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All Journal IJoICT (International Journal on Information and Communication Technology) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control eProceedings of Engineering Jurnal Rekayasa elektrika Jurnal INFOTEL LOGIC: Jurnal Penelitian Informatika
Pahlevi , Rizka Reza
Telkom University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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Journal : Jurnal INFOTEL

 1 
An Evaluation of SVM in Hand Gesture Detection Using IMU-Based Smartwatches for Smart Lighting Control Maya Ameliasari; Aji Gautama Putrada; Rizka Reza Pahlevi
JURNAL INFOTEL Vol 13 No 2 (2021): May 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i2.656

Abstract

Hand gesture detection with a smartwatch can be used as a smart lighting control on the internet of things (IoT) environment using machine learning techniques such as support vector machine (SVM). However, several parameters affect the SVM model's performance and need to be evaluated. This study evaluates the parameters in building an SVM model for hand gesture detection in intelligent lighting control. In this study, eight gestures were defined to turn on and off four different lights, and then the data were collected through a smartwatch with an Inertial Measurement Unit (IMU) sensor. Feature selection using Pearson Correlation is then carried out on 36 features extracted from each gesture data. Finally, two sets of gestures were compared to evaluate the effect of gesture selection on model performance. The first set of gestures show that the accuracy of 10 features compared to the accuracy of 36 features is 94% compared to 71%, respectively. Furthermore, the second set of gestures has an accuracy lower than the first set of gestures, which is 64%. Results show that the lower the number of features, the better the accuracy. Then, the set of gestures that are not too distinctive show lower accuracy than the highly distinctive gesture sets. The conclusion is, in implementing gesture detection with SVM, low data dimensions need to be maintained through feature selection methods, and a distinctive set of gesture selection is required for a model with good performance.
Room cleaning robot movement using A* algorithm and imperfect maze Vera Suryani; Kinkin Agustriana; Andrian Rakhmatsyah; Rizka Reza Pahlevi
JURNAL INFOTEL Vol 15 No 1 (2023): February 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i1.901

Abstract

Cleanliness is a mandatory requirement to help prevent virus spread. The cleaning process can be done automatically by humans or robotic devices. If a robot does this process, it is a must that the robot is able to explore the room autonomously. The robot movement in room tracking should reach all points without obstructions and return to its initial position. This study simulated the movement of a room explorer robot using the imperfect maze method, as well as searching a room that has not been explored using the A* algorithm. The A* algorithm was also used to find the shortest path to reach the initial place of the robot when the room exploration was completed. The results of the simulation showed that the imperfect maze could be used to explore the room well, and A* algorithm is quite optimal to be used for searching both the unexplored room and the path to return to its initial position
Co-Authors Aji Gautama Putrada Andrian Rakhmatsyah Bayu Aji Prakoso, Bayu Aji Bayu Erfianto Belva Rabbani Driantama Dicky Prasetiyo Fairus Zuhair Azizy Atoir Irfan Nugraha Kinkin Agustriana Mar Ayu Fotina Maya Ameliasari Muhammad Alkahfi Khuzaimy Abdullah Parman Sukarno Prayitno, Muhammad Ramadhan Rafie Afif Andika Seli Suhesti Shtevanie, Febryanti Subkhan Ibnu Aji Vera Suryani