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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Informatika Jurnas Nasional Teknologi dan Sistem Informasi INFORMAL: Informatics Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SemanTIK : Teknik Informasi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI International Journal of New Media Technology Jurnal ULTIMATICS Jurnal ULTIMA Computing GERVASI: Jurnal Pengabdian kepada Masyarakat Community Development Journal: Jurnal Pengabdian Masyarakat Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Unri Conference Series: Community Engagement Community Empowerment Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Info Kripto Jurnal Ilmiah Edutic : Pendidikan dan Informatika Proceedings Series of Educational Studies Majalah Pengabdian Indonesia Jurnal Media Informasi Teknologi Mekongga: Jurnal Pengabdian Masyarakat Media of Computer Science

Jayanti Yusmah Sari

Universitas Sembilanbelas November Kolaka

Author-ID : 501844

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Other

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Title

Pengenalan Wajah Menggunakan Metode Linear Discriminant Analysis dan k Nearest Neighbor Fandiansyah Fandiansyah; Jayanti Yusmah Sari; Ika Putri Ningrum
Ultimatics : Jurnal Teknik Informatika Vol 9 No 1 (2017): Ultimatics: Jurnal Ilmu Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Face recognition is one of the biometric system that mostly used for individual recognition in the absent machine or access control. This is because the face is the most visible part of human anatomy and serves as the first distinguishing factor of a human being. Feature extraction and classification are the key to face recognition, as they are to any pattern classification task. In this paper, we describe a face recognition method based on Linear Discriminant Analysis (LDA) and k-Nearest Neighbor classifier. LDA used for feature extraction, which directly extracts the proper features from image matrices with the objective of maximizing between-class variations and minimizing within-class variations. The features of a testing image will be compared to the features of database image using K-Nearest Neighbor classifier. The experiments in this paper are performed by using using 66 face images of 22 different people. The experimental result shows that the recognition accuracy is up to 98.33%. Index Terms—face recognition, k nearest neighbor, linear discriminant analysis.

Sistem Pengenalan Bahasa Isyarat Indonesia dengan Menggunakan Metode Fuzzy K-Nearest Neighbor Agum Agidtama Gafar; Jayanti Yusmah Sari
Ultimatics : Jurnal Teknik Informatika Vol 9 No 2 (2017): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

The Indonesian Natural Sign System (SIBI) is one of the most natural languages of communication, especially for deaf and speech impaired. Deaf and speech impaired can understand and communicate with each other by using sign language, but some normal people will have difficulty understanding sign language with deaf and speech impunity to say. To overcome these problems need develop a system that is able to recognize the Indonesian Sign System (SIBI) which is expected capable of learning media in communicating between the deaf and normal humans. The introduction of the Indonesian Sign System (SIBI) will consists of three main stages: image acquisition, preprocessing and recognition. In this research the classification method used is Fuzzy KNearest Neighbor (FKNN) method. Based on the results of experiments conducted with the classification using the method Fuzzy K-Nearest Neighbor (FKNN) obtained an accuracy of 88%. Index Term— Fuzzy K-Nearest Neighbor, Sistem Isyarat Bahasa Indonesia (SIBI).

Perbaikan Kualitas Citra Untuk Klasifikasi Daun Menggunakan Metode Fuzzy K-Nearest Neighbor Asih Setiyorini; Jayanti Yusmah Sari
Ultimatics : Jurnal Teknik Informatika Vol 9 No 2 (2017): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Plants have many benefits for human life such as food, medicine, industry, environmental protection, even oxygen provider for other organisms. To know the types of plants is necessary. Classification of plants can be done with additional features of leaves in these plants. In determining whether or not the image identification process is needed a process of image quality improvement. Improved image quality is used to prepare the image in an ideal form so as not to cause problems and interpellation results as well. In this research the method used is Fuzzy K-Nearest Neighbor (FKNN) method. The Fuzzy K-Nearest Neighbor (FKNN) method is the most objective method. Based on the results of experiments conducted, Fuzzy K - Nearest Neighbor (FKNN) modeling method was obtained for 93% completeness. Keywords-Image quality improvement, Fuzzy KNearest Neighbor (FKNN)

