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In the increasingly competitive Industry 4.0 era, companies need to forecast product demand to meet consumer needs and improve operational efficiency. CV Mamifood Sukses Abadi, an MSME that produces milk and cheese-based foods, has faced sales fluctuations in the last two years, thus requiring accurate forecasting to plan production strategies and resource management. This research aims to forecast demand using the Fuzzy Mamdani method and the POM-QM application. Fuzzy Mamdani was chosen for its ability to handle decision-making with multiple criteria and balanced weights, while POM-QM was used to validate predictions through quantitative methods. Product sales data for the years 2022 and 2023 were analyzed to produce accurate forecasts. The methods used include Moving Average for forecasting and evaluation of the results using MAPE. The analysis results show that the Moving Average method with N = 2 produces a MAD value of 402.523 and a MAPE of 22.155%, while the results of Fuzzy Mamdani show that product demand in the next period tends to decrease. This research is expected to provide insight for CV Mamifood Sukses Abadi in planning a more efficient production strategy.

The reliability of sterilization equipment, such as autoclaves, is essential to ensure patient safety, infection control, and operational continuity in healthcare facilities. Damage or malfunction of autoclaves may disrupt sterilization processes and pose significant risks to medical services. This study aims to develop an expert system for autoclave damage detection using the fuzzy logic method to support faster and more accurate diagnostic decision-making. The proposed system applies fuzzy inference to evaluate the level of damage based on input symptoms provided by users. By handling uncertainty and varying symptom intensities, the fuzzy logic approach enables proportional assessment rather than rigid rule-based classification. The system was designed through knowledge acquisition from technical experts and implemented using fuzzy membership functions and inference rules to determine damage severity levels. Experimental testing was conducted to evaluate system performance and diagnostic accuracy. The results indicate that the expert system successfully generated diagnosis outputs for all tested scenarios, achieving functional diagnostic accuracy within the defined test cases. The system was also able to calculate a quantified damage severity value of 11.6235981% based on the given symptoms, demonstrating its capability to assess damage levels numerically and objectively. Furthermore, the developed system significantly reduces the time required for damage detection compared to manual diagnostic procedures. Automating the evaluation process, it assists electromedical technicians in identifying faults more efficiently and taking preventive or corrective actions promptly. Overall, the implementation of a fuzzy logic-based expert system provides an effective, accurate, and practical solution for improving autoclave maintenance management and supporting healthcare service reliability.

CV Wangun Mandiri is a manufacturing company that produces tapioca flour. In order to achieve maximum profit targets and smooth production activities, the company is faced with problems relating to the amount of tapioca flour products due to the uncertainty of its demand that tends to fluctuate and the imbalance of machine capacity. Therefore, it is required to plan the amount of production using the forecasting and fuzzy inference system approach as an effective method to determine the optimal production level. This research relies on the availability of datasets to determine the appropriate forecasting method and fuzzy method. The Fuzzy Mamdani method concludes that CV Wangun Mandiri can produce 82.9 tons to maximize existing demand and the capacity of its machines. 

Stock management is an important aspect in the operations of a grocery store. By knowing when to add stock, shop owners can optimize the availability of goods without excess stock. In this research, the fuzzy logic method is applied to determine stock procurement decisions based on sales data and remaining stock. The results of the research show that fuzzy logic can be used to assist in making stock procurement decisions with a fairly high level of accuracy.

The aim of this research is to give a new definition and study a new notion of fuzzy α̂g-topological R-module spaces using fuzzy α̂g-open sets. The concept of fuzzy α̂g-topological R-modules is introduced and study them to provide a mathematical basis. Traditional cautiousness for F bisected by α̂g-tautologies reigns furtive-space yield we assay different fuzzy α̂g-separation axioms such as  where  in the context of these spaces.  Also, we study fuzzy -separation axiom  in fuzzy  - Topological. R-Module space. The results indicate that throughout the  domain of a fuzzy topological R-module space  the following fuzzy separation axioms  and are valid.  Also, we also show that possessing fuzzy α̂g-open neighborhoods has further consequences to the structure and continuity of fuzzy topological spaces. The main conclusion of our research is that the mysterious α̂g topological R-unit spaces are a new and interesting area for further study. The terms of their operations in addition to providing important information about the interaction between fuzziness and topological properties that may be useful in many mathematical and applied branches.

Renewable energy systems, particularly those incorporating solar and wind power, are prone to stability issues due to the intermittent and fluctuating nature of these energy sources. This paper investigates several nonlinear control techniques—namely, adaptive control, sliding mode control, and fuzzy logic control—that are designed to improve stability in renewable energy systems. Through simulations, we demonstrate how these methods can effectively reduce fluctuations and maintain stable energy output, offering a robust approach to enhancing the reliability of renewable energy systems.

Fire is an event that often occurs due to human negligence. Losses from fire include damage to goods, business delays and can even cause loss of life. For early handling of fires, a "Fire Fighting Control Design Using MQ-2 Sensor and Fuzzy Logic Based 5 Channel Flame Sensor" has been created. This tool uses the MQ-2 sensor to detect gases related to fires, such as hydrocarbon gas. A 5 channel flame sensor is used to detect flames. The predetermined fuzzy logic rules will be used to control the fire extinguisher and implemented using the Arduino Atmega 2560 microcontroller as the brain of the system. Next, the microcontroller will send a control signal to the 12V DC pump output as a water spray system to deal with fires. The test results of this system show that the tool can detect early fire hotspots and respond well to fire extinguishing according to the fuzzy rule decisions carried out by testing the tool with 30 fire spots at different distances.

