Journal of Applied Science, Technology & Humanities
Journal of Applied Science, Technology & Humanities is published by Batrisya Education. Published five times a year, in January, March, June, September, November and already have a registration number ISSN 3032-5765, DOI: https://doi.org/10.62535/jasth. Journal of Applied Science, Technology & Humanities is an academic, open access, and peer-reviewed journal that focuses on critical studies of Science, Technology & Humanities. It covers areas like science, technology, education, psychology, health & nutrition, agriculture, ecology & environment, history, sociology, philosophy, economics, political and quantitative studies. Science, Technology and Humanities promotes interdisciplinary perspectives drawing upon a number of "hard core" science disciplines. Journal of Applied Science, Technology & Humanities is an national journal devoted to the study of science and technology in humanities context. It focuses on the way in which advances in science and technology influence society. It is a peer-reviewed journal that takes an interdisciplinary perspective, encouraging analyses whose approaches are drawn from a variety of disciplines such as science, technology, education, psychology, health & nutrition, agriculture, ecology & environment, history, sociology, philosophy, economics, political and quantitative studies. The journal consciously endeavors to combine scholarly perspectives relevant to academic research and policy issues relating to development. Besides research articles the journal encourages research-based country reports, commentaries and book reviews.
Articles
122 Documents
<![CDATA[IoT-Based Water pH Monitoring and Control System for Ornamental Fish Using Fuzzy Logic Method ]]>
<![CDATA[Rizki Maariz Senjaya Senjaya]]>;
<![CDATA[Iqbaal Maulana Dwiputera Dwiputera]]>;
<![CDATA[Muhammad Faturrahman]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 2 (2026): March 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/88020163
<![CDATA[Water quality, particularly pH, temperature, and turbidity parameters, plays an important role in maintaining the health of ornamental fish in aquariums. Fluctuations in these parameters can cause physiological stress and even death in fish if not properly controlled. This study aims to design an Internet of Things (IoT)-based water quality monitoring and control system using the Mamdani type Fuzzy Inference System (FIS) method. The system utilizes pH, temperature, and turbidity sensors connected to an ESP32 microcontroller to acquire data and transmit it in real-time to a cloud-based platform. Sensor values are processed through fuzzification, inference using the MIN operator and MAX aggregation, then defuzzification using the centroid method to produce decisions on fish conditions in the categories of healthy, sick, or dead. Simulation results using MATLAB Fuzzy Logic Toolbox show that the system is capable of providing a more stable non-linear response compared to conventional threshold methods. The integration of IoT and fuzzy logic enables more adaptive, proportional, and effective control in maintaining water quality within the optimal range for ornamental fish]]>
<![CDATA[Mamdani Fuzzy Control Design for IoT-Based Exhaust Fan Automation ]]>
<![CDATA[Irfan Rifqy Widya Syahbani]]>;
<![CDATA[Fadila Azahra]]>;
<![CDATA[M. Qyblat Ilmy Mahdi]]>;
<![CDATA[Daffa Ardyana Eka Putra]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 2 (2026): March 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/ph1ekf12
<![CDATA[This study presents a simulation-based analysis of an automatic exhaust fan control system using the Mamdani Fuzzy Inference System (FIS) integrated within an Internet of Things (IoT) framework. Poor indoor air quality, along with uncontrolled temperature and humidity levels in enclosed environments, significantly affects human comfort and equipment reliability. The proposed system utilizes temperature and humidity data as input variables, which are processed through a Mamdani FIS to generate proportional control signals for exhaust fan speed regulation. Triangular and trapezoidal membership functions were designed to model environmental conditions, while the Center of Area (COA) method was applied for defuzzification to ensure smooth output transitions. The system was evaluated using MATLAB Fuzzy Logic Toolbox, and the surface analysis demonstrates stable and continuous control behavior across varying environmental conditions. The results indicate that the Mamdani fuzzy approach provides smooth, adaptive, and energy-efficient control compared to conventional threshold-based systems. Furthermore, the integration of IoT enables real-time monitoring and enhances operational flexibility. These findings confirm that Mamdani FIS is a suitable method for intelligent exhaust fan automation. ]]>
