Mamdani Fuzzy Logic Research Articles

Application of Fuzzy Mamdani Method to Predict the Number of Blood Bags Based on Demand and Supply Data Using Matlab

Fuzzy logic is a control system technique in solving problems and is applied to systems, from basic systems to difficult or complex systems. Fuzzy logic is the proper method to plan an input space into an output space using MATLAB's mathematical theory of fuzzy sets. The reason for using fuzzy logic is because it is related to uncertainty. The unstable demand for blood bags in hospitals makes the supply of blood bags excessive or lacking from demand. The lack of blood supply results in the unfulfilled demand for blood needed by the hospital, while the excess blood supply worsens the quality of blood. In this study, we will predict the number of bags produced using the Mamdani Fuzzy Inference System (FIS) method based on the minimum demand and maximum demand values and the minimum supply and maximum supply that produce output from the defuzzification process. Applying the Mamdani Fuzzy Inference System (FIS) method based on demand and supply data obtains optimal output with MATLAB in predicting the number of blood bags produced. The results of the study showed that the Mean Absolute Percentage Error (MAPE) fuzzy logic Mamdani error value was 24%, the accuracy value of the Fuzzy Inference System (FIS) Mamdani in determining the number of blood bag production was 76%, and the production output generated through the Fuzzy Inference System (FIS) Mamdani was 4,774 blood bags. The number of blood requests at the hospital is 4,443 blood bags, so the amount of blood that must be produced to meet the hospital's demand is 4,774 bags.

Implementation of Fuzzy Logic Mamdani in Determining Employee Job Appraisal of PT Exclusive Panca Anugerah Using Matlab

Human resources are one of the important components of a company. With good employee performance, it can be interpreted that the system in the company is also running well. This method utilizes attendance and performance variables to assess the employee. This journal aims to see and monitor how an employee's performance in a company is working optimally or not. It uses the implementation of fuzzy logic Mamdani as a proof model, coupled with the Matlab application toolbox that allows evaluation and assessment of performance according to the existing scenario. The results of this experiment show the effectiveness of providing accurate scores and can also help management to make more informed decisions

Application of Fuzzy Logic Mamdani in IoT-Based Air Quality Monitoring Systems

This study aims to develop and implement an air quality monitoring system using Internet of Things (IoT) technology and Mamdani fuzzy logic. The system integrates sensors to detect PM2.5, PM10, and CO concentrations. Real-time data is processed using fuzzy logic to generate an easily understandable Indeks Standar Pencemar Udara (ISPU). Testing showed 95% accuracy in ISPU measurement, 2-second response time, and 99.5% uptime over 30 days. The Mamdani fuzzy logic effectively handles uncertain data, providing accurate air quality interpretations. The system classifies air quality into different ISPU categories (Good, Medium, Unhealthy, Very Unhealthy, Dangerous) in real-time. The study concludes that integrating IoT and fuzzy logic yields a high-performing, reliable air quality monitoring tool, significantly aiding pollution mitigation and public health. Further research is recommended to enhance algorithms and integrate additional technologies for improved functionality and accuracy.

Predicting Vehicular SO2 Emissions Using Artificial Neural Networks and Mamdani Fuzzy Logic: A Comparative Analysis

Predicting Vehicular SO2 Emissions Using Artificial Neural Networks and Mamdani Fuzzy Logic: A Comparative Analysis

EXPERT SYSTEM DIAGNOSES VARICOCHEL DISEASE USING MAMDANI'S FUZZY LOGIC ALGORITHM METHOD

Varicoceles form when valves in the veins that run along the spermatic cord (the structure that suspends the testicles in the scrotum) prevent blood from flowing properly. Most varicocele cases occur during puberty, from the age of 15 to 25 years. If there are symptoms that are not prolonged, treatment is not necessary. However, if a varicocele causes pain, shrinkage of the testicles, impaired fertility, or swelling, surgery will be performed. Symptoms of this disease are similar to hemorrhoids and bladder stones, so it takes an expert. In the research conducted on the Expert System Application for Diagnosing Hyperthyroid Disease with the Mamdani Fuzzy Logic Inference Method, it can be concluded that the expert system can store expert knowledge from experts in solving problems diagnosing hyperthyroid disease while Mamdani fuzzy inference is used for knowledge processing in order to obtain a more accurate diagnosis conclusion. definitely with accuracy . Making the application is expected to make it easier for people to get information without having to wait for the presence of a doctor/expert for varicocele disease, and is expected to reduce or even solve existing problems.