Identifikasi Tingkat Kematangan Buah Pisang Menggunakan Metode Ektraksi Ciri Statistik Pada Warna Kulit Buah nina sularida limin; Jayanti Yusmah Sari; Ika Purwanti Ningrum Purnama
Ultimatics : Jurnal Teknik Informatika Vol 10 No 2 (2018): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Abstract—The Banana (musa paradical) is one of the national superior fruit production which is rich in vitamins. The level of banana production in Indonesia is above other fruit commodities. However, one of the postharvest problems for bananas produced on a large scale or industry is in the sorting of bananas. During this time the banana fruit is identified by the level of maturity based on the analysis of the skin color of the fruit visually the human eye that has limitations. The identification process like this has several disadvantages including requiring more energy to sort, and the level of perception of fruit maturity produced can be different because humans can experience fatigue, not always consistent, and human judgment is also subjective. To overcome this problem, this study builds a system to identify the maturity level of bananas using the extractive method of statistical features based on the skin color of bananas. The statistical feature extraction method used in this study is the maximum, minimum, and mean values of pixels for RGB and HSV color spaces. The system built has been tested using 40 datasets of image of bananas and shows the results of good accuracy. Index Terms—enter key words or phrases in alphabetical order, separated by commas

Deteksi Area Wajah Manusia Pada Citra Berwarna Berbasis Segmentasi Warna YCbCr dan Operasi Morfologi Citra Moh La Andi Rais Imran Yatim; Jayanti Yusmah Sari; Ika Purwanti Ningrum
Ultimatics : Jurnal Teknik Informatika Vol 11 No 1 (2019): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Face detection is one of the most important preprocessing steps in facial recognition systems used in biometric identification. Face detection is used to determine the location, size and number of faces in an image or video in various positions and backgrounds. One method used in face detection systems is segmentation based on skin color. In this study YCbCr skin color segmentation method and morphological operations were used. Based on the results of experiments conducted on 38 images, the system obtained an accuracy of 63.15%

Co-Authors A. Muhammad Idkhan Abdul Malik Abdullah Igo BD Adha Mashur Sajiah Agum Agidtama Gafar Agus Zainal Arifin Agustinus Suria Darme Amil A Ilham Andi Baso Kaswar Andi Baso Kaswar Andi, Ilham Arafat, Arafat Arief Budiman Aryadi Nurfalaq Asih Setiyorini Asih Setiyorini Aspian Achban Assagaf, Sayyed Auliani, Andi Nur Melly Bambang Pramono Bantun, Suharsono Chastine Fatichah Daiona, Abdullah Igo Baran Darme, Agustinus Suria Dewi Hastuti Dimas Febriyan Priambodo Eva Sapitra Fajar, Wahida Fandiansyah Fandiansyah Fandiansyah, Fandiansyah Firka Fransisca J Pontoh Hafidz Muhtar Hardianti Hardianti Hasnawati Munandar Henry Praherdhiono Hestiana, Sry Idkhan, A. Muhammad Ika Purwanti Ningrum Ika Purwanti Ningrum Ika Purwanti Ningrum Ika Purwanti Ningrum Purnama Ika Putri Ningrum Indar Ismail Jamaluddin Ingrid Nurtanio Isnawaty Isnawaty Jayawarsa, A.A. Ketut La Ode Hasnuddin S. Sagala Linda Purnama Muri Luh Putu Ratna Sundari Mardianto Mardianto Mardianto Mardianto Moh La Andi Rais Imran Yatim Muarif, Amar Muh. Abdi Fahmi Muh. Ariyandhi Masalu Muhammad Mail Muhammad Naim Muhammad Nur Khidfi Muhammad Syaiful Muhammad Syaiful Muhtar, Hafidz Mutmainnah Muchtar Naim, Muhammad Nanik Suciati nina sularida limin Ningrum, Ika Purwanti Nirsal Nirsal Nirsal Noorhasanah Zainuddin Novriadi, Teguh Nur Fajriah Muchlis Nur Inzani Reski Amalia Nurfagra Nurfagra Nurfalaq, Aryadi Nurfitria Ningsi Paisa Phradiansah ., Phradiansah Punaji Setyosari Purnama, Ika Purwanti Ningrum Putri, Sarnita Qammaddin Qammaddin R, Ranir Aftar Rabiah Adawiyah Rahman, Faizal Jumain Rahmat Karim Ranir Atfar R Rapa, Wiwi Rasmiati Rasyid Rendi Rendi, Rendi Reski Surya Aristika Ricky Ramadhan Rina Rembah Risnayanti Risnayanti Rizal Adi Saputra Saida Ulfa Sari, Indri Purnama Sarimuddin, Sarimuddin Sartika Sari Sartika Sari Sasmita, Anggit Sehan, Sahara Selviani Selviani Suci Pricilia Lestari Suharsono Bantun Suharsono Bantun Suharsono Batun Suharsono Suhar Syaban, Kharis Syahrul Syahrul Syamsuddin Teguh Novriadi Wiwi Rapa Wulandhany, Serly Yuwanda Purnamasari Pasrun Yuyun

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