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

— 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.


INTRODUCTION
Indonesia is one of the countries that has a summer every year [1].In this season, usually the temperature in the room feels hot, making it difficult for the body to concentrate [2].The difficulty of concentration can make productivity decrease so it is not uncommon in the room to always install air conditioners such as fans and Air Conditioners (AC) [3]- [5].In achieving a comfortable environment, temperature and humidity are important factors [6]- [8].Proper control of temperature and humidity is required in various sectors such as residential homes [9], industry [10], [11], agriculture [12], poultry farming [13], [14], and others.In industry or agriculture, uncontrolled humidity and temperature can reduce product quality and even damage it [15].While in a residential house, inappropriate humidity and temperature can affect the comfort of the occupants of the house.Then farm animals such as poultry may die if the temperature and humidity are incorrect.The same is true in other sectors.
Poor temperatures and humidity can cause problems in various sectors.Therefore, a temperature and humidity control system is needed that can control the room with high precision and accuracy.However, controlling temperature and humidity with conventional control methods still has a disadvantage, that is, it is less adaptive in controlling nonlinear systems.In addition, control with conventional control methods also tends to require accurate and detailed mathematical models, so that the design and arrangement process becomes more complex.Therefore, in this study the fuzzy control method will be used as an alternative to conventional control methods.
A fuzzy control method is a type of control that produces results based on input values for linked variables.This control method differs from traditional control methods in that it does not require a mathematical model of the controlled system.Therefore, the fuzzy control method is perfect for controlling complex and unpredictable non-linear systems.Basically, fuzzy control serves as a bridge between input and output.Fuzzy control techniques today have been used in various fields, including machine control, robot control, image processing control, and environmental system control.
One of the fuzzy methods is the Fuzzy Inference System (FIS) approach.This type of fuzzy has three models, one of which is the Tsukamoto model chosen for use in this study [16].This method was chosen because of its ability to solve uncertainty problems along with two other methods, namely probability and certainty factor [17].In addition to these reasons, the fuzzy method also has the ability to construct fuzzy values from assessment data and draw on the experience of experts without the need for training [18].FIS is a complete procedure that uses the set of inputs and outputs in the form of crisp numbers [19].All inputs are converted into linguistic fuzzy values at the fuzzification stage.After that, IF-THEN rules based on such linguistic values were developed.Then, using the AND, OR, and NOT operations, all possible combinations of fuzzy rules and membership functions are used to generate fuzzy output.In ISSN: 2715-5072 309 Furizal, Temperature and Humidity Control System with Air Conditioner Based on Fuzzy Logic and Internet of Things defuzzification, any approach is used to convert all fuzzy output into crisp values [20].
As a point of reference, many temperature and humidity control systems with various application functions, such as use in server rooms [21], [22], thermal [23], greenhouses [24], and others have been developed by previous researchers.The application of fuzzy logic and Internet of Things (IoT) to controlling room temperature and humidity is based on various reasons.These reasons mostly concern efficiency and health issues.Fuzzy logic is mainly used as a control system because it eliminates the ON/OFF paradigm seen in traditional control.To make it even better, a control system that uses a fuzzy approach such as FIS should be applied.This is corroborated by previous research showing fuzzy logic can contribute to a more optimal control system than an ON/OFF base [23].Whereas a fuzzy base gives a value from 0 to 1, the ON/OFF base only provides a value of 1 or 0. Another study used fuzzy logic to create a fan control system.The application of fuzzy logic this research is considered an energy-saving technique based on artificial intelligence [25].
In addition to the use of fuzzy logic, several related studies also discuss the advantages of utilizing IoT in control systems.For its users, IoT applications can make a significant contribution to convenience.According to one of the previous studies, the effect of implementing IoT is quite beneficial because it can improve user convenience, security, and intelligence [26].According to one other study, IoT systems are a good idea to provide convenience to users of digital technology.Any electrically powered device can be managed using the concept of IoT.Increased system efficiency greatly reduces the amount of electrical energy used by providing central control of the equipment [27].
In addition to some of the literature studies that have been described, this research is also based on previous studies that used fans as a control mechanism [28].This study shows that a fan that is turned in a closed room does not have too significant an impact in lowering the room temperature.The temperature of the room does not fall but becomes more and more up, although the increase that occurs is not too significant.Therefore, this study intends to continue previous research that was considered not to have obtained its proper target.This research will create a temperature and humidity management system using a fuzzy-based approach to IoT and air conditioning as a cooling tool based on literature studies as given.Temperature and humidity sensors will be used by this control system to continuously monitor conditions in the regulated space.The value will be processed by a fuzzy controller, which then generates an output that is used to control the cooling device in the controlled chamber.In the world of technology, IoT has made a great contribution in controlling the temperature and humidity of the environment due to the concept of connecting multiple devices together.IoT devices can be minicomputers, sensors, actuators, and other types of equipment [29]- [31].IoT enables interaction between different devices, making it easy to control temperature and humidity remotely.
This research uses ESP32 hardware as a microcontroller to implement an IoT-based fuzzy control system.The Espressif Systems introduced and created a family of microcontrollers, one of which is the ESP32.The ESP32 microcontroller is a replacement for the ESP8266 [32]- [34].These two microcontrollers are part of the NodeMCU family [35] along with NodeMCU LoRa [36].The WiFi module is available on this microcontroller and also has BLE (Bluetooth Low Energy) built into the chip.As a result, it is highly supportive and a suitable choice for building IoT application systems [37].This microcontroller will act as a processing center tasked with controlling all physically integrated devices [22].Basically the ESP32 has almost the same functions as Arduino and some other microcontrollers [38]- [40].This is evidenced by the use of Arduino codes that can also be used on the ESP32 [41], [42].The Arduino IDE is also compatible with this microcontroller [43].
The contribution of this research is to develop an effective and efficient air conditioning control system in controlling room temperature and humidity using FIS Tsukamoto and IoT methods.It aims to develop more accurate and adaptive fuzzy control techniques to improve the quality of controlled environments.The results of this study are expected to be compared with previous research to develop more optimal results.This comparison is also expected to present opportunities for the application of fuzzy control methods in the field of environmental control.

