Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) International Journal of Engineering, Technology and Natural Sciences (IJETS)
Intan Setiawati
Universitas Teknologi Yogyakarta
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
IMPLEMENTASI DECISION TREE UNTUK MENDIAGNOSIS PENYAKIT LIVER Intan Setiawati; Adityo Permana; Arief Hermawan
Journal of Information System Management (JOISM) Vol. 1 No. 1 (2019): Juli
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (235.112 KB) | DOI: 10.24076/joism.2019v1i1.17

Abstract

Hati merupakan salah satu organ manusia yang paling penting. UCI Machine Learning Repository mempunyai banyak dataset, salah satunya adalah dataset ILPD (Indian Liver Patient Dataset). Penelitian ini membahas tentang klasifikasi penyakit liver pada dataset ILPD menggunakan Algoritma Decision Tree C4.5. Berdasarkan hasil pengolahan yang dilakukan, didapatkan bahwa Algoritma Decision Tree C4.5 menghaasilkan nilai akurasi sebesar 72.67% dan juga membuktikan bahwa dari 11 variabel penyakit liver yang ada pada dataset ILPD, hanya 2 variabel (Almine Alminotransferase) yang menjadi pokok dalam penentuan penyakit liver.
Digital Watermarking Implementation Of Digital Watermarking On Images Using The Least Significant Bit Method Intan Setiawati; M. Thoni Hermanto; EIH Ujianto
Jurnal Internasional Teknik, Teknologi dan Ilmu Pengetahuan Alam Vol 5 No 1 (2023): International Journal of Engineering, Technology and Natural Sciences
Publisher : University of Technology Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46923/ijets.v5i1.191

Abstract

The ease of accessing the internet in this modern era has led to illegal crimes, especially data copying, data distribution and abuse of intellectual property rights. From these problems emerged a method of securing data and information, namely watermark. Watermark is used for data security techniques, both for copyright protection and digital signatures in the visible and invisible realms. One of the data security techniques used here is to use the least significant bit (LSB) method. This method is used for data security or images that contain watermarks, for example on currency there is usually a logo to distinguish real and fake currencies. This study uses nine host images taken from the https://www.kaggle.com/datasets/felicepollano/watermarked-not-watermarked-images dataset with different sizes, namely 513 x 513 pixels, 488 x 350 pixels, 467 x 350 pixels, 500 x 333 pixels, 512 x 301 pixels, 490 x 350 pixels, 500 x 332 pixels, 400 x 266 pixels, and 500 x 308 pixels. As for the label image, it uses the uty logo which has a size of 50 x 50 pixels, 80 x 80 pixels, and 124 x 124 pixels. From the results of the watermark test that has been carried out using the LSB method, the average PNSR value is 65 dB, so it can be concluded that the watermark research using the LSB method gets pretty good image results and can be used for data security. Keywords: Watermark, Least Significant Bit, Peak Signal to Noise Ratio (PNSR)
Co-Authors Adityo Permana Arief Hermawan EIH Ujianto M. Thoni Hermanto