Identification of Social Media Addiction Levels on "TikTok" Among Students Using Mamdani Fuzzy Logic

According to data from the Global Web Index in their early 2023 survey, advertising sources published by Byte Dance indicate that TikTok has 109.9 million users aged 18 and above in Indonesia alone. This highlights the inevitable trend of teenagers becoming addicted to social media, particularly the TikTok app. Related parties are starting to notice this addiction issue, along with a noticeable decline in academic performance, possibly as a result of students neglecting their time by spending it on social media (TikTok). Analyzing variables such as usage duration, productivity impact, and neglect of social interactions aims to measure TikTok addiction among students using the Mamdani fuzzy logic method. Of the 75 respondents surveyed, 17.33% were identified as "Not Addicted", 72% were identified as "Addicted", and the remaining 10.67% were identified as "Highly Addicted". The results show that most students are already identified as addicted to TikTok. The Mamdani fuzzy logic method is considered effective in handling uncertainties in human behaviour. By utilizing MATLAB’s Fuzzy Logic Toolbox, this research models and evaluates addiction levels, providing insights to reduce excessive TikTok usage. This study also provides a strong foundation for future research exploring social media addiction on other platforms or among different populations. It encourages using technologies like MATLAB’s Fuzzy Logic Toolbox in educational contexts to address other complex problems.

Classification of Temperature and Humidity in Green Open Spaces by Implementing Internet of Things (IoT) using Mamdani Fuzzy Logic

The condition of green open spaces plays a pivotal role in influencing the comfort and well-being of users engaged in various activities within these environments. Hydrological and microclimate factors, particularly temperature and humidity, hold significant sway over the ecological balance in these areas. This study addresses the need for a tool to assess air temperature and humidity, facilitating public access to critical environmental data that impacts the psychological well-being of living organisms. In pursuit of this objective, a comprehensive monitoring system harnessing the power of the IoT was developed. This system integrates DHT22 and MQ-9 sensors to monitor temperature, humidity, and CO2 gas levels within multiple green open spaces. Data from these sensors is transmitted to a central database with minimal time delays: 2 seconds from the sensors to the server, 1 second from the server to the application, and 3 seconds from the hardware to the application. Impressively, this data transmission achieved a 100% success rate. To assess the comfort levels of these green open spaces, the system employs fuzzy Mamdani logic. It processes data obtained from the DHT22 sensor, using predefined temperature and humidity value thresholds. This innovative monitoring system provides valuable insights into the environmental conditions of green open spaces, contributing to the enhancement of the overall quality and suitability of these areas for various activities.

Analysis of Service Satisfaction Level at Batam Center International Port in Batam City Using the Fuzzy Mamdani Method

