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All Journal Building of Informatics, Technology and Science Al-Fusha : Arabic Language Education Journal
Ilma, Zidni
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Religion Computer Science & IT Education Languange, Linguistic, Communication & Media

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Impact of SMOTE for Imbalance Class in DDoS Attack Detection Using Deep Learning MLP Ilma, Zidni; Ghozi, Wildanil; Rafrastara, Fauzi Adi
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6727

Abstract

DDoS attacks, which are becoming increasingly complex and frequent, pose significant challenges to network security, particularly with the rise of cyber exploitation of infrastructure. A major issue in detecting these attacks is the imbalance between normal traffic and attack data, which causes machine learning models to be biased toward the majority class. To address this, this study proposes the use of the Synthetic Minority Over-sampling Technique (SMOTE) to balance the CIC-DDoS2019 dataset, successfully enhancing the performance of a Multi-Layer Perceptron (MLP) in detecting various types of attacks. Analysis results indicate that, on the original dataset without SMOTE, the model achieved high accuracy but low F1-Score for minority classes, highlighting difficulties in recognizing underrepresented attack patterns. After applying SMOTE, the F1-Score significantly improved for minority classes, demonstrating the model's enhanced ability to identify attack patterns. All dataset subsets showed improved performance across key evaluation metrics, indicating that SMOTE effectively expanded the model's decision boundary for minority classes, enabling MLP to detect DDoS attacks more accurately in previously challenging data patterns. This approach illustrates increased model sensitivity to minority feature distributions without significantly compromising performance on majority classes.
Analisis Soal Tematik Bahasa Arab berbasis HOTS pada Kelas XII MAN 3 Jember Kafi, Fina Aunul; Ilma, Zidni
Al-Fusha : Arabic Language Education Journal Vol 4 No 1 (2022): January
Publisher : UAS PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62097/alfusha.v4i1.729

Abstract

The failure of learning Arabic can occur because of the measurability of the tests used to test students' abilities which results in information on student learning outcomes that are not mapped properly. This article aimed to analyze the HOTS-based Arabic thematic test items for class XII MAN 3 Jember in the 2020/2021 academic year in ar-riyāḍah and ash-syabāb material. Researchers used quantitative methods with item measurement techniques through the multiple-choice item analysis application Anates Version 4.0.2. The research findings showed that of the 15 questions tested, there were 9 questions that had not been HOTS, reliability was 0.78, and distractors number 4, 10, 11, and 14 could not be used. There were 4 questions with inappropriate interpretation and the rest were feasible with improvement. The questions being tested still need to be corrected both qualitatively and quantitatively.
Integration of Learning Theories to Build an Arabic Learning Ecosystem Kafi, Fina Aunul; Nurhadi, Nurhadi; Ilma, Zidni
Al-Fusha : Arabic Language Education Journal Vol 6 No 1 (2024): January
Publisher : UAS PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62097/alfusha.v6i1.1457

Abstract

In an effort to improve the effectiveness of Arabic language learning, a deep understanding of relevant learning theories and their application in a comprehensive learning ecosystem becomes fundamental. This study aims to establish the relationship between learning theories and the learning ecosystem implemented in Arabic classes at MAN 3 Jember. This research uses a qualitative approach with a case study type to collect data through in-depth interviews, observation, and document analysis. The results of this study show that the integration of cognitive, behavioris, and constructivis as learning theories into Arabic language learning in MAN 3 Jember can help create a conducive and comprehensive lear­ning environment ecosystem in building students’ knowledge and understanding through social interaction, collaboration, and reflection in the context of Arabic language learning.
Co-Authors Fauzi Adi Rafrastara Kafi, Fina Aunul Nurhadi Wildanil Ghozi