IMPLEMENTASI ARTIFICIAL INTELLIGENCE DALAM SISTEM PENCARIAN ORANG HILANG DENGAN FACE RECOGNITION STUDI KASUS POLRES KUDUS
DOI:
https://doi.org/10.36080/skanika.v8i1.3334Keywords:
HNSW, FAISS, PWA, OpenCVAbstract
This research aims to develop a missing person search system based on facial recognition technology to enhance the effectiveness and efficiency of identification. The system utilizes FaceNet to extract unique facial features from uploaded images, supported by OpenCV (haarcascade_frontalface_default.xml) for initial filtering, ensuring only images with detected faces are processed into the database. For managing large datasets, the HNSW (Hierarchical Navigable Small World) algorithm is implemented for fast indexing, while FAISS (Facebook AI Similarity Search) accelerates feature matching within extensive datasets. The system is designed as a Progressive Web App (PWA) with a user-friendly interface, accessible across various devices. Testing was conducted at the Kudus Police Department, yielding high identification accuracy and significantly faster search times compared to conventional methods. The PWA implementation ensures flexibility and ease of user access. This study concludes that the integration of modern technologies such as FaceNet, HNSW, and FAISS effectively supports missing person searches. These findings contribute significantly to the development of technology-based solutions for handling missing person cases.
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References
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[3] V. B. Anwari, “Implementasi Algoritma K-Nearest Neighbors Pada Analisis Sentimen Masyarakat Terhadap Penerapan Pemberlakuan Pembatasan Kegiatan Masyarakat.” SKANIKA: Sistem Komputer dan Teknik Informatika, vol. 5, no. 1, pp. 72-81, 2022.
[4] A. R. Hayati, “Image Searching Data Gambar Berwarna Algoritma K Means Clustering Pada Data Penjualan,” SKANIKA: Sistem Komputer dan Teknik Informatika, vol. 5, no. 2, pp 203-215, 2022.
[5] V. H. Nabilla, D. Fitria, D. Permana, and F. Fitri, “Comparison of Haversine and Euclidean Distance Formula for Calculating Distance Between Regencies in West Sumatra,” UNP Journal of Statistics and Data Science, vol. 1, no. 3, pp. 120-125, 2023.
[6] R. H. Madani dan S. Saputra, “Presensi Berbasis Progressive Web App (PWA) Menggunakan Laravel Dan Mysql,” Journal of Research and Publication Innovation, vol. 2, no. 3, pp 1909-1920, 2024.
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[8] Kepolisian Negara Republik Indonesia, "Jurnal Data Pusat Informasi Kriminal Nasional POLRI Tahun 2022," Jurnal Tahunan Pusiknas Bareskrim POLRI, 2022.
[9] Kepolisian Negara Republik Indonesia, "Jurnal Data Pusat Informasi Kriminal Nasional POLRI Tahun 2023," Jurnal Tahunan Pusiknas Bareskrim POLRI, 2023.
[10] S. Aitzhanov, et al. “Application of Facenet Machine Learning Model And Haar Cascade Classifier For Biometric Identification,” Journal of problem in computer science and information technologies, vol. 1, no. 3, 2023.
[11] C. Ryando, R. Sigit, S. Setiawardhana, and B. S. B. Dewantara, “Comparison of Machine Learning Algorithms for Face Classification Using FaceNet Embeddings,” The Indonesian Journal of Computer Science, vol. 13, no. 4, pp. 5767-5779, 2024.
[12] Cahyono, Ferry, “Pengenalan Wajah Menggunakan Model Facenet Untuk Presensi Pegawai.”, Masters Thesis, Institut Teknologi Sepuluh Nopember, 2020.
[13] M. H. Ramdani, I. G. P. S. Wijaya, and R. Dwiyansaputra, “Optimalisasi Pengenalan Wajah Berbasis Linear Discriminant Analysis Dan K-Nearest Neighbor Menggunakan Particle Swarm Optimization”, Jurnal Teknologi Informasi, Komputer dan Aplikasinya (JTIKA), vol. 4, no. 1, pp. 40-61, 2022.
[14] X. Sun, et al., “3rd Place: A Global and Local Dual Retrieval Solution to Facebook AI Image Similarity Challenge,” Arxiv - Computer Vision and Pattern Recognition, Des 2021.
