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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Journal of Telematics and Informatics Fountain of Informatics Journal Format : Jurnal Imiah Teknik Informatika JIEET (Journal of Information Engineering and Educational Technology) Jurnal Mantik Penusa Jurnal Informatika Universitas Pamulang Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Indonesian Journal of Applied Informatics Informatika : Jurnal Informatika, Manajemen dan Komputer CSRID (Computer Science Research and Its Development Journal) CCIT (Creative Communication and Innovative Technology) Journal JSAI (Journal Scientific and Applied Informatics) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Inkofar Jurnal Komtekinfo
Sinaga, Anita Sindar R M
STMIK Pelita Nusantara
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Medicine & Pharmacology Public Health Social Sciences Transportation

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Journal : Fountain of Informatics Journal

 1 
Real Time Database Seleksi Wajah Digital Menggunakan Algoritma CAMshift Anita Sindar RM Sinaga
Fountain of Informatics Journal Vol 5, No 1 (2020): Mei
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/fij.v5i1.3642

Abstract

AbstrakPerkuliahan yang ditempuh 4-5 tahun mempengaruhi perkembangan fisik. Penelitian ini menggunakan data video digital mahasiswa. Hasil rekaman video digunakan untuk data set menentukan ciri tertentu yang dimiliki mahasiswa nantinya tersimpan dalam katalog database file digital.  Dimulai dari konversi video .mp4 menjadi format .AVI. Algoritma CAMShift menggunakan dasar warna HSV untuk pelacakan posisi wajah (tracking) dan mengenal wajah (recognition). Video durasi 1-2 detik menghasilkan 45-200 frame format PNG. Algoritma CamShift melakukan penghitungan nilai Hue data sample. Hasil seleksi area bounding box disimpan dalam database wajah. Tracking wajah menggunakan Meanshift switching Matlab–OpenGL. Penelitian bertujuan mendokumentasikan profil wajah berbentuk digital berdasarkan warna dominan kulit. Hasil uji pencocokan wajah dilakukan pada beberapa video play, keberhasilan deteksi: 100% terseleksi, 45%-60%, 80-90%, disimpulkan sekitar 50%-100% berhasil. Gerakan wajah akan tertangkap centroid bounding box, bila warna wajah dominan Hue.Kata kunci: Algoritma Camshift; Database Wajah; Real Time; Seleksi Wajah; Warna Hue; Abstract[Real Time for Digital Face Database Selection Using Camshift Algorithm] Education taken 4-5 years affects physical development. This study uses student digital video data. The recording results are used to identify certain characteristics possessed by a student later stored in the digital file database catalog. The stages of the study consisted of identification, recognition and matching of faces. It starts from converting .mp4 videos to .AVI format. The CAMShift algorithm uses basic HSV colors for tracking face position (tracking) and faces recognition. 1-2 seconds video produces 45-200 frames PNG file. The research aims to document the digital profile of a face based on the dominant color of the skin. The face matching test results were carried out on several video play, the success of detection: 100% selected, 45%-60%, 80-90%, concluded around 50%-100% successful. Face movements will be caught by the centroid bounding box, if the color of the face is dominant in HueKeywords: Camshift Algorithm, Database Faces Face Selection; Hue Color; Real Time
Segmentasi Warna HSV Telapak Tangan Untuk Deteksi Bakteri Pada Pendemi Covid 19 Anita Sindar RM Sinaga; Endra Marpaung
Fountain of Informatics Journal Vol 5, No 3 (2020): Specials Issue November - Seminar Nasional Sains dan Teknologi
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/fij.v5i3.4925

Abstract

AbstrakMasa pendemi mengharuskan setiap warga negara mengikuti protokol kesehatan kapan dan dimana pun. Dianjurkan cuci tangan dengan air mengalir. Tangan termasuk organ penting perantara keluar masuk bakteri, jamur, virus dan berbagai kuman berbahaya yang secara langsung maupun tidak langsung. Dalam bidang pengolahan citra dikenal segmentasi warna. Proses ekstraksi ciri warna RGB, HSV dan ruang warna lainnya dapat menghasilkan akurasi yang tinggi dengan jumlah parameter ciri seminimal mungkin sehingga proses komputasi menjadi lebih cepat. Dalam penelitian ini, dilakukan proses segmentasi citra berwarna pada bakteri Bacilus yang menempel pada telapak tangan. Ekstraksi ciri warna dilakukan untuk mengklasifikasikan bakteri. Euclidean Distance untuk klasifikasi warna pada jarak minimum dua titik tetangga yang saling berdekatan (nearest neighbor). Jumlah kelompok terlebih dahulu ditentukan sebelum pengelompokan item berdasarkan analisa data. Ciri warna diekstraks menggunakan segmantasi warna, sedangkan ciri tekstur menggunakan analisis tekstur dengan deteksi BLOB (Binary Large Object). Segementasi berbasis clutering dapat mengidentifikasi tangan yang belum cuci tangan dan kondisi tangan sesudah mencuci tangan menggunakan sabun berdasarkan warna bakteri yang telah diekstrak.   Kata kunci: bakteri, telapak tangan, segmentasi warna, clustering, pendemi Abstract[HSV Color Segmentation of the Palm for the Detection of Bacteria in the Covid 19 Pandemic]. The pandemic period requires every citizen to follow health protocols anytime and anywhere. Hand washing under running water is recommended. The hand is a vital organ directly or indirectly as an intermediary for the entry and exit of bacteria, fungi, viruses, and various harmful germs. In the field of image processing, color segmentation is known. The extraction process for RGB, HSV, and other color space features can produce high accuracy with a minimum number of feature parameters so that the computation process is faster. In this study, a color image segmentation process was carried out on Bacillus bacteria attached to the hands' palms. The extraction of color features was carried out to classify bacteria. To classify colors in a certain color group, Euclidean Distance is used, finding the minimum distance between two points of the nearest neighbor. With K-Mean, the number of groups is determined in advance, and grouping is based on predetermined information. Color features are extracted using color segmentation, while texture features use texture analysis with BLOB (Binary Large Object) detection. Clustering-based segmentation can identify hands that have not been washed and the condition of hands after washing hands using soap based on the color of the extracted bacteria.Keywords: bacteria, palms, color segmentation, clustering, pandemic
Co-Authors Arjon Samuel Sitio Arjon Samuel Sitio Bosker Sinaga Desimeri Laoli Dewi Simanjuntak Endra Marpaung Jimmi Herdianda Gurusinga Julkari Sinta Parapat Murni Marbun Novi Sri Wanti Ginting Priskilla Parimanen Ravindran Ravindran Ricky Eka Putra Suciana Rahayu Sumitra Dewi