<![CDATA[Implementation of Mamdani Fuzzy Logic in Fire Early Warning Based on Gas Leaks ]]>
<![CDATA[Inas Samara Taqia]]>;
<![CDATA[Muhammad Rafi Riza Pratama]]>;
<![CDATA[Muhammmad Eka Fauzan]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 3 (2026): June 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/3wta8665
<![CDATA[Gas leaks represent one of the most critical triggers of residential and industrial fire accidents, particularly in environments reliant on Liquefied Petroleum Gas (LPG). Conventional threshold-based detection systems exhibit fundamental limitations in interpreting the gradual and simultaneous dynamics of multiple hazardous parameters, rendering them prone to delayed responses or false alarms. This study proposes an intelligent early warning system for fire detection based on gas leakage, employing the Mamdani Fuzzy Inference System (FIS) implemented on an Arduino Uno microcontroller. The system integrates three environmental input variables Gas Concentration (MQ-2 sensor), Flame Distance (IR flame sensor), and Ambient Temperature (DHT22 sensor) to determine the proportional speed output of a DC exhaust fan via Pulse Width Modulation (PWM) control. A rule base of 27 IF-THEN rules governs the inference process. The system was validated through MATLAB Fuzzy Logic Toolbox simulation and direct hardware implementation, yielding an average error rate of 0.22% between simulated, hardware computation, and actual outputs. The results demonstrate that the proposed multi-parameter Mamdani fuzzy system provides a significantly more adaptive and precise hazard assessment compared to conventional single-threshold approaches, offering a robust foundation for smart safety system deployment.]]>
<![CDATA[Implementation of the Mamdani Fuzzy Method for Gourami Aquaculture Water Quality Control Using Pump Systems ]]>
<![CDATA[Senthelee Vannessa Lai]]>;
<![CDATA[Alicia Maharani]]>;
<![CDATA[Naufa Hilmatuzzahra]]>;
<![CDATA[Luthfi Alviani]]>;
<![CDATA[Michael Lim Sony Wijaya]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 3 (2026): June 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/9qhc5h24
<![CDATA[Water quality stability is a critical factor in the cultivation of gourami fish (Osphronemus gouramy), as this species is highly sensitive to environmental changes. This study aims to implement the Mamdani fuzzy logic method in a pump-based water quality control system. The system is designed to analyze three primary parameters: temperature, ammonia concentration, and pH. Data acquired from sensors are processed by an ESP32 microcontroller through the stages of fuzzification, rule evaluation, implication, aggregation, and centroid-based defuzzification. A total of 48 fuzzy rules are formulated to adaptively determine the pump operating duration, allowing the system to adjust according to actual pond conditions. The experimental results show that at a temperature of 28.7 °C, an ammonia concentration of 0.28 ppm, and a pH value of 8.15—consistent with the simulation—the system produces a defuzzification output of 60 seconds, representing the pump operating duration. These findings confirm that the proposed system can generate flexible control decisions by considering the combined influence of multiple environmental parameters rather than relying on fixed threshold values. The implementation of the Mamdani fuzzy logic method improves system responsiveness in maintaining water quality stability in gourami aquaculture.]]>
<![CDATA[Application of Fuzzy Logic for Automatic Air Circulation Control System in Smoking Rooms Based on IoT ]]>
<![CDATA[Mikhail Hibrizi]]>;
<![CDATA[Ariel Pasha Ramaditya]]>;
<![CDATA[Muhammad Dzaky Azzshahir]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 2 (2026): March 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/r0q7c653