[15] Raden Marissa Lestari, Santi Rahmawati, Rifda Triani Mutmainah, Devi Nuralim, Ignatius Wiseto Prasetyo Agung., “Pengenalan Wajah Menggunakan Algoritma K-Nearest Neighbors Dan Teknik Penggabungan Citra,” Jurnal Teknologi Pembelajaran Interaktif, vol. 4, no. 3, pp.16-28, 2024.
[16] Nunsina, A. Rahmi, and C. Fadhila, “Sistem Pengenalan Pola Wajah Secara Digitalisasi Menggunakan Metode Eigenface,” Jurnal Elektronika dan Teknologi Informasi (JETI), vol.3, no.1. pp. 8-16, 2022.
[17] E. G-Morato, et al., “A General Framework for Distributed Approximate Similarity Search With Arbitrary Distances”, Arxiv-Information Retrival, 2024.
[18] X.-B. He, P.-H. Tomas. Tam, G.-B. Long, and Y. Zhang, “Is an upturn commonly seen in Fermi-LAT GRB afterglow spectra?,” Arxiv-High Energy Astrophusical Phenomena, Feb 2020.
[19] T. Pricillia dan Zulfachmi, “Perbandingan Metode Pengembangan Perangkat Lunak (Waterfall, Prototype, RAD),” Jurnal Bangkit Indonesia, vol. 10, no. 1, pp. 6–12, Mar 2021.
[20] S. Lina, and M. Sitio, “Penerapan Metode Rapid Application Development (Rad) Untuk Aplikasi E Learning Berbasis Web, CV. Eureka Media Aksara”, 2023.
[21] E. C. Simanjuntak, R. R. Isnanto, and A. B. Prasetijo, “Perancangan Aplikasi Portofolio Mahasiswa Universitas Diponegoro Berbasis Web Menggunakan Kerangka-Kerja Laravel,” Jurnal Teknik Komputer, vol. 1, no. 4, pp. 182–191, 2023.
[22] N. Loubser, “Creating a RESTful API: Flask,” dalam Software Engineering for Absolute Beginners: Your Guide to Creating Software Products, Berkeley, CA: Apress, 2021.
[23] M. Utami, and E. D. Putra, “Metode Identifikasi Pengenalan Wajah Menggunakan Metode Haar Feature,” JSAI: Journal Scientific and Applied Informatics, vol. 6, no. 3, pp. 488–492, 2023,
[24] A. I. Pradana dan W. Wijiyanto, “Identifikasi Jenis Kelamin Otomatis Berdasarkan Mata Manusia Menggunakan Convolutional Neural Network (CNN) dan Haar Cascade Classifier,” G-Tech: Jurnal Teknologi Terapan, vol. 8, no. 1, pp. 502–511, 2024.
[25] A. Firmansyah, et al., “Sistem Absensi Mahasiswa Menggunakan Face Recognition Dengan Algoritma CNN,” Jurnal AI dan SPK, vol 2, no.8, pp. 250-258, 2024.
[26] O. Pribadi, “Aplikasi Pengenalan Wajah Menggunakan Algoritma Haar Cascade Classifier Dan Local Binary Pattern Histogram”, Jurnal Times (Technology Informatics & Computer System), vol. 12, no. 1, pp 40-47, 2023.
[27] H. Kurniawan, K. Kusrini, and K. Kusnawi, “Klasifikasi Pengenalan Wajah Siswa Pada Sistem Kehadiran dengan Menggunakan Metode Convolutional Neural Network,” Jurnal Media Informatika Budidarma, vol. 7, no. 2, pp. 846, 2023.
[28] A. K. Muttaqiin, H. Yuana, and M. T. Chulkamdi, “Implementasi Algoritma Convolutional Neural Network Untuk Pengenalan Ekspresi Wajah,” Jurnal Riset Sistem Informasi dan Teknik Informatika (JURASIK), vol. 8, no. 2, pp. 772–792, 2023.
[29] J. Homepage, I. Permana, and F. Nur Salisah, “Pengaruh Normalisasi Data Terhadap Performa Hasil Klasifikasi Algoritma Backpropagation”, Indonesian Journal of Informatic Research and Software Engineering, vol. 2, no. 1, pp. 158-168, 2022.
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Published
2025-01-30
How to Cite
[1]
A. A. Nur Hakim, A. C. Murti, and R. Nindyasari, “IMPLEMENTASI ARTIFICIAL INTELLIGENCE DALAM SISTEM PENCARIAN ORANG HILANG DENGAN FACE RECOGNITION STUDI KASUS POLRES KUDUS”, SKANIKA, vol. 8, no. 1, pp. 168–180, Jan. 2025.
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