A. Stages of Research
Broadly speaking, this research consists of six stages, namely requirement analysis, design tools and mobile applications, developing tools and mobile applications, applying fuzzy logic to tools using coding, testing and analyzing the impact of tools, and drawing conclusions and suggestions for future research.
Requirement Analysis referred to in this study is to determine the research background, research objectives and benefits, and look for literature studies from previous research.This stage is considered important as the basis or cause of the research.After this stage is completed, then step on the stage of designing tools and mobile applications.
The stage of designing tools and mobile applications aims to make it easier to assemble tools and code applications in the development stage.The supporting application used in this stage is Adobe Photoshop 2020 [44], [45].After all the design is completed, then all these design applications are executed to produce products in the form of control tools and mobile applications.
The Developing tools and mobile applications stage is a stage that aims to develop all application designs and tools that have been made at the design stage.The mobile application is developed using Flutter [46]- [49].Flutter is a platform used to create multi-platform applications with only one coding base (codebase) [50]- [52].This means that the resulting application can be used on various platforms, both Android, iOS, web, and desktop mobile.Flutter has two important components, namely, the Software Development Kit (SDK) and also the user interface framework [53].SDK ISSN: 2715-5072 310 Furizal, Temperature and Humidity Control System with Air Conditioner Based on Fuzzy Logic and Internet of Things is a set of tools that function to make applications so that they can run on various platforms [54].While the UI framework is a UI component, such as text, buttons, navigation, and others, which can be customized as needed [55]- [57].Flutter is also a free and open-source platform [58], [59].Flutter was developed by Google using Dart programming [49], [60]- [62].
Next is the stage of applying fuzzy logic to the tools used to control room temperature.The fuzzy logic used is a type of FIS [63].The FIS model used is FIS Tsukamoto [64], [65].This fuzzy logic will play a role in adjusting the temperature of the air conditioner according to the input temperature and humidity of the room.This input indicator is measured in real time by a DHT22 sensor integrated with the ESP32 microcontroller as the processing center [66]- [68].After the fuzzy logic is finished coding inside the microcontroller, then the tool logic is tested and analyzed for its impact in controlling temperature and humidity in the room by utilizing air conditioning.After that, conclusions are drawn according to what has been obtained from the testing stage.If the test has deficiencies that have not been achieved, then suggestions are drawn for further research so that this research will be even better in the future.A summary of the research stages of this study is listed in Fig. 1.

