Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal TELEKONTRAN: Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan
Muhammad Aria
Unknown Affiliation
Computer Science & IT Control & Systems Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Algoritma Perencanaan Jalur Kendaraan Otonom di Lingkungan Perkotaan dari Sudut Pandang Filosofi Kuhn dan Filosofi Popper Muhammad Aria
Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Vol 7 No 2 (2019): TELEKONTRAN vol 7 no 2 Oktober 2019
Publisher : Program Studi Teknik Elektro, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1123.944 KB) | DOI: 10.34010/telekontran.v7i2.2627

Abstract

Autonomous vehicles can be useful to improve safety, efficiency, accessibility and convenience of transportation. One important task that must be carried out by autonomous vehicles is to do path planning through a dynamic urban environment where there are other vehicles and pedestrians. According to Kuhn's philosophy, a science has its own life cycle. The science life cycle consists of the birth phase, the proof phase and the acceptance phase of the new science into what is called normal science. Likewise with the scientific development of path planning algorithms, path planning algorithms for autonomous vehicles are still being researched and developed by various researchers. New studies continue to be conducted in an effort to find pathway planning techniques that can be generally accepted, so that the algorithm will become a normal science. According to Popper's philosophy, each proposed algorithm must be tested using the principle of falsification to determine whether the proposed technique can eventually become a normal science or not. So this paper aims to provide an overview of the scientific cycle of planning autonomous vehicle lanes. This paper also aims to compare the latest research on path planning algorithms for autonomous vehicles in urban areas. In comparing these algorithms, the principle of Popper's falsification will be used. The comparison results presented in this paper will help gain insight into the advantages and disadvantages of each algorithm, and will also help to choose the algorithm used in the design of autonomous vehicle systems. Keywords ­: Autonomous vehicles, path planning algorithms, urban environment, Khun’s scientific cycles, Popper’s falsification
Perancangan Sistem Home Automation Dengan Kendali Perintah Suara Menggunakan Deep Learning Convolutional Neural Network (DL-CNN) Lery Sakti Ramba; Muhammad Aria
Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Vol 8 No 1 (2020): TELEKONTRAN vol 8 no 1 April 2020
Publisher : Program Studi Teknik Elektro, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1272.967 KB) | DOI: 10.34010/telekontran.v8i1.3078

Abstract

The purpose of this research is to design home automation system that can be controlled using voice commands. This research was conducted by studying other research related to the topics in this research, discussing with competent parties, designing systems, testing systems, and conducting analyzes based on tests that have been done. In this research voice recognition system was designed using Deep Learning Convolutional Neural Networks (DL-CNN). The CNN model that has been designed will then be trained to recognize several kinds of voice commands. The result of this research is a speech recognition system that can be used to control several electronic devices connected to the system. The speech recognition system in this research has a 100% success rate in room conditions with background intensity of 24dB (silent), 67.67% in room conditions with 42dB background noise intensity, and only 51.67% in room conditions with background intensity noise 52dB (noisy). The percentage of the success of the speech recognition system in this research is strongly influenced by the intensity of background noise in a room. Therefore, to obtain optimal results, the speech recognition system in this research is more suitable for use in rooms with low intensity background noise.
Algoritma Perencanaan Jalur Kendaraan Otonom berbasis Hibridisasi Algoritma BFS dan Path Smoothing Muhammad Aria
Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Vol 8 No 1 (2020): TELEKONTRAN vol 8 no 1 April 2020
Publisher : Program Studi Teknik Elektro, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (420.081 KB) | DOI: 10.34010/telekontran.v8i1.3083

Abstract

Abstract - In this paper an alternative algorithm is designed for autonomous vehicle path planning. The proposed algorithm is a hybridization of the Breadth First Search algorithm (BFS) and the path smoothing algorithm (BFS - path smoothing). Based on observations from the test results, the advantage of the BFS algorithm is that it can provide solutions that lead to optimal solutions, but has the disadvantage of high computational time. In order to obtain an optimal solution, then the path produced by the BFS algorithm will be further processed by the path smoothing algorithm. Although the BFS - path smoothing algorithm has a high computational time, but for the purpose of getting an optimal solution, the BFS - path smoothing computation time is still lower than the RRT* algorithm to get the optimal solution. RRT* algorithm is one algorithm that is commonly used for autonomous vehicles path planning. This hybridization process is carried out by first running the BFS algorithm to provide an initial solution. The initial solution is then improved by using the path smoothing algorithm to obtain an optimal solution. The BFS-path smoothing algorithm is tested in simulations using several existing benchmark cases, namely narrow, maze, trap and clutter environments. The optimality criteria that are compared are path costs and computational time. In testing, the performance of the BFS-path smoothing algorithm is compared with the performance of the RRT* algorithm. We show that the proposed algorithm can produce path output with higher quality than the path produced by RRT *. Keywords ­: Breadth First Search, path smoothing, path planning, simulation testing, RRT*
Co-Authors Lery Sakti Ramba