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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) International Journal of Advances in Intelligent Informatics InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Data Science: Journal of Computing and Applied Informatics Jurnal Mantik Indonesian Journal of Electrical Engineering and Computer Science

Opim Salim Sitompul

Universitas Sumatera Utara

Author-ID : 2405303

Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Title

Enhancing Performance of Parallel Self-Organizing Map on Large Dataset with Dynamic Parallel and Hyper-Q Alexander F.K. Sibero; Opim Salim Sitompul; Mahyuddin K.M. Nasution
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

Self-Organizing Map (SOM) is an unsupervised artificial neural network algorithm. Even though this algorithm is known to be an appealing clustering method,many efforts to improve its performance are still pursued in various research works. In order to gain faster computation time, for instance, running SOM in parallel had been focused in many previous research works. Utilization of the Graphics Processing Unit (GPU) as a parallel calculation engine is also continuously improved. However, total computation time in parallel SOM is still not optimal on processing large dataset. In this research, we propose a combination of Dynamic Parallel and Hyper-Q to further improve the performance of parallel SOM in terms of faster computing time. Dynamic Parallel and Hyper-Q are utilized on the process of calculating distance and searching best-matching unit (BMU), while updating weight and its neighbors are performed using Hyper-Q only. Result of this study indicates an increase in SOM parallel performance up to two times faster compared to those without using Dynamic Parallel and Hyper-Q.

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

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

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.

Co-Authors Afriandy Sharif Alexander F.K. Sibero Andrew Handoko Dedy Arisandi Dennis Dennis Elviawaty Muisa Zamzami Erna Budhiarti Nababan Goklas Tomu Simbolon Hartono Hartono Jonas Franky R Panggabean Lubis, Arif Ridho Mahyuddin K. M Nasution Mardingsih Mardingsih Muhammad Khahfi Zuhanda Rahmad Nurhadi Yusra Romi Fadillah Rahmat Saib Suwilo Sarah Purnamawati Sawaluddin Nasution Seniman Tulus Tulus Yundari, Yundari Yuni Cancer

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