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

Internet of Things: Water Quality Classifying Based on Estimation Dissolved Oxygen Solubility and Estimation Unionized Ammonia for Small-scales Freshwater Aquaculture Shandikri, Rheza; Erfianto, Bayu
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vo. 6, No. 3, August 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i3.1329

Abstract

In aquaculture, poor water quality can affect fish growth and mortality. Water quality parameters such as ammonia, temperature, pH, and dissolved oxygen must be controlled and monitored. There are available measuring devices for dissolved oxygen and ammonia levels, but measurements cost is not suitable for small-scale aquaculture and are manually process. Our experimental study proposes the Emerson formula to find the estimated value of unionized ammonia and the Benson-Krause formula to find the estimated dissolved oxygen solubility value without using an ammonia sensor or dissolved oxygen sensor. Internet of things can be applied to aquaculture to monitor and collect water parameter data without human intervention. The values ​​of both estimates are validated using the Seneye Sensor. RMSE and MAE are used to calculate the performance evaluation between the Seneye value and the estimated value. Fuzzy logic clasify water quality derived from estimates of ionized ammonia and estimates of dissolved oxygen as input.
On the Experiment of Path Planning Using Multi-way Points with A* Algorithm for Autonomous Surface Vehicle Bayu Erfianto; Adysti Adrianne; Ramzy Rashaun Arif
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 6, No. 2, May 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i2.1244

Abstract

Commonly, surveillance activities on lake waters is mostly carried out by using a surface vehicle as special-designed vehicle, especially to conduct water quality measurements, underwater surveys, and bathymetry mapping. However, conventional survey and monitoring still involves humans on the site. If a survey is conducted during strong wind conditions, it could jeopardize surveyor’s safety. Therefore, a vehicle must have several criteria, e.g., it must be pretty spacious and comfortable to carry surveyors, free from engine vibrations, stabilized and easy to maneuver, and the surveyor's safety can be guaranteed. This paper discusses preliminary research aiming to develop an Autonomous Raft Vehicle (ARV), a type of autonomous unmanned surface vehicle. The ARV is equipped with autonomous control based on multi-way-points with an A* algorithm. Thus, a user only requires giving a command once initially during path planning. A* algorithm over multi-way-point could improve ARV navigation when there are obstacles along the predetermined trajectory. Hence the predetermined trajectory will be maintained throughout the mission. It is a significant contribution to this paper.
Forensic Analysis of Braking Classification Based on Acceleration, Jerk, and Velocity Data Bayu Erfianto; Andrian Rahmatsyah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vo. 6, No. 3, August 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i3.1284

Abstract

Nowadays, four-wheeled vehicles are equipped with an event data recorder (EDR) device to record sensors data. With advances in-memory technology, EDR provides evidence for forensic analysis after an accident happens, that uses information technology to facilitate forensic analysis to provide complete and valuable results using digital investigations. Several types of research have been conducted to reconstruct accidents from forensic data and Fuzzy Logic is an alternative method for classifying crash data taken from the accelerometer due to less complexity of implementation. Vehicle braking data is one of the most important evidence for digital investigation, since braking is a complex process determined by many factors, such as the condition of the vehicle, road construction, and the driver’s physiological condition. However, the existing digital investigation still process vehicle speed, deceleration, and varia- tion time of deceleration (known as a jerk) in separated manner to determine braking distance, driver response time, and braking category. The problem identified in this paper is how to use deceleration, velocity, and jerk to categorize the braking evidence forensic analysis. In this paper, forensic analysis is limited to produce forensic evident of braking events based on the collected data. The contribution of this paper is to propose a braking detection model by combining acceleration, speed, and jerk data into a Fuzzy Inference System. As a result, a forensic analysis of braking data can better understand the braking maneuvers, which can be further developed to identify the cause of the accident and provide recommendations on which actions to include in future analyses.