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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Masyarakat Informatika International Journal of Advances in Intelligent Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Edu Komputika Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Dinamisia: Jurnal Pengabdian Kepada Masyarakat Journal of Computer Science and Informatics Engineering (J-Cosine) Adimas : Jurnal Pengabdian Kepada Masyarakat MULTINETICS Journal of Electronics, Electromedical Engineering, and Medical Informatics Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Indonesian Journal of Electrical Engineering and Computer Science Janaka : Jurnal Pengabdian Masyarakat BHAKTI PERSADA Jurnal Aplikasi IPTEKS (Journal of Applied Sciences and Technology) JURNAL POLI-TEKNOLOGI Jurnal Atma Inovasia Piston: Jurnal Teknologi Panthera : Jurnal Ilmiah Pendidikan Sains dan Terapan Taawun: Jurnal Pengabdian kepada Masyarakat
Mera Kartika Delimayanti
Politeknik Negeri Jakarta
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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

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DDoS Attacks Detection With Deep Learning Approach Using Convolutional Neural Network Widodo, Rafiq Amalul; Delimayanti, Mera Kartika; Wulandari, Asri
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8242

Abstract

The detection system of DDoS (Distributed Denial-of-Service) attacks aims to enhance network security across all facets of internet technology utilization. One is at SPKLU, which stands for Public Electric Vehicle Charging Station. The research employed a deep learning approach utilizing a Convolutional Neural Network (CNN) on a publicly available dataset. Based on our study and analysis, CNN has a precision rate of 95%. Its high accuracy and balanced performance across diverse attack types indicate the model's practical application in real-life situations. The model demonstrates promising performance in detecting different network traffic anomalies, offering significant insight into its potential for practical use. Further investigation is necessary to strengthen the resilience of DDoS assault tactics against emerging dangers and to tackle any potential constraints.
An Intelligent Web-Based Mental Health Management Platform with Rule-Based Music Therapy Recommendation Delimayanti, Mera Kartika; Wibowo, Harits Taqiy
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.10799

Abstract

This research developed a web-based application for mental health management with an emotional music therapy recommendation feature using Rule-Based Filtering. The system is designed to help individuals recognize and manage emotional conditions caused by life pressures, work stress, and often overlooked psychological issues. A 2023 survey showed that 43% of respondents were concerned about mental health problems, followed by stress at 40%, while 43.8% of parents of teenagers managed their children’s mental health issues independently, 19.2% did not know where to seek help, and 15.4% believed the problems would improve on their own. The system analyzes daily emotional input and weekly PANAS questionnaires to classify moods (Positive, Negative, Mixed, Neutral) based on Positive Affect (PA) and Negative Affect (NA) scores, then recommends relevant music from the database. The technical implementation uses Laravel for the backend and Tailwind CSS for the frontend. Black Box Testing showed 100% functionality. User Acceptance Test (UAT) with 32 respondents resulted in UAT-J 90.25%, UAT-K 90.41%, UAT-R 89.18%, and UAT-A 91.24%. The System Usability Scale (SUS) reached an average score of 85 (very high), while the Net Promoter Score (NPS) was 59.37% (62.50% Promoters), indicating strong user satisfaction and loyalty. This research is expected to help individuals monitor emotional conditions and increase mental health awareness through an innovative music-based approach.
Co-Authors Abdurahman Abdurrahman Ahmad Athoillah Aldias Bahatmaka Anggi Mardiyono Ari Dwi Nur Indriawan Musyono Asri Wulandari Baride, La Bayu Bagas Hapsoro Dewi Kurniawati Dewi Yanti Liliana Didik Supriadi Dodon Turianto Nugrahadi Dwi Kartini, Dwi Eko Saputro, Wahyu Danang Fahmi, Fiqri Fadillah Friska Abadi Hanin Wendho Hendra Kurniawan Iklima Ermis Ismail Imanu Danar Herunandi Imanu Danar Herunandi Indriawan, Ari Dwi Nur Irwan Budiman Iskandar, Ranu Kristiana, Indah Maya Kriswanto Kriswanto Kriswanto Kriswanto, Kriswanto La Ode Ahmad Barata Mahesa Rama Triwijaya Mauldy Laya Mohamad Naufal Aditya Mohammad Reza Faisal Muhammad Faizal Ardhiansyah Arifin Muhammad Faizal Ardhiansyah Arifin, Muhammad Faizal Ardhiansyah Muhammad Haekal Muhammad Ihsan Muhammad Reza Faisal, Muhammad Reza Mustofa, Fahmi Charish Nalawati, Rizki Elisa Naryanto, Rizqi Firti Naryapramono, Afrilza Daffa Nor Indrani Puspitasa, Nana Reisa Siva Nandika Reza Rendian Septiawan Riandini Riandini Riandini _ Rika Novita Wardhani Rizky Adi Rizqi Fitri Naryanto Samhuddin Sari, Risna Sari, Risna Septyan Eka Prastya Solly Aryza Sudirko, Danu Sudirko, Danu Sugiarto, Iyon Titok Sukoco, Imam Supriadi, Didik Suratmi, Sifera Umar Ali Ahmad Warsiti Warsiti Warsiti Warsiti Warsuta, Bambang Wibowo, Harits Taqiy Widodo, Rafiq Amalul Wildan Panji Tresna Wiwi Prastiwinarti Yoga Putra Pratama Yusuf Subagyo