Examining child obesity risk level using fuzzy inference system

Sari, Febrina; Desyanti, Desyanti; Radillah, Teuku; Nurjannah, Siti; Julimar, Julimar; Pakpahan, Juwita Yanti

doi:10.11591/ijphs.v10i3.20928

Cited by 3 publications

(5 citation statements)

References 32 publications

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“…al, 2019). Fuzzy Inference System, also called fuzzy inference engine, is a system that can evaluate all rules simultaneously to produce conclusions, and the order of the rules can be arbitrary (Sari et al, 2021). The Fuzzy Inference System can be carried out using the Tsukamoto method (Reynaldi et.…”

Section: Fuzzy Inference System (Fis)mentioning

confidence: 99%

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Heart Disease Diagnosis Using Tsukamoto Fuzzy Method

Hakim

Fajriati

Pratama

2023

J. Adv. Inf. Syst. Tech

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As one of the leading causes of death in the world, heart disease needs special attention. Heart disease often causes sudden death because the signs of a heart attack are not easy to detect. However, early detection efforts can still be pursued and continue to be carried out, especially using information technology. This study aims to diagnose the risk level of heart disease using Tsukamoto method and involving 11 input variables such as cholesterol, blood pressure, ECG, and others. At the same time, the output variables include healthy, small, medium, large, and very large. The stages of the method consist of four main processes, namely literature review, fuzzy inference system design, applying of Tsukamoto fuzzy, and evaluation. The research concluded that the fuzzy logic of the Tsukamoto method can be used to diagnose the risk level of heart disease, although the model performance is still limited to an accuracy value of 58%.

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Section: Fuzzy Inference System (Fis)mentioning

confidence: 99%

“…The Fuzzy Inference System can be carried out using the Tsukamoto method (Reynaldi et. al, 2021;Permadi & Alamsyah, 2020), the Mamdani method (Damayanti et al, 2022), and the Sugeno method (Sari et al, 2021;Reynaldi et. al, 2021).…”

Section: Fuzzy Inference System (Fis)mentioning

confidence: 99%

Heart Disease Diagnosis Using Tsukamoto Fuzzy Method

Hakim

Fajriati

Pratama

2023

J. Adv. Inf. Syst. Tech

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“…The purpose of forming fuzzy rules is as an input and output statement. Each rule is a function where the operator that connects two inputs is AND and the one that maps the input-output is IF-THEN [12]. Based on the fuzzy input consisting of weight and height variables, each having three fuzzy sets, and the Body Mass Index output variable with 5 fuzzy sets, 9 rules are formed as shown in TABLE 1.…”

Section: ) Fuzzy Logic Flowchartmentioning

confidence: 99%

“…Fuzzy logic methods can use for determining nutritional status include the Mamdani method, the Takagi Sugeno method, and the Tsukamoto method [10]. In this study, the Mamdani method is used as a determinant of nutritional status, whereas the Mamdani method is also known as the Min-Max method [10], [12]. The Min-Max method is a search for the minimum value in each rule which then looks for the maximum value from the combined consequences of each rule.…”

Section: Introductionmentioning

confidence: 99%

A Design of Body Mass Index (BMI) and Body Fat Percentage Device Using Fuzzy Logic

Faradisa

Muhammad

Girindraswari

2022

Indones.J.electronic.electromed.med.inf

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Nutritional status is something that should consider because it is related to the level of health. Poor health can lead to malnutrition and death. The purpose of this study is to create a tool with a system that can determine the value and category of Body Mass Index (BMI) automatically using fuzzy logic to maintain nutritional status. However, because BMI can only decide underweight or overweight, it is necessary to determine the fat percentage based on the British Journal of Nutrition. In determining BMI and fat percentage, a load cell weight sensor with a capacity of 200 kg as a bodyweight measurement, an ultrasonic sensor HCSR-04 as a body height measurement, and a keypad that functions to enter a name, age, gender, and type of activity data. Database in this system can provide and store easier and real-time data, so the data output is accessible directly. The results are analyzed by comparing the measurement with standard tools. The BMI test taken 5 times, showed that the categories in the system (very thin, thin, normal, heavy, obese) were the same as the MATLAB test and manual calculations. Meanwhile, the results of testing body fat percentage taken 4 times also show the same category as the Body Monitor tool. So, this system can use for daily to monitor the condition of nutritional status and fat percentage in real-time.

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“…Thus, the research builds a Fuzzy Inference System (FIS) in MATLAB according to the Mamdani method. Mamdani method produces an output in the form of a value in the domain of the fuzzy set, which is categorized into linguistic components (Sari et al, 2021;Ahmad Shukri & Isa, 2021).…”

Section: Introductionmentioning

confidence: 99%

Implementation of Fuzzy Mamdani Method to Classify Public Health Level in North Sumatra Province

Sihombing

Dahlia²

2022

ComTech

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Health is one of the most important fields aspects in people’s lives. Public health is influenced by several factors, such as environmental factors and lifestyle. Every year, the government makes a program to improve people’s health and welfare. Therefore, the government needs to obtain information about the classification of public health levels to monitor the progress of the programs that have been carried out. The research created an interface application to classify the level of public health in North Sumatra Province. The research classified the public health level using data from Badan Pusat Statistik (BPS) in 2018. Next, the application was made using the Matlab 2013b GUI. Classification of the level of public health was carried out using the Fuzzy Mamdani method that generated public health classification levels based on the inputted indicators. Then, the level of health classification was divided into four parts: low, lower middle, upper middle, and high. The result shows that for the 2018 data, some cities/ districts are still at low health levels. However, many cities or districts have good health levels. The final result can be used as a reference for the government to analyze which cities/districts should be paid attention to improve their health and welfare.

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Examining child obesity risk level using fuzzy inference system

Cited by 3 publications

References 32 publications

Heart Disease Diagnosis Using Tsukamoto Fuzzy Method

Heart Disease Diagnosis Using Tsukamoto Fuzzy Method

A Design of Body Mass Index (BMI) and Body Fat Percentage Device Using Fuzzy Logic

Implementation of Fuzzy Mamdani Method to Classify Public Health Level in North Sumatra Province

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