Article Per Year (5 Year)
p-Index From 2019 - 2024
1.376
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Informatika Komputer Jurnal Ilmiah Teknologi dan Rekayasa Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Ilmiah Matrik Jurnal Teknik Informatika (JUTIF)
Dessy Tri Anggraeni
Universitas Gunadarma
Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Other

Published : 10 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi

 1 
Perbaikan Citra Dokumen Hasil Pindai Menggunakan Metode Simple, Adaptive-Gaussian, dan Otsu Binarization Thresholding Dessy Tri Anggraeni
EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Vol 11, No 2 (2021): December
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/expert.v11i2.2170

Abstract

The use of digital images from scanned documents is commonly used both for data backup and for further processing. However, often the digital image obtained is not optimum due to various factors like noise. The method to improve the quality of digital images is to filter images using the Thresholding method. This study compares three Thresholding methods, which are Simple Thresholding, Adaptive-Gaussian Thresholding, and Otsu Binarization. All three methods have advantages and disadvantages. However, using the MSE and PSNR assessment parameters, the Simple Thresholding method shows better quality with an MSE value of 5,196.76, followed by Otsu Binarization with a value of 5,934.10, and Adaptive-Gaussian Thresholding with a value of 9,025.29. Meanwhile, by using PSNR, the value for Simple Thresholding is 13.37, followed by Otsu Binarization with a value of 12.47, and Adaptive-Gaussian Thresholding with a value of 10.31.
Analisis Sentimen Vaksinasi Booster Covid-19 pada Platform Twitter Menggunakan Metode Naïve Bayes Dessy Tri Anggraeni
EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Vol 12, No 2 (2022): December
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/expert.v12i2.2812

Abstract

Since the end of 2019, the Covid-19 virus hit the whole world, including in Indonesia. One of the efforts to deal with the Covid-19 virus is vaccination. In Indonesia, the government requires people to vaccinate 3 times, that are  First Vaccination, Second Vaccination, and Booster Vaccination. The public's response to the booster vaccine are varies. This study aims to reveal public sentiment towards booster vaccine activities. The research was conducted by collecting tweet data from the Twitter platform. The research was conducted by collecting data tweets from Twitter. The method used is the Naïve Bayes Classifier because the method is simple, the process is fast, and it has a fairly high level of confidence. In this method, public sentiment is divided into three, that are positive, neutral, and negative. The results showed that most people responded positively to this booster vaccine activity with a value of 56.8%, neutral as much as 39.9%, and negative as much as 3.3% with an accuracy rate of 86%.
Co-Authors Condro Wibawa Khalidah Khalidah Metty Mustikasari Qomariyah Qomariyah Wibawa, Condro