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All Journal Journal of Mechatronics and Artificial Intelligence
Muhamad Fajar Imanul Haq
Universitas Pendidikan Indonesia

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Air Quality Classification System using Random Forest Algorithm using MQ-7 and MQ-135 Sensors with IoT-based Aisyah Aira Putri Maharani; Rizky Hamdani Sakti; Muhamad Fajar Imanul Haq; Muhamad Ajis; Abdu Malikh Silaban
Journal of Mechatronics and Artificial Intelligence Vol. 1 No. 2 (2024): JMAI: December 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v1i2.75591

Abstract

Air is one of the essential elements in human life besides water and soil. However, currently the air quality in Indonesia is getting worse. Therefore, an air quality classification system using Random Forest algorithm based on CO and CO2 levels using IoT-based MQ7 and MQ13 sensors is needed as a smart solution. The workflow of this system begins with detecting air quality using the MQ-7 sensor for CO gas and the MQ-135 sensor for CO2 gas. Then, the classification process is carried out with the Machine Learning Random Forest algorithm by utilizing a number of training data that has been stored in the program to classify the gas sensor detection results into three types of classes, namely “Good”, “Bad”, or “Toxic”. The final output of this system is a website display that can be accessed on a PC/Laptop monitor in real time. From the results of the Random Forest machine learning algorithm classification testing process, 1 unsuitable data was found from a total of 100 trials that have been carried out. Therefore, the Random Forest machine learning algorithm can be said to be successful in detecting air levels in the surrounding environment well because it provides an accuracy value of 99%.
Cage Environment Monitoring System in Modern Livestock: A Literature Review Yohanes Adi Nugroho; Muhamad Fajar Imanul Haq; Reyhan Praditya Bagaskara; Diky Zakaria
Journal of Mechatronics and Artificial Intelligence Vol. 1 No. 2 (2024): JMAI: December 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v1i2.77243

Abstract

Livestock in Indonesia is one of the sectors that can have a considerable economic impact. However, livestock in Indonesia still implements conventional livestock models so that livestock in Indonesia can still be developed into modern livestock, one of the things that can improve the Indonesian livestock system is through a monitoring system or cage monitoring. Therefore, the author conducted a literature review to find out how the cage monitoring system on the livestock can work. Based on the study conducted by the author, the author can conclude that temperature, humidity, air quality, water quality and livestock movement are the parameters controlled by most researchers. These various parameters can be monitored so that the system can control gas levels, temperature & humidity. With this monitoring system, researchers believe that it can increase the level of effectiveness in terms of cost and time so that it can also indirectly increase the economic value of the livestock sector.
Co-Authors Abdu Malikh Silaban Aisyah Aira Putri Maharani Diky Zakaria Muhamad Ajis Reyhan Praditya Bagaskara Rizky Hamdani Sakti Yohanes Adi Nugroho