital agency. Data dianalisis menggunakan regresi linier berganda untuk mengukur pengaruh masing-masing variabel terhadap minat beli. Hasil penelitian menunjukkan bahwa kecepatan loading, kualitas CTA, dan kemudahan navigasi berpengaruh signifikan terhadap minat beli. Website yang memuat dengan cepat meningkatkan kenyamanan pengguna, CTA yang efektif mendorong interaksi dan konversi, sedangkan navigasi yang intuitif memperpanjang durasi kunjungan dan keterlibatan pengguna. Ketiga elemen ini secara kolektif berkontribusi pada pengalaman pengguna yang positif dan mendorong perilaku pembelian. Temuan ini menegaskan pentingnya optimalisasi website dalam strategi digital marketing. Digital agency dan pelaku bisnis lainnya dapat memanfaatkan temuan ini untuk meningkatkan performa website dan daya saing.
Convolutional Neural Network Method in Determining Pfizer Vaccination Sentiment Analysis Supono, Riza Adrianti; Muljana , Hizkia Abiel
Journal of Social Science Vol. 5 No. 4 (2024): Journal of Social Science
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jss.v5i4.869

Abstract

Coronavirus (COVID-19) is a disease caused by the SARS-CoV-2 virus by attacking the respiratory system in humans and because of the rapid spread of infection, WHO declared COVID-19 a pandemic. Over time, several types of vaccines have been discovered which are thought to minimize the possibility of infection. One of the vaccines is Pfizer. During the use of the Pfizer vaccine, there have been pros and cons caused by the side effects of using the vaccine. Therefore, sentiment analysis was carried out on public opinion with data sourced from tweets on Twitter. The method used in making the model is Convolutional Neural Network (CNN). This model has been successfully created and has been tested on 1158 training data and 773 test data. The training data obtained an accuracy level of 98.87 % and the test data obtained an accuracy level of 69.46%.
Co-Authors Arrizky, Regista Baros, Cuzaintra Bima Kurniawan, Ary Emy Haryatmi Muljana , Hizkia Abiel Riyadi, Tri Agus Robbani, Fatih Dien Rosdiana Rosdiana