B. Application Development Methods
This research uses the Waterfall model to create a mobile application which is one of the Software Development Life Cycle (SDLC) models [69], [70].This model is a model that is often used among existing models, such as spiral, incremental, agile and others [71], [72].This is based on the advantages of this method in terms of problem solving that is structured in analysis, design, implementation, testing, and maintenance that has been tested in solving problems [73].This old model is easy to learn [74].In the waterfall model, progress is observed flowing gradually downwards (like a waterfall).This implies that the development phase can only begin if the phase is before it is completed [75].In general, the SDLC waterfall model method has 5 phases, namely Requirement Analyst, Design, Development, Testing, and Maintenance [76], [77].All these stages have their own functions and roles.
The requirements analyst is the stage of defining the specifics of the software requirements, which refers to a complete and detailed description of the behavior of the program to be built.Functional and non-functional requirements that determine how users interact with the product to be developed [78].These characteristics include scalability, testing capabilities, availability, maintenance, performance, and quality requirements.
The design phase is the process of planning and troubleshooting software solutions.Software developers and designers must decide on a solution strategy, which includes algorithm design, software architecture design, database conceptual schema design, logic diagram design, concept design, graphical user interface design, and data structure definition [79], [80].All designs in this phase are then executed in the Development phase [81].
The development phase involves writing native code and compiling operational applications [82].All generated code will be tested and validated in the testing phase.The testing phase is the process of assessing whether a software solution meets the initial requirements and specifications and meets its intended purpose or not [83].After all the requirements have been met in the Testing phase, then it will enter the last phase, namely Maintenance.All errors that were missed at the previous stage are corrected as part of this phase [84].
A description of each stage in this Waterfall model can be seen in Fig. 2.

C. Fuzzy Logic
The logic known as fuzzy logic has a degree of vagueness between right and wrong.Fuzzy logic outperforms Boolean logic in terms of the idea of truth.Fuzzy logic replaces the level of truth for Boolean truths consisting only of values 1 and 0 [85].Fuzzy logic accepts the region between black and white (gray) as well as ambiguous linguistic terms such as "few", "passable", and "many" [86].Lotfi Asker Zadeh is an American Physicist of Iranian descent who first proposed and developed this concept through his 1965 article on fuzzy set theory [87]- [89].
Fuzzy logic can be applied in various fields such as in some cases science management, control theory, and decision theory.The advantage of fuzzy logic is that it is able to process reasoning linguistically (linguistic reasoning), so that in its design there is no need for mathematical equations of controlled objects.In general, fuzzy logic is used to solve problems involving components of uncertainty, inaccuracies, etc [90].This reasoning combines proper machine language with human language that focuses on meaning.This logic was developed on the basis of human language (natural language) [91].
FIS is a type of fuzzy logic used in this study [92].FIS or fuzzy inference machine is another name for a computer program that can perform reasoning on the same basis as humans do when using instincts [91].The crisp value is used as the input for the FIS process and the crisp value is also used for the output [93].This type of fuzzy has three models, namely Tsukamoto, Sugeno [31], [94], and Mamdani [95]- [97].
The FIS model used in this study is the Tsukamoto model.Any result of the IF-THEN rule in this model needs to be represented by a fuzzy set with monotonous membership functions.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].
Broadly speaking, this Tsukamoto model has three stages in producing outputs in the form of crisp values, namely fuzzification, machine inference, and defuzzification [101].Fuzzification is a process of converting a non-fuzzy (crisp) set into a fuzzy set [94], a non-fuzzy (crisp) input mapped to a fuzzy set form according to the variations of the input speech universe [102].One of the most important components in the fuzzification step is the membership function.The mapping between 0 and 1 for each data point in the input space is determined by a membership function in the form of a fuzzy curve [85].Membership in fuzzy sets has different shapes consisting of linear, bell, gaussian, trapezoidal, shoulder curves (left and right), and triangular shapes [103], [104].In this study, only two types of curves were used, namely the shoulder curve (left and right) and the triangle curve.The shape of the shoulder and triangular curves is depicted on Fig. 3.While the triangular curve notation is listed in Equation ( 1), the left shoulder curve notation in Equation ( 2), and the right shoulder curve notation in Equation (3).
After the fuzzification process, then there is the inference machine process.Fuzzy establishes theory-based rules in the form of IF-THEN statements used at the inference machine stage [105].Each of these rules will be executed by using logical operators.Zadeh divides these logical operators into three operators, namely the AND, OR, and NOT operators [106], [107].The AND operation is used to obtain the most minimum membership value between items in the relevant set (MIN).The representation of the AND operator is annotated like Equation ( 4).The OR operator relates to union operations on set.α-predicates as a result of operations with the OR operator are obtained by taking the maximum membership value between items in the relevant set (MAX).The representation of the OR operator is denoted like Equation ( 5).Meanwhile, the NOT operator is related to the complement operation of the set.α-predicates as a result of operations with the NOT operator are obtained by subtracting the value of the element's membership in the corresponding set from the value of 1(one) [108].The NOT operator is denoted like Equation (6).
The form of rule used in Tsukamoto's fuzzy is a rule with monotonous reasoning annotated as below: For example, two input variables are assumed, namely, x and y, as well as one output variable z.Then x is assumed to consist of two sets namely X1 and X2, while y is also divided into two sets Y1 and Y2, z also consists of two sets namely Z1 and Z2.Based on this description, four fuzzy rules can be formed as in Fig. 4. In addition, the visualization can be seen on Fig. 5.The final stage, known as defuzzification, is the next stage to be achieved after the inference machine stage.The purpose of defuzzification is to convert the results of the inference machine expressed as fuzzy sets into crisp values.The actions taken from fuzzy logic control are the result of conversion at this stage [109].This stage can be completed using several methods, such as centroid method, mean-max method, weighted average method, and center-of-gravity (COG) method [110], [111].While the defuzzification method used for this study is weighted average.The formula used in the weighted average method is as in Equation (7).
Equation (7) shows Z is the defuzzification, n is the number of terms to be averaged, wi is the weight applied to the value of x, and Xi is the value of the data to be averaged.