<![CDATA[Indoor air quality (IAQ) in smoking rooms presents significant health risks due to the accumulation of pollutants such as carbon monoxide (CO) and cigarette smoke. Conventional ventilation systems typically operate using constant speed or threshold-based ON/OFF control, which cannot provide adaptive responses to dynamic pollutant variations. This study proposes an Internet of Things (IoT)–based automatic air circulation control system utilizing a Mamdani Fuzzy Inference System (FIS) to regulate exhaust fan speed proportionally in real time. The system integrates MQ-2 and MQ-7 sensors with an ESP32 microcontroller for pollutant detection and processing. The fuzzy control mechanism consists of fuzzification, MIN implication, MAX aggregation, and Centroid of Area (CoA) defuzzification to generate a crisp output representing fan speed. The output is converted into an 8-bit PWM signal for proportional actuator control, while environmental data are transmitted via MQTT for real-time monitoring. Experimental and simulation results demonstrate that the proposed fuzzy-based controller provides smoother and more adaptive ventilation performance compared to conventional ON/OFF control, particularly under moderate pollution conditions. The closed-loop architecture improves responsiveness and operational efficiency for intelligent smoking room ventilation management.]]>
<![CDATA[DESIGN OF FUZZY MAMDANI IN THE SOIL FERTILITY MONITORING SYSTEM FOR CORN CROPS ]]>
<![CDATA[Ilham Bonardo Marpaung]]>;
<![CDATA[Hafiz Tiftazani]]>;
<![CDATA[Muhammad Rifki Munawar]]>;
<![CDATA[Rafie Hafizhsatryo]]>;
<![CDATA[Ariel Mughnika Beers]]>;
<![CDATA[Nur Kholis Nafis]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 2 (2026): March 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/vw7vc913
<![CDATA[Soil fertility is an important factor that affects the growth and productivity of corn plants. Soil fertility assessments that are still carried out manually often produce different interpretations because they are influenced by the subjectivity of the observer. This study aims to design a soil fertility monitoring system using the Mamdani fuzzy logic method implemented through the MATLAB Fuzzy Logic Toolbox. The system uses three input parameters, namely soil pH, soil moisture, and soil temperature, with the output being the level of soil fertility. The data processing stages include fuzzification, application of IF–THEN-based rules, aggregation, and defuzzification using the centroid method to produce a definite output value. Simulation results show that the system is able to classify soil conditions into infertile, moderately fertile, and fertile categories consistently. The developed system can help users understand soil conditions more objectively and support decision-making in corn field management. Thus, the Mamdani fuzzy method is effective in processing uncertain environmental parameters into measurable information]]>
<![CDATA[Application of Fuzzy Logic System for Coffee Bean Quality Detection ]]>
<![CDATA[Baracahya Panata Cendikia Rahayu]]>;
<![CDATA[Ahmad Farrell Raafii Alaiyya Al-Attas]]>;
<![CDATA[Imam Yanif]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 2 (2026): March 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/myb58j95
<![CDATA[Manual assessment of coffee bean quality is often subject to inconsistency and evaluator bias, potentially leading to economic losses for farmers and industry stakeholders. This study proposes an objective simulation model for coffee bean quality evaluation using the Mamdani Fuzzy Logic method implemented in MATLAB Fuzzy Logic Toolbox. A quantitative descriptive approach was adopted, utilizing secondary data synthesized from validated experimental literature. The model incorporates three physical input variables: kadar air (%), color intensity (lux), and bean size (mm), with a single output variable representing the quality score. The system process includes fuzzification using trapezoidal and triangular membership functions, evaluation of 27 IF–THEN rules, aggregation through the MAX operator, and defuzzification using the Centroid method. Simulation results demonstrate that the proposed system effectively classifies coffee bean quality into three categories: Premium, Sedang, and Rendah. Under optimal conditions (11.5% moisture content, bright color, and large bean size), the defuzzified score consistently exceeds 70 (Grade 1), aligning with industry quality standards. The findings confirm that fuzzy logic provides a transparent and reliable decision-support framework capable of transforming ambiguous physical measurements into measurable quality indices for coffee standardization.]]>
<![CDATA[Implementation of the Mamdani Fuzzy Algorithm for Monitoring Server Room Conditions ]]>
<![CDATA[Bramantyo Wicaksono]]>;
<![CDATA[Ridho Albab Mufarid]]>;
<![CDATA[Ilham Alfianda Fatwa]]>;
<![CDATA[Radyanka Irza Pramono]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 3 (2026): June 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/wsw9d271
