Claim Missing Document
Check
Articles

Found 27 Documents
Search

IMPLEMENTASI HYBRID CNN, FACIAL LANDMARK DAN LIVENESS DETECTION PADA SISTEM ABSENSI WAJAH Akbar DB, Andi Muhammad; Faisal, Muhammad; AM Hayat, Muhyiddin
PROGRESS Vol 17 No 2 (2025): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i2.483

Abstract

This paper presents the implementation of a hybrid approach for face recognition attendance systems, combining Convolutional Neural Network (CNN), facial landmark detection, and liveness detection. The CNN model extracts facial features for identity recognition, while facial landmark detection captures dynamic movements such as eye blinking and mouth motion. Liveness detection ensures system robustness against spoofing attempts including photo and video replay. The system was developed using Python with OpenCV, MediaPipe, and TensorFlow, and tested under multiple spoofing scenarios. Results show a detection accuracy of 95.5%, with real-time performance and resilience against common spoofing threats.
Penerapan Machine Learning untuk Mengklasifikasikan Genre Musik Berdasarkan Fitur Audio Abrah, Rezkytullah; Hayat, Muhyiddin A M; Lukman , Lukman
Arus Jurnal Sains dan Teknologi Vol 3 No 2: Oktober (2025)
Publisher : Arden Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57250/ajst.v3i2.1699

Abstract

Penelitian ini bertujuan untuk mengembangkan sistem klasifikasi genre musik secara otomatis berdasarkan fitur-fitur audio yang diekstraksi dari file lagu. Proses ekstraksi fitur menggunakan pustaka Librosa untuk menghitung Zero Crossing Rate (ZCR), Spectral Centroid, dan 13 koefisien Mel-Frequency Cepstral Coefficients (MFCC). Setelah melalui proses normalisasi, fitur-fitur tersebut digunakan sebagai input dalam pelatihan tiga model klasifikasi: K-Nearest Neighbor (KNN), Random Forest, dan Naïve Bayes. Dataset terdiri dari lima genre musik populer dengan lebih dari 500 lagu. Hasil pengujian menunjukkan bahwa model Random Forest menghasilkan akurasi tertinggi dan mampu mengenali pola audio dengan baik, termasuk pada lagu-lagu yang tidak terdapat dalam data pelatihan. Sistem juga mampu menampilkan hasil ekstraksi fitur dan prediksi dalam bentuk visualisasi, sehingga memberikan transparansi dalam proses klasifikasi. Dengan pendekatan ini, sistem dapat digunakan untuk membantu analisis musik secara otomatis dan efisien.
A Bluetooth-Based Attendance System for Educational Administration at SMA Muhammadiyah: Cross-Platform Development and Usability Validation Hayat, Muhyddin A.M.; Rasyidi, Muhammad Fachri; Faisal, Muhammad; Bakti, Rizki Yusliana; Syamsuri, Andi Makbul
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.4873

Abstract

The transformation of educational administration through technology has accelerated significantly, particularly in attendance systems, which have traditionally relied on manual roll calls. These conventional methods are time-consuming, error-prone, and susceptible to manipulation. This study presents a novel Bluetooth-based attendance system that contributes to the field by demonstrating passive MAC address detection for automated attendance recording, eliminating the need for additional software installations on student devices. The system was developed using React Native for cross-platform compatibility, with PostgreSQL for data management and NestJS for backend processing. The software engineering process followed Rapid Application Development (RAD) methodology, combined with comprehensive system validation through experimental testing. Usability evaluation with 133 participants using the System Usability Scale (SUS) yielded a score of 79.85, categorizing the system within the "Good to Excellent" usability range. The findings demonstrate significant improvements in efficiency and a reduction in attendance fraud compared to conventional methods. However, hardware quality and device proximity remain key limitations. Future research should explore the integration of Bluetooth Low Energy (BLE) technology, the implementation of machine learning algorithms for anomaly detection, or the development of hybrid validation models that combine multiple authentication factors. This system demonstrates the potential to modernize educational administration through seamless, device-level integration while maintaining high user acceptance.
Game Edukasi Berbasis Android sebagai Media Pembelajaran Matematika untuk Anak Tunarungu Bakti, Rizki Yusliana; Wahyuni, Titin; Hayat, Muhyiddin A M; Ridwang, Ridwang
PROtek : Jurnal Ilmiah Teknik Elektro Vol 8, No 1 (2021): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v8i1.2377

