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Journal : Data Science: Journal of Computing and Applied Informatics

Genetic Algorithms Dynamic Population Size with Cloning in Solving Traveling Salesman Problem Erna Budhiarti Nababan; Opim Salim Sitompul; Yuni Cancer
Data Science: Journal of Computing and Applied Informatics Vol. 2 No. 2 (2018): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1177.754 KB) | DOI: 10.32734/jocai.v2.i2-326

Abstract

Population size of classical genetic algorithm is determined constantly. Its size remains constant over the run. For more complex problems, larger population sizes need to be avoided from early convergence to produce local optimum. Objective of this research is to evaluate population resizing i.e. dynamic population sizing for Genetic Algorithm (GA) using cloning strategy. We compare performance of proposed method and traditional GA employed to Travelling Salesman Problem (TSP) of A280.tsp taken from TSPLIB. Result shown that GA with dynamic population size exceed computational time of traditional GA.
Data Security Using Multi-bit LSB and Modified Vernam Cipher Goklas Tomu Simbolon; Opim Salim Sitompul; Erna Budhiarti Nababan
Data Science: Journal of Computing and Applied Informatics Vol. 3 No. 2 (2019): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (633.531 KB) | DOI: 10.32734/jocai.v3.i2-1048

Abstract

Data security is one of the most important aspects of today's information era. Some methods are used to secure important data from hackers. The LSB is a steganographic algorithm that is often used to store data in the last bit. In order to improve the security, we combine steganography with cryptography enables. In this research LSB is modified using the multi-bit LSB model. Modifications are made to the bits of each character, the rotation by a certain amount can randomize the plaintext content before cryptographic algorithm, Vernam is performed. The bit on LSB can be inserted data as much as 1, 2, 3 or 4 - bit information. The calculation results of MSE and PSNR values indicate that the use of 1-bit LSB is superior to that of 2-, 3-, or 4-bit LSB.
Detection of the Use of Mask to Prevent the Spread of COVID-19 Using SVM, Haar Cascade Classifier, and Robot Arm Pratiwi, Andini; Nababan, Erna Budhiarti; Amalia
Data Science: Journal of Computing and Applied Informatics Vol. 6 No. 2 (2022): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v6.i2-9289

Abstract

In the effort to hold up the case spread of COVID-19’s growth rate by implementing health protocols such as the use of masks, supervision is needed especially for the people who have not or still have problems to wearing masks. In this research, the system utilizes the robotic power to identify visitors whether they are wearing masks or not, and automatically distribute masks if the user is detected as not wearing a mask. The user face detection process uses the Haar Cascade Classifier algorithm and SVM (Support Vector Machine) to classify users who wear masks or not. For the user who is detected as not wearing masks, myCobot-Pi with the support of suction pump will distribute masks to users. The use of myCobot-Pi as a raspberry pi based robotic arm allows the application of the system on devices that are minimal in terms of specifications and size. Through trials by taking 41 examples of detection cases, 29 cases were found that managed to detect the correct use of masks. In addition, in this study we use PP sheet plastic protector to replace the packaging of the mask because it can be carried by the suction pump properly.