D. Internet of Things
The future use of computers will be able to surpass human labor and surpass human computing capabilities such as utilizing the internet to operate electronic devices remotely such as the Internet of Things (IoT) [112], [113].IoT is a frequent and interesting technology to discuss.IoT means that the internet is everything.This implies that the applied concept contains technologies, such as sensors and software connected to the internet for the purpose of interacting [36], [114], communicating and sharing data with other devices [115].It shows how the internet is actively influencing daily digital activities.With this, it will make it easier when you want to transfer data or communicate to someone as long as they still have a connection to the internet.It also opens up wide opportunities for automation, monitoring, and optimization in various fields, including healthcare, manufacturing, transportation, and others [116]- [118].
IoT gives people the ability to manage and optimize electronic equipment by using the internet [112], [113].The fundamental difficulty in IoT is bridging the gap between the physical and digital worlds, for example, how to process data collected from electronic equipment through user equipment interfaces.IoT devices may detect a variety of environmental factors, including temperature, humidity, and movement, as well as sophisticated machinery like autonomous vehicles or home appliances that can be connected to the internet.IoT combines several technologies that are broadly integrated into a single system, such as sensors that act as data readers, internet connections with various network topologies, radio frequency identification (RFID) [119], wireless sensor networks, and technologies that will continue to advance in answering needs [120]- [122].In its implementation, IoT works continuously and real-time, so this has the potential to produce a lot of data.This large amount of data can be utilized in various activities, such as forecasting [123], decision support systems, data pattern recognition, and others.
One of the technologies that is closely related to the concept of the IoT is M2M (machine-to-machine) [124].Smart gadgets are tools used in M2M because they can communicate.Smart devices were developed to assist humans in performing various jobs and solving the difficulties encountered.In response to this, IoT is one of the conveniences created to help everyone's work.The development of this technology is not easy and there are several steps that need to be taken in creating convenience for humans.IoT has a nickname as "the next big things" which makes it have great potential to be developed even better in the future [125].Because it can be said that this technology can make life much better.The working concept of IoT is explained on Fig. 6.Fig. 6.IoT working concepts Fig. 6 shows that broadly speaking, the concept of IoT has three interconnected parts, namely a microcontroller with a wireless module that will control devices (things), a network connection with data storage, and a platform as an interface for users.Devices that can be used such as air conditioners, televisions (TVs), lights, fans, and other electronic devices.The microcontroller will be a bridge device to access the internet by utilizing a wireless module.This wireless module will access the internet directly and access data from storage (data center).On the other hand, users can control the device through the application interface.This application will access data from data storage with the help of an internet connection.The application interface displayed to users can be various types of platforms, such as mobile, web, desktop, and others.