Achieving financial stability for the family is a goal that everyone has. The family is the most significant foundation for the growth of human life in Indonesia. The first and most important living environment where the personality that shapes a person's life is created is the family. The development of moral values, social justice, humanity, and religion is essentially a process decided by the family. The family is the first and main social structure that plays an important role in providing life values ​​to children who are growing and developing so that they can find purpose in their life journey. The classification of family welfare according to population data owned by the village government is the aim of this study. Based on the results of the study, fuzzy logic and the Tahani model can be used to process population data according to the level of family welfare, resulting in output in the form of family classifications such as prosperous, poor, and underprivileged families. To assess the effectiveness of incorporating fuzzy logic into the program being developed, the fuzzyTECH application is also used to test the program subdistrict.    

In this article, the starting condition was defined using a fuzzy initial value problem (IVP). Additionally, we discussed various methods for solving fuzzy differential equations, including the modified two-step Simpson method and Runge-Kutta of orders (two, three, four, five, and six). For each method, we provided a numerical example and the known convergence rates of the solutions. Then we discussed the comparison of the solutions of all methods, using computer software to offer rough solutions for the Runge Kutta method. And take some application solve by Runge-Kutta in physics and medical

Gas Sulfur adalah salah satu polutan berbahaya bagi manusia. Akibat utama polutan (SO2) terhadap manusia adalah terjadinya iritasi pada sistem pernafasan. Terutama kesehatan bagi usia lanjut dan penderita yang mengalami penyakit kronis pada sistem pernafasan dan kardiovaskular yang sangat sensitif jika kontak dengan (SO2). Sehingga pada penelitian ini perlu adanya sebuah rancang sistem monitoring kadar gas sulfur dioksida (SO2), suhu dan kelembaban pada ruangan. Sistem monitoring ini menggunakan sensor MQ-136 sebagai pendeteksi kadar gas sulfur dioksida (SO2) dengan satuan ppm dan sensor DHT11 sebagai pendeteksi suhu dan kelembapan pada ruangan. Hasil pembacaan kedua sensor tersebut akan diproses melalui Modul Wifi ESP32 dengan mempunyai output Aplikasi BLYNK dan Google Spreadsheet. Sementara output Exhaust Fan menyala sesuai dengan ketentuan Fuzzy Logic Mamdani.

Home is one of the primary needs of society. Various considerations of a person in buying a house, including considerations in terms of accessibility, environmental safety, road infrastructure and drainage, price, size and layout, building structure and model, availability of internet connection and signal layout, building structure and model, availability of internet connection and cell phone signal, availability of water and electricity, legal availability of water and electricity, legality, distance to workplace, and public facilities.public facilities. The fuzzy method is able to be used to classify the set of membership criteria and the SMART method can be used to rank the value of the criteria used criteria used. Calculations that have been carried out starts from using a fuzzy method that is useful for finding the set of membership criteria, followed by calculating the membership set of criteria, followed by calculating the matrix and ranking with the SMART method. ranking with the SMART method. Ranking with the highest value is house 2 with a value of 87.16 followed by house 3 with a value of 85.87 followed by house 1 with a value of 84.92 and the last house 4 with a value of 72.13

Determining the provision of bonuses or rewards to employees plays a crucial role in maintaining the quality and motivation of employees. One effort that can be made to establish a bonus policy is by implementing the fuzzy Mamdani method as a systematic approach in determining employee bonuses, particularly at PT. ABC. By utilizing the fuzzy Mamdani method to process subjectivity in evaluations, it generates membership levels that allow for a more contextual employee assessment. Through the analysis of data involving various performance variables and bonus criteria, this research aims to present a fuzzy Mamdani system model that can support accurate and adaptive decision-making in determining employee bonuses. The results of this research and the evaluation of this model are expected to contribute significantly to the development of more effective bonus policies in the workplace of PT.

LP is one of the pharmaceutical companies located in Serang, Banten. The production of the company is tablets, capsules, and syrup. Problems that occur at PT. LP is a product defect that occurs in capsule filling, especially in capsule A. The purpose of this study is to determine the defective products that occur in capsule A and to find out the proposed improvements that will be made to reduce product defects in capsule A. The research methods used are Statistical Process Control (SPC)  and Fuzzy Failure Mode and Effect Analysis (F-FMEA). The population and samples used were defective capsule A during the production process from March 2022 to May 2023, with sampling techniques through production data, observation and interviews. And the results of research using a check sheet show that the percentage of defects reaches 6%, based on the pareto chart, the priority of improvement that needs to be done is for the dominant type of defect, namely  the dented capsule reject reaches 90%, and on the control chart there are still control points that are outside the UCL and LCL. FMEA calculations, the RPN value of the capsule is dented on the head of the capsule or capsule body reaches 384, and the FRPN value is 6.76.    

The apple cider vinegar fermentation process requires careful monitoring and control of variables such as pH, alcohol content, and amount of acetic acid.  This research adopts Fuzzy Logic Control by utilizing the MQTT communication protocol, pH, alcohol and water pump sensors, as well as solenoid valves and DC motors as actuators.  This Internet of Things (IoT) based solution provides real-time monitoring information on the fermentation process.  The results showed that the test system succeeded in maintaining a stable pH of around 3.9-4.0 during the initial stages of fermentation, while industrial data showed greater variations.  Alcohol content increased consistently in the test system, in contrast to the spike on day 7 in industry data.  At the formulation stage, the pH dropped to 3.68 in the test system, while the industry maintained 3.70.  At medium and slow mixing stages, the test system showed a significant decrease in pH and a consistent increase in alcohol.  At the harvest stage, the pH was lower in the test system compared to industrial, with slightly higher alcohol content.  Test results show that the implementation of this system can reduce the fermentation process time by up to 2 days faster compared to conventional methods.  This conclusion shows that IoT-based systems are able to provide better control and monitoring than conventional systems, so they have great potential for wider adoption in the apple vinegar fermentation industry to increase production effectiveness.