Fiber Optic Attenuation Analysis Based on Mamdani Fuzzy Logic in Gambir Area, Central Jakarta

Yuliza, Yuliza; Sari, Ninda; Muwardi, Rachmat; Lenni, Lenni; Rahmawati, Yosy

doi:10.26555/jiteki.v8i4.24549

Cited by 1 publication

(2 citation statements)

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“…In addition, it is also necessary to further investigate the effectiveness of tools in various sizes and more complex room layouts by trying other FIS methods, such as the Sugeno and Mamdani models. Especially in previous research work, these two methods produced good results in performance and accuracy [94], [99], [100], [137]- [140].…”

Section: Discussionmentioning

confidence: 77%

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Temperature and Humidity Control System with Air Conditioner Based on Fuzzy Logic and Internet of Things

Furizal,

Sunardi,

Yudhana

2023

Journal of Robotics and Control

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Work is an activity that takes most of the day to earn a living and improve the standard of living. During work, many people have to work indoors, which can be a less comfortable and unhealthy place if the temperature and humidity are not well controlled. Unsuitable temperature and humidity conditions can negatively affect the health and comfort of workers, as well as interfere with productivity and work quality. However, the problem that often arises is the difficulty of controlling room temperature and humidity effectively, especially in rooms that are closed and do not get air circulation from outside. Therefore, an effective solution is needed to control the temperature and humidity of the room automatically and remotely via the internet. The contribution of this research is to develop an effective and efficient AC control system in controlling room temperature and humidity using Tsukamoto's Fuzzy Inference System (FIS) method and the Internet of Things (IoT). Tsukamoto's FIS is used to produce AC temperature values in room temperature and humidity control as measured by the DHT22 sensor directly integrated with the ESP32 microcontroller. This control system is monitored remotely using IoT concepts through a mobile application interface. The results of this study show that room temperature can be controlled under normal conditions, with an average change of -1.67°C and an overall average temperature of 25.95°C. While the average humidity is at a value of 80.16% which is included in the Wet set. This suggests that humidity cannot be controlled under normal conditions, so it still requires further development. In addition, it is also necessary to further investigate the effectiveness of the tool in various sizes and more complex layouts of rooms.

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Section: Discussionmentioning

confidence: 77%

“…As a result, the inference output of each rule is provided explicitly (crisp) depending on the α-predicate [93]. A weighted average approach or other methods are used to obtain the final result [98]- [100].…”

Section: Fuzzy Logicmentioning

confidence: 99%