<![CDATA[This study presents the design and simulation of a server room feasibility evaluation system using the Mamdani Fuzzy Logic approach. The system evaluates three environmental parameters: temperature, relative humidity, and airborne particle concentration. A total of 27 IF–THEN rules were developed based on operational considerations and international environmental recommendations. Triangular membership functions were applied to represent normal operating conditions to enhance sensitivity, while trapezoidal functions were used for extreme conditions to ensure response stability under sensor uncertainty. The inference process employed the minimum operator for rule activation, maximum aggregation, and centroid defuzzification to produce a quantitative feasibility score within a 0–100 scale. Simulation results demonstrate that the fuzzy approach provides smoother and more adaptive decision boundaries compared to crisp logic, enabling gradual evaluation of transitional environmental conditions. A case study simulation confirmed that variations in humidity and particulate levels significantly influence the final feasibility score, even when temperature remains within the recommended range. Furthermore, rescaling the particle concentration domain (0–200 µg/m³) improved system sensitivity for indoor pollutant monitoring. The proposed system proves effective as a decision-support tool for intelligent server room environmental monitoring.]]>
<![CDATA[DESIGN AND IMPLEMENTATION OF AN ARDUINO BASED AUTOMATED NUTRIENT CONTROL SYSTEM FOR HYDROPONIC TOMATO CULTIVATION USING MAMDANI FUZZY LOGIC ]]>
<![CDATA[Bagus Priwendy Simangunsong]]>;
<![CDATA[Althof Zufar Musyaffa]]>;
<![CDATA[Muhammad Faris Al Fajri]]>;
<![CDATA[Gilang Ramadhan]]>;
<![CDATA[M Aqil Fazli Y]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 3 (2026): June 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/b8zsjx97
<![CDATA[Achieving optimal growth and yield in hydroponic tomato farming demands strict control over nutrient composition and environmental factors. To support efficient physiological functions such as photosynthesis, transpiration, and nutrient uptake key parameters including nutrient solution pH, ambient temperature, and water levels must remain within specific thresholds. Relying on manual control frequently leads to delayed responses against environmental shifts, causing inconsistent plant performance. Consequently, this research focuses on developing an automated nutrient control system tailored for hydroponic tomatoes, leveraging Mamdani Fuzzy Logic embedded in an Arduino microcontroller. Input data from pH, temperature, water level, and light intensity sensors undergoes fuzzification, rule-based inference, and centroid defuzzification. Based on these processes, the system generates control signals to adjust fan speeds and solenoid valve durations, ensuring environmental stability. Experimental findings indicate that the proposed system adapts effectively to parameter variations, offering smoother control than traditional threshold-based methods. Ultimately, this Mamdani fuzzy-based approach significantly stabilizes the hydroponic environment while minimizing the need for manual intervention.]]>
<![CDATA[Fuzzy Logic-Based Monitoring and Control of Water pH Quality ]]>
<![CDATA[Genta Fallah Munggaran Sonagar]]>;
<![CDATA[Fauzi Luqman Noor Ikhwan]]>;
<![CDATA[Muhammad Rifqi Annaufal]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 3 (2026): June 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/nx1r3818
<![CDATA[Water quality monitoring is essential to keep water environmental safety and healthy, espescially when keeping pH levels stable within acceptable standards. Conventional monitoring system usually limited to periodic measurement and lack flexible control mechanism to handle real-time fluctuations. This research based on implementation of a mamdani fuzzy logic-baesd system for continous pH monitoring and autmatic control of water pH quality. With system that integrated to pH sensor with microcontroller to process input data and apply fuzzification, rule assesment, aggregation, and centroid defuzzification. The fuzzy setup classifies pH into acidic, neutral, or basic states and determines appropiate corrective actions acordingly. Experimental testing was conducted under varying pH conditions to evaluate system responsiveness and stabilization performance. This fuzzy method enable adaptable choices, minimizes disruptions from rigid thresholds, and reliably holds pH in target zone.]]>