E. Design Tools and Applications
This design tool and application was designed using Adobe Photoshop 2020.The designed design takes into account all the necessary needs in the study.The design of these tools and applications aims to provide convenience in developing tools and applications into products that are ready to use.Building applications and tools without design will make the development process more complicated.This is because developers must develop applications while thinking about concepts that must be created simultaneously.Therefore, what must be done before developing is to design and conceptualize the applications and tools to be built.This research tool was built using the ESP32 microcontroller.This microcontroller was chosen because it is accompanied by an internal WiFi module [126], so there is no need for an external module to access the internet.This microcontroller is integrated directly with several components [68] such as KY-005 InfraRed Transmitter, I2C, PIR Sensor [32], DHT22 Sensor [68], and LED.While some other components such as LCDs are also integrated with ESP32 through I2C intermediaries as a link.AC and smartphones are also integrated wirelessly, namely smartphones through the internet network and AC via infrared.Infrared is electromagnetic radiation from wavelengths increasing in length from visible light, but increasing in short from radio wave radiation.The built suite of tools has been depicted on Fig. 7. Fig. 7. Tool design Fig. 7 explains that all components are integrated and work together so that a tool is formed as expected.ESP32 acts as a microcontroller that will become a data processing center.This microcontroller will control all the components that are integrated with it, both directly integrated and with other component intermediaries.The program code will be embedded in its memory, including code programmed for fuzzy logic.
Initially, the ESP32 will command the PIR sensor to detect the presence of humans in the room [32].If a human object is not detected, then the PIR sensor will detect again until the human object is detected.Once a human object is detected in the room, ESP32 will instruct the DHT22 sensor to read temperature and humidity.Then ESP32 will process this temperature and humidity with a fuzzy method to obtain the temperature value of the air conditioner which will be sent by the KY-005 IR Transmitter with an infrared signal.Then this value will be captured by the air conditioner and will be set to the temperature of the air conditioner.After that, the air conditioner will provide action to the room.The temperature and humidity generated by this AC action will be read again by DHT22 for processing again on the ESP32.This process will take place continuously and in real time.
On the other hand, ESP32 also sends data on room temperature, humidity, air conditioning temperature (fuzzy logic processing), and human presence (Boolean) to Firebase as a data center.This value will be accessed by the smartphone to display on its interface.In addition, smartphones can also provide action on the ESP32.But this action is not sent directly to ESP32 but rather through a Firebase intermediary, meaning that the smartphone will send the value to Firebase.Meanwhile, ESP32 will access the value provided by the smartphone on Firebase.A simple block diagram that will be applied by the tool in controlling the temperature and humidity of the room is contained in Fig. 8.In addition to tool design, mobile application design is also needed to make it easier to develop mobile applications using programming languages.In the professional world, this job is usually done by UI and UX Designers.UI Designer focuses on the appearance of the application, while UX Designer focuses on the user's feeling or experience when using the application.The collaboration between UI and UX Designer can create an application that is pleasing to the eye, responsive, and easy to use [127], [128].
The application in this study only consists of one interface.In this interface, users can see the status of the fan (ON/OFF), the status of human objects or not (bool type), room temperature, humidity, and air conditioning temperature.In addition, users can also provide several actions, namely activating the mode of turning on the air conditioner without human objects, selecting the automatic mode (with fuzzy logic), and selecting the manual mode (the AC temperature is set manually).The interface design of the mobile application is listed on Fig. 9.

F. Developing Tools and Mobile Application
The control tool in this study was developed using the Arduino IDE because in addition to being able to be used to develop Arduino microcontrollers, this application can also be used to develop ESP32 microcontrollers [129].The development of the ESP32 microcontroller control tool with Arduino IDE involves several basic steps, namely preparing hardware, software, carrying out the develop process to uploading the developed code into the ESP32 flash memory [43].
Hardware needs to be prepared in the form of research tools and supporting tools needed during the development process.In addition to hardware, software also needs to be prepared.Because these two components will be related.In the absence of software, the hardware cannot be operated and used.The required hardware is listed in Table I, while the software is listed in Table II.The device used to develop the tool.On this PC will be installed the software needed during the develop process 11 Breadboard Breadboard is a board that serves to design a simple electronic circuit.Tool prototypes can be tested without having to be soldered