Abstract

Education is a right for every individual. Not only those with normal conditions, but also those with special needs such as the deaf. Limited intellectual ability in deaf children has consequences for their difficulties in attending academic lessons including maths lessons. This research aims to create an application as a learning medium to attract deaf children in developing their intelligence. This application was created as a means to provide convenience to deaf children in helping the learning process of mathematics. This study uses observation data collection methods, interviews / questionnaires and library studies. The design method used is the waterfall and the testing technique used is Integration and System testing. The result of this study is an android-based game application named math games. The test results show that this application is easy to learn and there are media that make childrenhappy.
Stacking architecture-endpoint detection: a hybrid multi layered architecture for endpoint threat detection Wahid, Abd Rahman; Anggreani, Desi; Hayat, Muhyiddin A. M.; Abd Rahman, Aedah; Faisal, Muhammad
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1263-1280

Abstract

Modern endpoint threat detection systems face persistent challenges in balancing detection accuracy, resilience against zero-day attacks, and the interpretability of artificial intelligence (AI) models. Although deep learning (DL) approaches often achieve high accuracy on benchmark datasets, they remain vulnerable to adversarial perturbations and operate as opaque “black boxes,” thereby reducing trust and limiting practical adoption in critical infrastructures. This research introduces stacking architecture-endpoint detection (STACK-ED), a hybrid multi-layered architecture for endpoint threat detection. STACK-ED integrates three complementary paradigms: supervised learning for known attack patterns, self-supervised Fgraph-based learning for structural relationships, and unsupervised anomaly detection for emerging or unknown threats. The outputs are consolidated by a meta learner, followed by a post-hoc correction (PHC) mechanism to minimize false negatives. The framework was evaluated on a combined benchmark dataset (CSE-CIC-IDS2018 and UNSW-NB15, hereafter referred to as HIDS-Set). Experimental results demonstrate state-of-the-art performance, achieving an F2-score of 98.89% after hybrid integration and active learning, with the primary optimization objective being the reduction of undetected attacks. Furthermore, the Shapley additive explanations (SHAP) method enhances interpretability by revealing feature contributions, while the PHC successfully recovered 62.64% of missed zero-day candidates. The findings position STACK-ED not only as a highly accurate detection model but also as an adaptive, resilient, and transparent framework, offering practical implications for enterprise-grade endpoint defense and future zero-trust cybersecurity systems.
Implementasi Tanda Tangan Digital dengan Metode AES dan Deflate untuk Verifikasi Surat Permohonan KKP Lukman; Hayat, Muhyiddin A M; Nur, Muhammad Ikhsan
Journal of Muhammadiyah’s Application Technology Vol. 4 No. 3 (2025)
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/k6zs6353

Abstract

ABSTRAKTransformasi digital di lingkungan akademik menuntut adanya sistem verifikasi dokumen yang aman, efisien, dan mudah diimplementasikan. Penelitian ini bertujuan untuk mengimplementasikan tanda tangan digital dalam proses verifikasi Surat Permohonan Kuliah Kerja Profesi (KKP) dengan mengombinasikan algoritma Advanced Encryption Standard (AES) dan metode kompresi Deflate. Sistem dirancang melalui beberapa tahapan, meliputi preprocessing data surat untuk menggabungkan seluruh informasi penting ke dalam satu format string, kompresi data menggunakan metode Deflate, serta enkripsi menggunakan algoritma AES-128 dengan mode Cipher Block Chaining (CBC). Data terenkripsi selanjutnya dikonversi ke dalam bentuk QR Code yang berfungsi sebagai representasi tanda tangan digital. Proses verifikasi dilakukan dengan memindai QR Code menggunakan aplikasi client, kemudian dilakukan tahap dekripsi dan dekompresi untuk mengembalikan data ke bentuk aslinya. Hasil pengujian menunjukkan bahwa sistem mampu menjaga kerahasiaan dan integritas data, mempercepat proses verifikasi administrasi, serta meminimalkan potensi kesalahan manusia dalam pengelolaan dokumen. Dengan demikian, integrasi algoritma AES dan metode Deflate dapat diterapkan secara efektif sebagai solusi verifikasi dokumen digital di lingkungan akademik. Kata Kunci: Tanda Tangan Digital, AES, Deflate, Enkripsi, Dokumen Akademik   ABSTRACTDigital transformation in academic environments requires a document verification system that is secure, efficient, and easy to implement. This study aims to implement a digital signature system for verifying Internship Application Letters (Kuliah Kerja Profesi/KKP) by combining the Advanced Encryption Standard (AES) algorithm and the Deflate compression method. The system is designed through several stages, including preprocessing of letter data to merge essential information into a single string format, data compression using the Deflate method, and encryption using the AES-128 algorithm in Cipher Block Chaining (CBC) mode. The encrypted data is then converted into a QR Code, which serves as a digital signature representation. The verification process is carried out by scanning the QR Code using a client application, followed by decryption and decompression to restore the original data. The testing results indicate that the proposed system is capable of maintaining data confidentiality and integrity, accelerating administrative verification processes, and reducing human error in document management. Therefore, the integration of AES and Deflate proves to be an effective solution for digital document verification in academic institutions. Keyworsds: Digital Signature, AES, Deflate, Encryption, Academic Document
Penerapan Watermark‎‎‎‎‎ Tak Terlihat pada Materi Pembelajaran ‎Digital Menggunakan QR Code‎ dan Least Significant Bit Wahyuni, Titin; Hayat, Muhyiddin AM; khairat, arikal
Journal of Muhammadiyah’s Application Technology Vol. 4 No. 3 (2025)
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/hqt4ec35

