ANALISIS COMPUTER VISION MENGGUNAKAN ALGORITMA HOG PADA VIDEO PENGUNJUNG GRAMEDIA CENTRAL PARK

PRATAMA, IDHA (2023) ANALISIS COMPUTER VISION MENGGUNAKAN ALGORITMA HOG PADA VIDEO PENGUNJUNG GRAMEDIA CENTRAL PARK. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Gramedia is one of the most visited bookstores in the Jakarta area. Currently, the calculation of visitors at Gramedia still uses a manual counting tool, namely the hand tally counter. Therefore the authors are interested in designing a system that can automatically calculate the number of visitors at one of the Gramedia located in Central Park Mall Jakarta. In this study, the authors used Computer Vision technology with the Histogram Of Oriented Gradients algorithm. The sample in this study was taken using the Simple Random Sampling technique, in the form of an mp4 video containing footage of visitors at the entrance to Gramedia Central Park Mall Jakarta. By utilizing the pre-processing stages such as resizing and grayscaling, then classifying using SVM to classify whether the detected object is human or not. Which results in an accuracy rate at POV or low angle in the form of an accuracy rate of 88.37%, and accuracy results with a high angle or POV recording produces an accuracy rate of 93.18%. Keywords: Computer Vision, Histogram of Oriented Gradients, Perhitungan Manusia, OpenCV Gramedia merupakan salah satu toko buku yang banyak dikunjungi di wilayah Jakarta. Saat ini perhitungan pengunjung di Gramedia masih menggunakan alat perhitungan manual yaitu hand tally counter. Oleh karena itu penulis tertarik untuk merancang suatu sistem yang dapat menghitung jumlah pengunjung secara otomatis di salah satu Gramedia yang terletak di Central Park Mall Jakarta. Pada penelitian ini, penulis menggunakan teknologi Computer Vision dengan algoritma Histogram Of Oriented Gradients. Sampel dalam penelitian ini diambil dengan menggunakan teknik Simple Random Sampling, berupa video mp4 yang berisi cuplikan pengunjung di pintu masuk Gramedia Centrall Park Mall Jakarta. Dengan pemanfaatan tahap pre-processing seperti resizing dan grayscaling, kemudian pengklasifikasian menggunakan SVM untuk mengklasifikasi apakah objek yang terdeteksi adalah manusia atau bukan. Yang menghasilkan hasil tingkat akurasi pada POV atau angle rendah berupa tingkat akurasi sebesar 88.37%, serta hasil akurasi dengan angle atau POV perekaman tinggi menghasilkan tingkat akurasi sebesar 93.18%. Kata Kunci : Computer Vision, Histogram of Oriented Gradients, Perhitungan Manusia, OpenCV

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 23 008
NIM/NIDN Creators: 41519010102
Uncontrolled Keywords: Computer Vision, Histogram of Oriented Gradients, Perhitungan Manusia, OpenCV
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
100 Philosophy and Psychology/Filsafat dan Psikologi > 150 Psychology/Psikologi > 154 Subconscious and Altered States and Process/Psikologi Bawah Sadar > 154.6 Sleep Phenomena/Fenomena Tidur > 154.63 Dreams/Mimpi > 154.634 Analysis/Analisis
500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik
500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: ADELINA HASNA SETIAWATI
Date Deposited: 13 Mar 2023 02:46
Last Modified: 13 Mar 2023 02:46
URI: http://repository.mercubuana.ac.id/id/eprint/75022

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