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Journal : Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control

Performance Comparisson Human Activity Recognition Using Simple Linear Method Kusuma, Wahyu Andhyka; Sari, Zamah; Minarno, Agus Eko; Wibowo, Hardianto; Akbi, Denar Regata; Jawas, Naser
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 1, February 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (731 KB) | DOI: 10.22219/kinetik.v5i1.1025

Abstract

Human activity recognition (HAR) with daily activities have become leading problems in human physical analysis. HAR with wide application in several areas of human physical analysis were increased along with several machine learning methods. This topic such as fall detection, medical rehabilitation or other smart appliance in physical analysis application has increase degree of life. Smart wearable devices with inertial sensor accelerometer and gyroscope were popular sensor for physical analysis. The previous research used this sensor with a various position in the human body part. Activities can classify in three class, static activity (SA), transition activity (TA), and dynamic activity (DA). Activity from complexity in activities can be separated in low and high complexity based on daily activity. Daily activity pattern has the same shape and patterns with gathering sensor. Dataset used in this paper have acquired from 30 volunteers.  Seven basic machine learning algorithm Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosted and K-Nearest Neighbor. Confusion activities were solved with a simple linear method. The purposed method Logistic Regression achieves 98% accuracy same as SVM with linear kernel, with same result hyperparameter tuning for both methods have the same accuracy. LR and SVC its better used in SA and DA without TA in each recognizing.
QoS Analysis Of Kinematic Effects For Bluetooth HC-05 And NRF24L01 Communication Modules On WBAN System Faiqurahman, Mahar; Novitasari, Diyan Anggraini; Sari, Zamah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 4, No 2, May 2019
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v4i2.826

Abstract

Wireless Body Area Network (WBAN) consists of a number of sensor nodes that are attached to the human body, and intended for monitor the human body condition. The WBAN system has several wireless communication modules that are used for sending or exchanging data between sensor nodes and gateway nodes or gateway nodes. There are some factors that are used to decide which communication modules should be implemented on WBAN system, including communication efficiency, distance range, power consumption, and the effect of mobility on QoS. In this study, we analyze the impact of the kinematic movement of sensor nodes on QoS parameter of HC-05 Bluetooth and NRF25L01 communication modules, during sending and receiving process among nodes. We assume that the sensor node and gateway node are attached on the limbs to catch the movement. We use Quality of Service (QoS) parameters such as delay, jitter, and packet loss, to analyze the impact of movement on communication modules. Based on the experimental result, it was found that the average value of delay and jitter for booth communication modules was slightly influenced by the speed of the sensor node movement. During the sensor node movement and data transmission, we found that the NRF24L01 module have a lower delay and jitter value than Bluetooth HC-05 module. The percentage of packet loss tends to be stable at 0% value, even though the speed value becomes higher.