USB cable
The cable used to connect the ESP32 microcontroller to a power source or USB port on the computer A library is a set of code that functions to simplify or simplify programming.The use of Arduino can be extended through the addition of libraries 3 Operating System (OS) The operating system does not affect the results to be obtained from the develop process.Develop can use operating systems such as Microsoft Windows, Mac OS, and others.
Similar to the tool development process, mobile application development also requires hardware and software preparation so that the development process can be carried out.However, the hardware required during developing mobile applications is relatively less when compared to developing tools.In this study, only three hardware were used, namely smartphones, PCs, and USB cables.Smartphones are used to run mobile applications developed on a PC using a connector in the form of a USB cable.Flutter framework was used in the creation of this mobile application.The framework was developed with the Dart programming language [49], [60]- [62].In the development process, Visual Studio Code (VSC) is used as a text editor by utilizing the extension provided to simplify the development process.
VSC is one of the open-source code editors that can be used for Windows, Linux, or Macintosh desktop computers [130].This application was created by one of the big companies in the field of technology, namely Microsoft [131].Despite being a powerful editor, VSC remains a lightweight program.Source code for various programming languages, including JavaScript, TypeScript, and Node.js, can be created and edited using this code editor.In reality, VSC is also compatible with various programming languages and operating systems, including Java, Python, PHP, and .NET.This is thanks to its extensive ecosystem and abundant availability of extensions [131], [132].

G. Applying Fuzzy Logic to the Tool
The FIS Tsukamoto method has an input variable and an output variable as objects for which the fuzzy value will be searched [133].Therefore, room temperature and humidity are used as input variables in this study.While the temperature of the air conditioner as the output variable.The details of the input and output variables are listed in Table III.
Temperature is a measure of the hot or cold intensity of an object or environment.Temperature is generally measured in units of degrees Celsius (°C) or Fahrenheit (°F), and can also be measured in units of Kelvin (K) on an absolute thermometer scale.Temperature is influenced by many factors, including heat emitted by the sun, human activities, weather, and many other environmental factors.Temperature has an important role in many fields, including physics, chemistry, and meteorology.Air humidity is a measure of water vapor content in the air.Air humidity can be measured in various ways, such as by using a hygrometer or hygrometer.The unit used to measure air humidity is the percentage of relative humidity (%RH).While AC temperature is the temperature that is regulated or selected on the air conditioning system or air conditioning device used to control the air temperature in the room.Air conditioners regulate temperature by taking hot air from inside the room and expelling cooler air.AC temperature is usually measured in °C or °F.
Table III describes the domain details on each set that have been formed from the fuzzy variables used.The ideal temperature and humidity domains for each country's body will vary [134].Many factors will influence this difference, one of which is the geographical condition of a country.Not only between different countries, but even the same country with different regions will also experience variations [135].In 2011, Indonesia's National Standardization Agency (BSN) sought to solve this variation problem by providing a comfortable temperature standard of 25.5°C Ta, a range of ±1.5°C Ta, and a relative humidity of 60% ± 5% [136].Based on this description, a temperature curve is formed at Fig. 10 and a humidity curve at Fig. 11.In addition to the variable membership function curve of the room temperature and humidity, there is also a variable curve of air conditioning temperature which acts as an output curve.The variable membership curve of AC temperature was obtained from the temperature range of air conditioners used in this study.The air conditioner temperature listed has a range of 18-32C.This range is divided into three fuzzy sets, namely Cold, Normal, and Hot.The shape of the air conditioner temperature curve is listed on Fig. 12.While the fuzzy rules applied are 25 fuzzy rules such as Table IV.This number is obtained from two input variables that have a fuzzy set of five sets each.

