Garuda - Garba Rujukan Digital

p-Index From 2020 - 2025

4.741

P-Index

This Author published in this journals

All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Informatika JUTI: Jurnal Ilmiah Teknologi Informasi 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 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 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 Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

Published : 51 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4 5

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%

Pengenalan Finger Vein Menggunakan Local Line Binary Pattern dan Learning Vector Quantization Jayanti Yusmah Sari; Rizal Adi Saputra
Ultima Computing : Jurnal Sistem Komputer Vol 9 No 2 (2017): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

This research proposes finger vein recognition system using Local Line Binary Pattern (LLBP) method and Learning Vector Quantization (LVQ). LLBP is is the advanced feature extraction method of Local Binary Pattern (LBP) method that uses a combination of binary values from neighborhood pixels to form features of an image. The straight-line shape of LLBP can extract robust features from the images with unclear veins, it is more suitable to capture the pattern of vein in finger vein image. At the recognition stage, LVQ is used as a classification method to improve recognition accuracy, which has been shown in earlier studies to show better results than other classifier methods. The three main stages in this research are preprocessing, feature extraction using LLBP method and recognition using LVQ. The proposed methodology has been tested on the SDUMLA-HMT finger vein image database from Shandong University. The experiment shows that the proposed methodology can achieve accuracy up to 90%. Index Terms—finger vein recognition, Learning Vector Quantization, LLBP, Local Line Binary Pattern, LVQ.

ekspresi Mengidentifikasi Mood Mahasiswa Berdasarkan Ekspresi Wajah dengan Menggunakan Discrete Wavelet Transform dan Fuzzy K-Nearest Neighbor Nur Inzani Reski Amalia; Jayanti Yusmah Sari
Ultima Computing : Jurnal Sistem Komputer Vol 11 No 1 (2019): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Mood is a temporary emotional state. Mood usually has positive or negative quality values. Emotional intelligence has a role of more than 80% in achieving life success and is one of the factors that influence the students' capture power in the lecture process. By knowing the emotions of students, we can help capture students' ability during the lecture process, and the need for a system that can identify emotions that are formed during lectures.This system is built using the Discrete Wavelet Transform which transforms the image into 4 sub-images. The image of Discrete Wavelet Transform results looks rough or forms a face that can distinguish student expressions. The results of the Discrete Wavelet Transform image processing are classified using Fuzzy K-nearest neighbor. Classification is divided into three expressions, namely: Angry, Happy and Sad with accuracy of 77.49%

PENDIDIKAN DASAR KOPERASI (DIKSARKOP) SEBAGAI UPAYA MENINGKATKAN PENGETAHUAN PERKOPERASIAN ANGGOTA KOPERASI MAHASISWA Muhammad Syaiful; Suharsono Bantun; Jayanti Yusmah Sari; Abdullah Igo Baran Daiona; Teguh Novriadi
RESWARA: Jurnal Pengabdian Kepada Masyarakat Vol 3, No 2 (2022)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v3i2.1973

Koperasi pada umumnya memiliki masalah pada manajerial dan partisipasi anggota yang kurang aktif. Sementara hidup matinya koperasi tergantung partisipasi keseluruhan anggotanya. Koperasi mahasiswa merupakan sebuah koperasi yang berisikan para mahasiswa milenial yang tentunya memiliki kemampuan yang baik dalam mempelajari sesuatu dan mengaplikasikannya. Tujuan kegiatan ini dilaksanakan untuk meningkatkan pengetahuan perkoperasian para anggota koperasi mahasiswa sehingga partisipasi mereka semakin baik lagi dalam berkoperasi. Untuk itu Pendidikan dasar koperasi dirasa sangat perlu diberikan kepada anggota koperasi mahasiswa agar dapat memahami lebih jauh lagi terkait dengan perkoperasian sehingga dengan begitu partisipasinya dalam koperasi dapat meningkat. Kegiatan Pendidikan dasar koperasi ini dilaksanakan selama satu hari dengan menggunakan metode ceramah serta tanya jawab. Hasil dari pengabdian masyarakat ini terlihat adanya peningkatan pengetahuan perkoperasian para anggota yang dilihat dari hasil evaluasi yang dikemas dalam bentuk games kelompok

