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All Journal IPTEK The Journal for Technology and Science JUTI: Jurnal Ilmiah Teknologi Informasi International Journal Of Computer, Network Security and Information System (IJCONSIST) Sinergi Aksi Nyata Cendekia
Yoga Ari Tofan
Universitas Pembangunan Nasional Veteran Jawa Timur
Agriculture, Biological Sciences & Forestry Computer Science & IT Dentistry Education Library & Information Science Social Sciences Other

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A Systematic Comparison of Software Requirements Classification Fajar Baskoro; Rasi Aziizah Andrahsmara; Brian Rizqi Paradisiaca Darnoto; Yoga Ari Tofan
IPTEK The Journal for Technology and Science Vol 32, No 3 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i3.13005

Abstract

Software requirements specification (SRS) is an essential part of software development. SRS has two features: functional requirements (FR) and non-functional requirements (NFR). Functional requirements define the needs that are directly in contact with stakeholders. Non-functional requirements describe how the software provides the means to carry out functional requirements. Non-functional requirements are often mixed with functional requirements. This study compares four primarily used machine learning methods for classifying functional and non-functional requirements. The contribution of our research is to use the PROMISE and SecReq (ePurse) dataset, then classify them by comparing the FastText+SVM, FastText+CNN, SVM, and CNN classification methods. CNN outperformed other methods on both datasets. The accuracy obtained by CNN on the PROMISE dataset is 99% and on the Seqreq dataset is 94%.
MALICIOUS TRAFFIC DETECTION IN DNS INFRASTRUCTURE USING DECISION TREE ALGORITHM Thooriqoh, Hazna At; Azzmi, M. Naufal; Tofan, Yoga Ari; Shiddiqi, Ary Mazharuddin
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 20, No. 1, January 2022
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i3.a1054

Abstract

Domain Name System (DNS) is an essential component in internet infrastructure to direct domains to IP addresses or conversely. Despite its important role in delivering internet services, attackers often use DNS as a bridge to breach a system. A DNS traffic analysis system is needed for early detection of attacks. However, the available security tools still have many shortcomings, for example broken authentication, sensitive data exposure, injection, etc. This research uses DNS analysis to develop anomaly-based techniques to detect malicious traffic on the DNS infrastructure. To do this, We look for network features that characterize DNS traffic. Features obtained will then be processed using the Decision Tree algorithm to classifyincoming DNS traffic. We experimented with 2.291.024 data traffic data matches the characteristics of BotNet and normal traffic. By dividing the data into 80% training and 20% testing data, our experimental results showed high detection aacuracy (96.36%) indicating the robustness of our method.
Classification of Eye Diseases Using the AlexNet Convolutional Neural Network Model Algorithm Pratama, Moch Deny; Sultoni, Royal Fajar; Wardhani, Adil Sandy; Sechuti, Maulana Hassan; Yerezqy Bagus; Dina Zatusiva Haq; Yoga Ari Tofan
IJCONSIST JOURNALS Vol 7 No 1 (2025): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijconsist.v7i1.160

Abstract

This study uses the Convolutional Neural Network (CNN) method with the AlexNet model to classify eye diseases based on medical images. The dataset includes labeled images of three types of eye diseases: cataract, glaucoma, and diabetic retinopathy. The experimental results show that the model achieved an accuracy of 75.18%, which indicates that CNN with the AlexNet architecture can classify eye diseases quite well. This research shows that deep learning can be used to help doctors or health professionals in diagnosing eye diseases through automatic image analysis. Although the accuracy still needs to be improved, this study can serve as a reference for developing an automated diagnostic system in the future. Further research is expected to increase accuracy, expand the dataset, and apply other deep learning techniques to improve the performance of eye disease detection.
Pengenalan Teknologi Arduino untuk Meningkatkan Literasi Teknologi Siswa Sekolah Menengah Yerezqy Bagus; Yoga Ari Tofan
Sinergi Aksi Nyata Cendekia Vol 1, No 2 (2025): November
Publisher : Lembaga Penelitian, Pengembangan, Pemberdayaan Potensi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.6131/sancaka.v1i2.199