A port is defined as a facility and system where a port is a work environment consisting of a land and water area equipped with berthing and mooring facilities for ships, a place for loading and unloading, and boarding and disembarking passengers from one mode of sea transportation to another mode of transportation. In carrying out activities at the port, apart from providing sufficient facilities and equipment, quality services cannot be neglected. This research aims to analyze and determine how much influence the level of service provided has on the satisfaction response of ship passengers at the Batam Center International Port, Batam City. To carry out this research, the study used a literature review, observation, and distribution of questionnaires using a Likert scale and the Fuzzy Mamdani method. However, several challenges were encountered during the study. First, there was a difficulty in obtaining a representative sample of passengers due to the variability in passenger traffic and schedules. Second, the subjective nature of satisfaction measurement posed challenges in ensuring the accuracy and consistency of responses. Third, integrating the qualitative data from the Likert scale with the quantitative Fuzzy Mamdani method required careful handling to avoid misinterpretation The expected results from this research are the levels of satisfaction ship passengers feel regarding the dimensions of tangibles, reliability, responsiveness, assurance, and empathy. This will help determine whether passengers perceive themselves as satisfied or dissatisfied. Based on the analysis and discussion carried out with 50 respondents using the Likert scale method, the respondents stated that they were quite satisfied. This indicates that the Batam Center International Port, Batam City, is quite successful in providing satisfactory services to passengers. From the dimensions of reliability, responsiveness, assurance, empathy, and tangibles, overall consumers feel quite satisfied, with an average satisfaction percentage of 71% (35.5 out of 50 respondents). Similarly, the results obtained from the Fuzzy Logic Mamdani method show an output value for consumer satisfaction of 150 (within a range of 50–250), indicating that the level of consumer satisfaction with the services provided by the Batam Center International Port, Batam City, is quite satisfactory

Implementation of the Fuzzy Logic Mamdani Method in the KUB Chicken Egg Incubator

Poultry farming plays an important role in rural Indonesia's economy, with increasing demand for poultry meat and protein-rich eggs. One of the main challenges for farmers is the limited production of chicken seeds and suboptimal egg incubation methods. Modern egg incubators offer a solution with higher ease and efficiency compared to traditional methods. However, existing machines on the market have weaknesses, such as less accurate temperature and humidity control, and less optimal power source switching. The use of fuzzy logic methods in egg incubators has proven to be more efficient than manual methods, with a hatching success rate of 100% for 10 eggs. Fuzzy logic-based egg incubators start hatching earlier and more on days 18 and 19, while manual methods begin on days 19 and 20. The automatic egg-turning process in fuzzy logic machines saves labor and reduces the risk of error. This research highlights the importance of using accurate sensors and optimal temperature and humidity control systems to improve the success rate of chicken egg hatching. Index Terms—poultry farming; egg hatching; temperature; humidity; fuzzy logic

Improved Drycooler control by custom hybrid controller

Refrigeration devices designed for use in industrial environments are typically equipped with universal control algorithms, which require a minimal number of signals and parameters to ensure satisfactory device operation. These algorithms are typically of the PID type. This study elaborates upon the impact of using a dedicated hybrid controller, which was designed with specific consideration of the operating conditions of a given refrigeration device. The identified nonlinear Drycooler characteristics were used to support the controller at steady-state operating conditions. The system dynamics were supervised by a dedicated, experience-based designed hybrid fuzzy logic Mamdani type controller for both freecooling and compressor modes. The switchable configuration of the MISO control architecture results in a reduction in overshoots and oscillations in the system, a decrease in the time necessary for stabilization, a reduction in CO2, and an increase in control quality and energy efficiency.

Pengungkapan Kinerja Lingkungan Instansi Pemerintah Daerah Melalui Laporan Keberlanjutan Berbasis Global Reporting Initiative

Laundry washing is a crucial process in daily life. Although automatic washing machines have simplified the washing process, utilizing advanced technology like fuzzy logic control can enhance the performance of smart washing machines to achieve optimal washing results. This research aims to implement fuzzy logic control using the Mamdani method on smart washing machines to improve efficiency and washing quality. The research methodology consists of several stages. Firstly, analyzing variables that affect the washing process, such as laundry load, fabric thickness, dirt level, and water temperature. Next, designing a Mamdani fuzzy logic control system by determining membership functions for each variable and creating fuzzy rules to link input and output variables. Lastly, evaluating washing results based on predefined input variables. The research findings demonstrate that implementing Mamdani fuzzy logic control on smart washing machines can significantly enhance washing quality and adaptively determine washing parameters to achieve cleaner washing outcomes. Therefore, integrating Mamdani fuzzy logic control into smart washing machines has the potential to improve overall washing performance. In conclusion, utilizing Mamdani fuzzy logic control on smart washing machines is an effective step towards enhancing efficiency and effectiveness in laundry washing. This research contributes to the development of more adaptive and environmentally-friendly smart washing machine technology and plays a crucial role in advancing fuzzy logic control technology for other smart household applications.