IDENTIFIKASI LANDMARK ORBITAL CEPHALOMETRY MENGGUNAKAN METODE FUZZY C-MEANS CLUSTERING Hasnawati Munandar; Ika Purwanti Ningrum; Jayanti Yusmah Sari
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Orthodontics is a branch of dentistry. In orthodontic treatment, several analyzes are needed, one of them is cephalometry analysis. Basically, cephalometry analysis is done manually, but this method requires a lot of time. In line with this, a computerized application is needed as a solution. In cephalometry analysis some landmarks are used as reference fields. Orbital is one of the landmarks that are difficult to identify. Orbital is located at the lowest point between the region of the eye cavity and the lower edge of the Orbital bone. One way to find Orbital landmarks is to segment the Orbital region. The segmentation aims to clearly separate the eye regions and Orbital bone in the cephalogram image. Fuzzy C-Means Clustering method is a segmentation method that can produce a clearer region partition. For this reason, the Fuzzy C-Means Clustering method is applied to get better segmentation results of the Orbital region so that the results of identification of the correct Orbital landmarks are obtained. Based on the results of testing on 90 image data provide an accuracy of 82.2% identification results with a cropping template size of 180 x 180 pixels.Keywords—Cephalometry Analysis, Fuzzy C-Means Clustering, Landmark Cephalometry, Orbital

RANCANG BANGUN APLIKASI PENDETEKSIAN KESAMAAN PADA DOKUMEN TEKS MENGGUNAKAN ALGORITMA ENHANCED CONFIX STRIPPING DAN ALGORITMA WINNOWING Muhammad Nur Khidfi; Isnawaty Isnawaty; Jayanti Yusmah Sari
semanTIK Vol 4, No 2 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

With the development of technology, the increase of acts of plagiarism in the world of education. Many students who did plagiarism in doing their task, thesis etc. Therefore, an application that can detect the similarity between text documents is required. This research used Enhanced Confix Stripping (ECS) Stemmer algorithm for text stemming process and Winnowing algorithm to calculate the similarity between documents. By specifying the gram and window values of the Winnowing algorithm, it made easier for the user to use the application without being confused to determine the value of the gram and the window to produce an accurate equality value. From the test results 5 pairs of chapters 1 thesis of students who categorized together produced a similarity score of about 45-20%.Keywords: Enhanced Confix Stripping (ECS) Stemmer, Winnowing, Similarity, Plagiarism.DOI: 10.5281/zenodo.1407866

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 Arief Budiman Aryadi Nurfalaq Asih Setiyorini Asih Setiyorini Aspian Achban Auliani, Andi Nur Melly Bambang Pramono Bantun, Suharsono Chastine Fatichah Daiona, Abdullah Igo Baran Darme, Agustinus Suria Dewi Hastuti Dimas Febriyan Priambodo Eva Sapitra Fandiansyah Fandiansyah Fandiansyah, Fandiansyah Fransisca J Pontoh Hafidz Muhtar Hardianti Hardianti Hasnawati Munandar Henry Praherdhiono Idkhan, A. Muhammad Ika Purwanti Ningrum Ika Purwanti Ningrum Ika Purwanti Ningrum Ika Purwanti Ningrum Purnama Ika Purwanti Ningrum, Ika Purwanti Ika Putri Ningrum Ilham Andi 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 Phradiansah ., Phradiansah Punaji Setyosari Purnama, Ika Purwanti Ningrum Qammaddin Qammaddin R, Ranir Aftar Rabiah Adawiyah Rabiuldien Amat, Rabiuldien Rahman, Faizal Jumain Rahmat Karim Ranir Atfar R Rapa, Wiwi Rasmiati Rasyid Reski Surya Aristika Ricky Ramadhan Rina Rembah Risnayanti Risnayanti Rizal Adi Saputra Saida Ulfa Sarimuddin, Sarimuddin Sartika Sari Sartika Sari Sehan, Sahara Selviani Selviani Suci Pricilia Lestari Suharsono Bantun Suharsono Bantun Suharsono Batun Suharsono Suhar Syaban, Kharis Syahrul Syahrul Syamsuddin Teguh Novriadi Wiwi Rapa Yuwanda Purnamasari Pasrun

Title

Found 51 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 51 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 51 Documents
Search