Abstract

ABSTRAKPerkembangan bahan ajar digital meningkatkan risiko pelanggaran hak cipta dan pemalsuan konten, sehingga diperlukan mekanisme perlindungan yang tidak mengganggu tampilan visual. Penelitian ini mengimplementasikan watermark‎ing‎ tak terlihat dengan menggabungkan Quick Response (QR) Code sebagai pembawa informasi dan steganografi‎ Least Significant Bit (LSB) sebagai teknik penyisipan pada citra yang terdapat dalam dokumen. Sistem dikembangkan berbasis web dengan tiga modul utama: pembuatan QR Code‎, penyisipan watermark‎, dan validasi dokumen. Evaluasi dilakukan pada 10 dokumen berformat DOCX dan PDF dengan total 169 gambar. Kinerja imperceptibility diukur menggunakan Peak Signal-to-Noise Ratio (PSNR) dan Mean Squared Error (MSE). Hasil pengujian menunjukkan PSNR berada pada rentang 55,4–67,1 dB dengan MSE sangat rendah (0,02–0,19), menandakan kualitas visual citra tetap terjaga. Selain itu, seluruh watermark‎ berhasil diekstraksi (100%) dan QR Code‎ dapat dipindai tanpa kegagalan. Validasi integritas payload‎ secara opsional menggunakan CRC32 terbukti membantu memastikan keutuhan data yang disisipkan. Temuan ini menunjukkan bahwa kombinasi QR Code‎ dan LSB efektif, andal, dan efisien untuk melindungi bahan ajar digital dari penyalahgunaan tanpa menurunkan kualitas visual.Kata Kunci: Watermark‎ing‎ tak terlihat; QR Code‎; steganografi‎; Least Significant Bit; bahan ajar digital. ABSTRACTThe growth of digital teaching materials increases the risk of copyright infringement and content tampering, requiring protection mechanisms that do not degrade visual quality. This study implements an invisible watermark‎ing‎ scheme by combining Quick Response (QR) Code as the information carrier and Least Significant Bit (LSB) steganography for embedding within images contained in documents. A web-based system was developed with three core modules: QR Code‎ generation, watermark‎ embedding, and document validation. The evaluation used 10 DOCX and PDF documents comprising 169 images. Imperceptibility was assessed using Peak Signal-to-Noise Ratio (PSNR) and Mean Squared Error (MSE). Experimental results indicate PSNR values of 55.4–67.1 dB with very low MSE (0.02–0.19), confirming that visual quality is preserved. All embedded watermark‎s were successfully extracted (100%), and the QR Code‎s remained fully scannable without failure. Optional payload‎ integrity checking using CRC32 further ensured the correctness of embedded data. Overall, the proposed QR Code‎–LSB combination provides a reliable and efficient approach to protect digital teaching materials against misuse while maintaining visual fidelity.Keywords: Invisible watermark‎ing‎; QR Code‎; steganography; Least Significant Bit; digital teaching materials.