Implementation of Mamdani Fuzzy Logic on PLN Electricity Sales in East Java

This research aims to provide innovation in the development of a smarter and more adaptive electricity distribution system, able to face the challenges that arise in the digital era. The results of this research can be a guide in improving the efficiency and reliability of electricity sales. The experimental method is applied by implementing mamdani fuzzy logic on PLN electricity sales data in East Java. From the results of the application of mamdani fuzzy by comparing the prediction results with the original data, the Mean Absolute Error (MAE) result is 0.17% and the Root Mean Squared Error (RMSE) value is 0.21%. So it can be concluded that fuzzy logic mamdani method can be used in predicting electricity sold and provide valuable guidance for PLN in improving the efficiency and reliability of electricity sales in the East Java region in a sustainable manner.

Application of Mamdani Fuzzy Logic System on Catfish Sorting System (Clarias sp.)

In catfish farming activities, there is a sorting process and a calculation process that is carried out manually or conventionally which causes a lack of effectiveness of labor and time in cultivation and causes fish wounds or injuries after the sorting activity. This research aims to make the sorting process easier and more flexible. By considering factors such as weight, length and other physical conditions in a fuzzy manner, the system can provide more accurate decisions in determining the quality and type of fish, increase sorting efficiency, and reduce errors in fish grouping process. Logic systems can provide more accurate assessments, allowing fish producers or traders to better sort fish according to market standards and consumer needs. The data analysis method used uses qualitative methods. Data is analyzed by identifying patterns, themes and categories through the coding and interpretation process. Fuzzification in the development of an automatic fish sorter uses weight (gram) and length (cm) parameters as input while the output is a measure of consumption. Using this tool is said to be more effective than conventional fish sorting.

Simulation of a Mathematical Model of Rail Transportation Scheduling Based on Bp Neural Network

Rail transportation, a cornerstone of modern logistics and passenger transit systems, plays a pivotal role in facilitating the efficient movement of goods and people across vast distances. Operating on a network of interconnected tracks, rail systems offer a reliable and environmentally sustainable mode of transportation, particularly for long-distance travel and freight shipments. The paper presents a comprehensive investigation into the application of advanced computational techniques in the realm of rail transportation management. Specifically, Mamdani fuzzy logic and Backpropagation (BP) Neural Networks are employed to address critical challenges in scheduling and classification within rail networks. The utilization of Mamdani fuzzy logic facilitates nuanced decision-making in scheduling processes, considering uncertainties and complexities inherent in rail operations. Through linguistic rules and fuzzy sets, the scheduling system can effectively adapt to various operational constraints and disruptions, leading to more resilient and efficient scheduling solutions. Additionally, the integration of BP Neural Network enhances classification accuracy and prediction capabilities, enabling precise forecasting of train movements, passenger flows, and other key variables.

Correlation Analysis of Teachers' Educational Technology Quality and Teachers' Professional Competence by Integrating Collaborative Filtering Algorithm

In today's educational landscape, the effective integration of technology into teaching practices is paramount for fostering engaging and impactful learning experiences. Central to this integration is the competence of educators and the quality of educational technology utilized. This study presents a novel approach to correlating teachers' educational technology quality with their professional competence, utilizing a fusion of collaborative filtering algorithm and Weighted Collaborative Mamdani Optimization (WCMO). By leveraging collaborative filtering, the model extracts patterns from historical data to recommend educational technology tools tailored to individual teachers' needs and preferences. The WCMO framework further refines these recommendations by incorporating weighted factors related to teachers' professional competence, ensuring a more nuanced understanding of their instructional requirements. WCMO considers the collaborative input from multiple stakeholders or sources, assigning weighted values to each input based on their relevance or significance. This collaborative approach allows for a more comprehensive analysis of the problem space, ensuring that diverse perspectives and factors are adequately accounted for in the decision-making process. Additionally, by leveraging Mamdani fuzzy logic, WCMO can handle imprecise or uncertain input data effectively, enabling more robust and adaptive optimization outcomes. Through extensive analysis and evaluation using real-world educational datasets, proposed approach demonstrates a significant correlation between teachers' technology quality and professional competence, achieving a correlation coefficient of 0.92. Moreover, qualitative assessments reveal the effectiveness of the WCMO-enhanced recommendations in enhancing teachers' instructional practices and technology integration.