Abstract

Kegiatan pengabdian masyarakat ini dilaksanakan untuk menjawab kebutuhan peningkatan literasi teknologi pada siswa sekolah menengah pertama, khususnya terkait pemahaman dasar mengenai perangkat mikrokontroler. Jumlah peserta pada kegiatan ini berjumlah 120 peserta (20 siswa per kelas) untuk enam kelas. Siswa kelas tujuh di SMP Al-Muslim Sidoarjo masih memiliki keterbatasan dalam mengakses pembelajaran teknologi yang aplikatif, sehingga diperlukan suatu program yang mampu memperkenalkan konsep komputasi dasar secara menarik dan mudah dipahami. Tujuan kegiatan ini adalah memberikan pemahaman awal tentang penggunaan Arduino melalui pendekatan praktik langsung. Metode pelaksanaan meliputi penyampaian materi pengantar, demonstrasi penggunaan perangkat, pendampingan praktik, serta pengamatan terhadap respons dan keterlibatan peserta. Hasil kegiatan menunjukkan bahwa siswa mampu memahami prinsip dasar kerja Arduino, mengoperasikan komponen sederhana, dan menunjukkan peningkatan minat terhadap teknologi. Kesimpulan dari kegiatan ini adalah bahwa pendekatan praktik langsung efektif dalam meningkatkan pemahaman siswa mengenai konsep komputasi dasar dan mendorong motivasi belajar teknologi di tingkat sekolah menengah pertama.
Peningkatan Literasi Digital Siswa Sekolah Menengah melalui Program Code for Kids di SMP Negeri 1 Sukaputra Muhammad Septama Prasetya; Yoga Ari Tofan; Muhamad Liswansyah Pratama; Sischa Wahyuning Tyas; Mohammad Al Hafidz; Muhamad Aris Burhanudin; Yerezqy Bagus
Sinergi Aksi Nyata Cendekia Vol 1, No 2 (2025): November
Publisher : Lembaga Penelitian, Pengembangan, Pemberdayaan Potensi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.6131/sancaka.v1i2.198

Abstract

Program pengenalan pemrograman bagi siswa usia dini masih terbatas di wilayah non perkotaan, termasuk di lingkungan sekolah sekitar kawasan pegunungan Sukapura. Kondisi tersebut menyebabkan siswa memiliki pemahaman yang rendah terhadap literasi digital dasar serta belum terpapar pada konsep pemrograman. Kegiatan ini bertujuan memperkenalkan logika komputasi dan pemrograman dasar kepada siswa kelas VII di SMP Negeri 1 Sukapura yang berjumlah 120 peserta melalui program Code for Kids. Metode pelaksanaan meliputi observasi awal, penyusunan materi pembelajaran, pelatihan interaktif menggunakan perangkat lunak pemrograman visual, dan evaluasi sederhana terhadap pemahaman peserta. Hasil kegiatan menunjukkan bahwa siswa mampu memahami konsep dasar pemrograman melalui praktik langsung dan bimbingan terstruktur. Peserta juga menunjukkan peningkatan minat dan keterlibatan selama proses pembelajaran. Kesimpulan dari kegiatan ini adalah bahwa pengenalan pemrograman dengan pendekatan interaktif dapat meningkatkan pemahaman awal dan minat siswa terhadap teknologi, serta memberikan kontribusi positif bagi penguatan literasi digital di daerah non perkotaan.
Co-Authors Ary Mazharuddin Shiddiqi Azzmi, M. Naufal Baskoro, Fajar Brian Rizqi Paradisiaca Darnoto Dina Zatusiva Haq Mohammad Al Hafidz Muhamad Aris Burhanudin Muhamad Liswansyah Pratama Muhammad Septama Prasetya Pratama, Moch Deny Rasi Aziizah Andrahsmara Sechuti, Maulana Hassan Sischa Wahyuning Tyas Sultoni, Royal Fajar Thooriqoh, Hazna At Wardhani, Adil Sandy Yerezqy Bagus Yerezqy Bagus