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Journal : JAIS (Journal of Applied Intelligent System)

An Enhancement of One Time Pad Based on Monoalphabeth Caesar Cipher to Secure Grayscale Image Christy Atika Sari; Lalang Erawan; Eko Hari Rachmawanto; De Rosal Ignatius Moses Setiadi; Tan Samuel Permana
Journal of Applied Intelligent System Vol 2, No 2 (2017): December 2017
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v2i2.1616

Abstract

Image is an object that has been used by various people since long ago. Utilization of these images evolve in line with advances in technology. Image in this information technology era is not only in a physical form, there is also a form of so-called digital image. Many people use digital images for personal use, so prone to be manipulated by others. Cryptographic technique, such as Caesar Cipher and OTP is a security techniques that can be applied to the digital image to avoid manipulation or theft of data image. The result is, an image can be read only by the sender and the recipient's image alone. Combined the two algorithms have fast turnaround time, up to 0.017791 seconds for the image to the size of 512x341 and 0.032302 seconds for the image to the size of 768x512. In addition, the resulting image has a very low degree of similarity,  with the highest PSNR value obtained is 6.8653 dB. It can be concluded that the combined algorithm and OTP Caesar Cipher algorithm is fast and difficult to solve.
Prediction of Sleep Disorders Based on Occupation and Lifestyle: Performance Comparison of Decision Tree, Random Forest, and Naïve Bayes Classifier Lestiawan, Heru; Jatmoko, Cahaya; Agustina, Feri; Sinaga, Daurat; Erawan, Lalang
(JAIS) Journal of Applied Intelligent System Vol. 8 No. 3 (2023): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i3.8987

Abstract

Health is a very important thing in life. Therefore, to maintain health, we need adequate rest. Without adequate rest, the body will not be healthy and fit. In this study, a person's sleep disorder prediction will be made based on their lifestyle and work. The predictions made will classify sleep disorders that are absent, sleep apnea and insomnia from certain lifestyles and work. The methods used to make predictions are decision tree classifier, random forest classifier and naïve Bayes classifier. The test was carried out using a total of 375 data which was broken down into 70% training data and 30% testing data. The results obtained after testing with test data are by using the decision tree classifier algorithm to get an accuracy of 89.431%, using the random forest classifier algorithm to get an accuracy of 90.244% and by using the naïve Bayes classifier algorithm to get an accuracy of 86.992%.