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All Journal Abdi Jurnal Publikasi OKTAL : Jurnal Ilmu Komputer dan Sains
Aldis Sahputra
Universitas Pamulang
Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences Other

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EDUKASI DIGITAL MARKETING Annisa Ayuningtyas; Rian Priadi Rhomadon; Muhamad Rayhan Fazri; Pratamar Dhika Pasca Anarki; Ani Kurniawati; Erfina Yuanita; Aldis Sahputra; Riza Jafar Sidiq; Wahid Aditya Permana; Ari Setia Gunawan; Suryaningrat
Abdi Jurnal Publikasi Vol. 1 No. 2 (2022): November
Publisher : Abdi Jurnal Publikasi

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Akselerasi perkembangan teknologi digital saat ini dipengaruhi oleh beberapa faktor seperti penggunaan teknologi internet, perkembangan smartphone, munculnya berbagai media sosial, berkembangnya e-commerce dan banyaknya masyarakat yang aktif menggunakan internet. Digital marketing adalah strategi atau upaya untuk memasarkan atau mempromosikan produk melalui segala jenis media digital, baik melalui internet atau jaringan lainnya yang saling terhubung. Dengan adanya seminar edukasi digital marketing yang diadakan mahasiswa Universitas Pamulang diharapkan para siswa dapat lebih mengenal tentang digital marketing, karena tujuan dari seminar ini sendiri untuk menambah wawasan serta menggali potensi para siswa di bidang digital marketing.
DETEKSI WAJAH BERBASIS SEGMENTASI WARNA KULIT MENGGUNAKAN RUANG WARNA YCbCr & TEMPLATE MATCHING Aldis Sahputra; Raden Azka Hermanto; Muhamad Anwar; Muhamad Reza Ghifari
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 2 No 07 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Face Detection is an important part of digital image processing to determine the location, size and number of faces in an image. Face detection is the initial stage in a facial recognition system that is used for personal identification, human-computer interaction, monitoring systems, criminal law and so on. This study presents face detection with skin color segmentation & template matching methods. The first step is to make a skin color model by transforming into YCbCr and then find the average number of facial skin colors. Next build a Gaussian distribution for the chroma chart which shows the possible skin colors. Adaptive thresholding is used to emphasize skin and non-skin areas presented in binary images. Segmentation of skin areas is done by labeling. Face candidates are obtained from calculating the number of holes in the segmented skin area, calculating the face width-to-height ratio and matching with the face template (template matcing). The centroid of the detected face is calculated and a marker is placed at the centroid of the face in the image. Based on trials with the Matlab 2011 tool with datasets taken from FDDB (Face Detection Data Set and Benchmark), the detection accuracy obtained from trials on 76 images with varied backgrounds and lighting levels reached 81.58%.
Co-Authors Ani Kurniawati Annisa Ayuningtyas Ari Setia Gunawan Erfina Yuanita Muhamad Anwar Muhamad Rayhan Fazri Muhamad Reza Ghifari Pratamar Dhika Pasca Anarki Raden Azka Hermanto Rian Priadi Rhomadon Riza Jafar Sidiq Suryaningrat Suryaningrat Wahid Aditya Permana