Prediction on Target of Underprivileged Scholarships Using Fuzzy Logic Method

Education is key to the country's development, but in Indonesia, financial constraints for students often occur. In Java, population density and poverty are high, making it difficult for students. The government strives with scholarship programs, such as Bidikmisi/KIP Perguruan (Bidikmisi/KIP Lecture), Baznas Institute, KJMU, West Java Leadership Scholarship. However, scholarship disbursements often face misappropriation and discrepancies. Therefore, a Fuzzy Logic calculation is performed. This research uses the Mamdani Fuzzy Logic method to overcome this. This method is accurate and suitable for this study. The hope is that the distribution of scholarships will be more efficient and fair, focusing on those in need.

Sistem Smart Garden Tanaman Bayam Menggunakan Metode Fuzzy Logic

Treatment of Spinach, even though it has been given fertilizer, also keep on eye to monitor lots of water when watering. If the soil is too wet it will interfere with the absorption of nutrients needed for spinach growth. The use of technology makes it easy to monitor and control the condition of spinach plants in real time. Good soil moisture for spinach plants is in the range of 45% equivalent to a voltage value of 2.78 Volts to 60% which is equivalent to a voltage value of 2.03V. Meanwhile, soil that is suitable for growing spinach is soil that has a pH between 6-7. Mamdani fuzzy logic method is applied to a microcontroller as a reference in making decisions to regulate the speed of the water pump. There are five levels of pump speed for automatic watering of spinach from very fast to very slow to maintain stable soil moisture. Based on the test results, it is proven that the system can work correctly using Mamdani fuzzy with an error of 0.023%.

Sistem Pendukung Keputusan Penentuan Dakian Gunung Di Pulau Jawa Menggunakan Fuzzy Logic Mamdani

Mountain climbing is an activity with a relatively high level of danger that requires climbers to walk in the forest and spend quite a long time with increasingly low oxygen levels and very cold temperatures that can even reach 0 degrees Celsius. In this research, decisions play an important role in determining mountain climbing routes. especially on the island of Java which has a variety of mountains with different characteristics, therefore we help climbers in choosing mountain climbs that suit their individual preferences and personal conditions. The method used is Mamdani's Fuzzy Logic which can overcome uncertainty and complexity of information in decision making. To collect data regarding height, distance, track length and climbing costs, namely through interviews and related analysis. Fuzzy Logic Mamdani is implemented to manage and process related data and can produce output in the form of recommendations for climbing routes. This fuzzy model can integrate environmental variables, such as height, distance, cost and track length.

Drip Irrigation Control System based on Mamdani Fuzzy Logic and Internet of Things (IoT)

Drip Irrigation Control System based on Mamdani Fuzzy Logic and Internet of Things (IoT)

Menerapkan Konsep Logika Fuzzy Dalam Meningkatkan Efisiensi Persediaan Barang Dengan Menggunakan Metode Mamdani

Jars are one of the handicrafts used as a tool to fulfill daily life, and have social, ritual and artistic values. With good prospects to be developed considering the market potential that is increasingly widespread in its use. So that a good promotional strategy is needed to improve the urn product industry. The method used in this research is Fuzzy Logic Mamdani which can overcome uncertainty and complexity of information in decisions. For data collection in this study, namely by survey or asking directly to the urn seller. The objectives of this study include the application of Mamdani calculations, prediction of urn stock, and guidelines for determining the optimal amount of production. From the calculations obtained, demand increased by (0.029), products sold a lot by (0.105) and inventory increased by (0.222).