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All Journal JURNAL SISTEM INFORMASI BISNIS Riau Journal of Computer Science Jurnal CoreIT Jurnal Penelitian Pendidikan IPA (JPPIPA) JSFK (Jurnal Sains Farmasi & Klinis) Buletin Ilmiah Nagari Membangun Building of Informatics, Technology and Science Zonasi: Jurnal Sistem Informasi Bulletin of Computer Science Research Pharmaceutical Sciences and Research (PSR)
Rahmad Abdillah
Teknik Informatika Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Medicine & Pharmacology Nursing Physics Public Health Veterinary Other

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Journal : Jurnal CoreIT

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Security Testing Sistem Penerimaan Mahasiswa Baru Universitas XYZ Menggunakan Open Source Security Testing Methodology Manual (OSSTMM) Fernando, Yendri Ikhlas; Abdillah, Rahmad
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 2, No 1 (2016): Juni 2016
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (747.817 KB) | DOI: 10.24014/coreit.v2i1.2354

Abstract

Teknologi aplikasi web berkembang pesat sehingga digunakan untuk berbagai tujuan seperti keperluan akademik pada suatu universitas. Namun teknologi ini tidak bisa lepas dari tingginya ancaman kemanan yang tinggi sehingga bisa merugikan pihak-pihak tertentu. Pada dunia keamanan informasi dikenal security testing yakni suatu proses yang menguji seberapa tinggi tingkat kemanan suatu aplikasi yakni aplikasi web sehingga dapat diketahui nilai dan tingkat keamanan dan rekomendasi yang berguna. Salahsatu metode security testing yang efektif adalah Open Source Security Testing Methodology Manual (OSSTMM). OSSTMM adalah metode tertentu untuk melakukan security testing dan menyajikan hasil berupa RAV dan STAR. Aplikasi web yang diteliti adalah Sistem Penerimaan Mahasiswa Baru Universitas XYZ sehingga didapatkan hasil dan rekomendasi yang berguna dalam pengembangan lebih lanjut dimasa yang akan datang. Hasil penilaian yang didapatkan yakni dengan nilai Actual Security 74,5877.
SMS Phishing Detection Model with Hyperparameter Optimization in Machine Learning Abdillah, Rahmad; Insani, Fitri
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 1 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i1.35547

Abstract

Phishing is one of the growing cybersecurity threats, including through SMS, known as smishing. This research aims to build a model for SMS phishing detection using a machine learning approach optimized through hyperparameter tuning techniques. The data used is obtained from personal SMS messages collected through questionnaires, which are then labeled by information security experts. The SMS text is cleaned using Natural Language Processing (NLP) techniques and represented using the TF-IDF method. Ten classification algorithms are tested in this study: K-NN, Logistic Regression, Support Vector Machine (SVM), Decision Tree, Random Forest, AdaBoost, Bagging, ExtraTree, Gradient Boosting, and XGBoost. Hyperparameter optimization is performed using Grid Search and Optuna, and performance is evaluated using accuracy, F1-score, and ROC-AUC metrics. The results show that the SVM and Logistic Regression models performed the best, achieving accuracy up to 98.5%. Hyperparameter optimization techniques have proven effective in improving the performance of SMS phishing classification models. This research is expected to contribute to the development of accurate and efficient SMS phishing detection systems.
Co-Authors Amni, Hudiyah Ardiansyah, Aan Benardo, Benardo Dian Ayu Juwita Dwi Afrianti, Rezy Dwisari Dillasamola Elvia Budianita Fadhilah Syafria Fatma Sri Wahyuni Febi Yanto Fernando, Yendri Ikhlas Fitri Insani Harni, Yulia Iis Afrianty Julmiza, Adinny Meliani, Meliani Muhammad Fahri Najwa, Nina Fadilah Okfalisa Okfalisa Pasiolo, Lugas Pizaini Pizaini Putri, Adilah Atikah Rachmaini, Fitri Rahmi Yosmar Reski Mai Candra Rifqi, Melvi Auliya Simaremare, Harris Simaremare Srangenge, Yoneta Surya Agustian Suwanto Sanjaya Yufri Aldi