A. Testing and Analyzing the Impact of the Tool
The stage that will determine the impact of this research is the testing and analysis stage.This stage of testing and analysis is carried out after the tools and applications have been successfully developed and the fuzzy logic has been applied to the tools.This developed tool was tested in a room with a length of 600 cm, a width of 300 cm, and a height of 400 cm.The impact of this tool was tested by placing the DHT22 sensor in two different positions, namely in front of the air conditioner with a distance of 400 cm and 600 cm.The position of the AC and its DHT22 sensor are illustrated on the Fig. 13.
Each position of the DHT22 sensor on Fig. 13 was tested three times in a span of 30 minutes.Both of these positions are tested by turning on the air conditioner and analyzing their effect on the temperature and humidity of the room.Fuzzy logic is used directly to control the air conditioner temperature according to the room temperature and humidity inputs read by the DHT22 sensor in real-time.The test results of the DHT22 sensor in the first position are listed on Fig. 14, while the test results of the second position are listed on Fig. 15.On the left, the room temperature and air conditioning temperature are juxtaposed, while on the right is the pair between humidity and air conditioning temperature.The first sensor position test on Fig. 14 produced an almost identical output for the temperature in each test.A room that is given a higher air conditioning temperature, will make the temperature higher as well, so that when the temperature is in a high state, the temperature of the air conditioner will be lowered by fuzzy logic to lower the room temperature.The temperature value generated by fuzzy logic corresponds to the fuzzy literacy value obtained in each set on each of its variables (room temperature and humidity).Fuzzy logic is able to keep the temperature in normal conditions, which is 24-27C.This result is shown in Fig. 14  points a, c, and e.As for the humidity at Fig. 14 points b, d, and f show results that have not been maximized.Humidity has not been able to be directed to normal conditions (55%-65%).Meanwhile, testing the position of the second sensor in Fig. 15 showed almost the same results as testing the position of the first sensor.High temperatures can be lowered and maintained under normal conditions.Although the humidity is still the same, it is still uncontrollable to normal conditions.
In detail, the results of the recapitulation of measurements of the impact of fuzzy logic on temperature in the first and second positions are listed in Table V.While the recapitulation of the impact on humidity is listed in Table VI.

B. Discussion
Table V shows that fuzzy logic in controlling the air conditioner can have an impact on the temperature in the room.The test was carried out under initial temperature conditions ranging between 27.2C and 27.8C.After 30 minutes, the temperature changed with an average change in all tests of -1.67C, meaning the temperature dropped by an average drop of 1.67C.The average temperature in each test ranged between 25.61C and 26.30C, resulting in an overall average of 25.95C.This value is still included in the normal temperature set/category.This means that overall the temperature can be controlled under normal conditions.VI shows that fuzzy logic does not give the expected impact (controlling humidity to normal/standard conditions).The first sensor position test was performed at initial humidity conditions of 89.4%, 87.5%, and 85.7%.While the second sensor position test was carried out at initial humidity conditions of 88.1%, 67.9%, and 74.8%.After 30 minutes, six tests (three tests of the first position and three tests of the second position) resulted in three changes to higher values and three changes to values lower than the initial humidity value.Meanwhile, the average humidity in the entire test was at 80.16% (Wet set), meaning that humidity has not been able to be controlled under normal conditions.Even so, these results have given better results than the results in previous studies [28].In previous studies, the temperature could not be controlled to normal conditions by using a device in the form of a fan in a closed room.The results obtained showed that the temperature rose by an average of 0.3-0.5°Cwithin 40-75 minutes.While the implication of this study (using AC and the same method) is that the temperature can be controlled well in the normal range with an average temperature of 25.95 ° C (included in the normal set).But for moisture, further research is still needed to provide optimal results.

IV. CONCLUSION
This research shows that FIS Tsukamoto can have a good impact on the temperature in a room by utilizing air conditioning.The results showed that the temperature could be controlled under normal conditions, with an average change of -1.67C and an overall average temperature of 25.95C.However, the fuzzy logic of this model did not achieve the expected impact on humidity control to normal/standard conditions.From six tests conducted, the average humidity was at a value of 80.16% (Wet set).This indicates that humidity cannot be controlled under normal conditions, so it still requires further development.These results may be influenced by several factors that were not addressed in this study, so in future studies it is advisable to consider several other factors such as air quality, noise level, air circulation, light, number of human objects, individual comfort level as well as include user feedback or conduct user testing to ensure that the tools and mobile applications developed are easy to use and effective in meeting needs end user.
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].

Fig. 3 .
Fig. 3. Curves of the left shoulder, triangle, and right shoulder

Fig. 8 .
Fig. 8. Block diagram of tools in controlling the temperature and humidity

Fig. 15 .
Fig. 15.(a) Effect of fuzzy on room temperature in the first test, (b) Effect of fuzzy on humidity in the first test, (c) Effect of fuzzy on room temperature in the second test, (d) Effect of fuzzy on humidity in the second test, (e) Effect of fuzzy on room temperature in the third test, (f) Effect of fuzzy on humidity in the third test

TABLE I .
HARDWARE NEEDED WHEN DEVELOPING TOOLS

TABLE II .
SOFTWARE NEEDED WHEN DEVELOPING TOOLS

TABLE III .
MEMBERSHIP FUNCTION FORMATION SCHEME

TABLE IV .
FUZZY RULES

TABLE V .
RECAPITULATION OF THE IMPACT OF FUZZY LOGIC ON ROOM TEMPERATURE