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[Application of Fuzzy Logic to Detect TSS and DO Contamination in Aquaculture ]]>
<![CDATA[wefi vianita]]>;
<![CDATA[Daffa Zulqisthi]]>;
<![CDATA[Muhammad Faiz Assar]]>;
<![CDATA[Lulu Susan Hanifah]]>;
<![CDATA[Intan Nazwa Oktarani]]>;
<![CDATA[Fandhika Al Fatdri Susilarso]]>;
<![CDATA[Mahesa Rafi Zaka Fatahila]]>;
<![CDATA[Isti Kentjana]]>;
<![CDATA[Ranti Ayu Rahmawati]]>;
<![CDATA[Muhammad Naufal Hazimulfikri]]>;
<![CDATA[Naufal Auzan Ramadhan]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 5 (2025): November 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/f4tdgd70
<![CDATA[The quality of water in aquaculture systems plays a critical role in maintaining the health andproductivity of aquatic organisms. Two key parameters affecting water quality are DissolvedOxygen (DO) and Total Suspended Solids (TSS), both of which fluctuate and can negativelyimpact fish survival rates. This study aims to design and evaluate a fuzzy logic-basedclassification system using the Mamdani method to assess water quality conditions based on DOand TSS values. The research employed a qualitative approach supported by simulation usingMATLAB software. The input variables were DO and TSS, while the output was theclassification of water quality into two categories: good and poor. The fuzzy inference systemwas constructed using membership functions and rule-based logic. The results showed that thesystem was capable of generating accurate and adaptive outputs, with a sample input of DO 9.04mg/L and TSS 235 mg/L producing an output value of 0.742, indicating good water quality.These findings demonstrate the effectiveness of the system in supporting water monitoring inaquaculture operations.]]>
<![CDATA[IMPLEMENTATION OF FUZZY LOGIC ON SIMULATION OF PH, TEMPERATURE, AND DISSOLVED OXYGEN MONITORING SYSTEM FOR DISCUS FISH ]]>
<![CDATA[Farhan Adha]]>;
<![CDATA[Yassar Ariq Pradian]]>;
<![CDATA[Muhammad Faiz Assariy]]>;
<![CDATA[Hafiz Kurniawan]]>;
<![CDATA[Fahmi Fadillah]]>;
<![CDATA[Dimas Muhammad Fathur Rifki]]>;
<![CDATA[Kevin Soerhensen]]>;
<![CDATA[Baihaqi Al Faatih]]>;
<![CDATA[Ridwan Kuasa Samudra Singajaya]]>;
<![CDATA[Abu Dzar Al-Ghifari]]>;
<![CDATA[Fauziah Prima Aulia]]>;
<![CDATA[Rachel Delamaya Fefriani]]>;
<![CDATA[Shabrina Kesya Azizah]]>;
<![CDATA[Larisa Syafa Adisti]]>;
<![CDATA[Muhammad Rafa Najwan]]>;
<![CDATA[Daffa Zulqisthi]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 4 (2025): September 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/fzqysf66
<![CDATA[Discus fish (Symphysodon spp.) are ornamental fish that require special attention to water quality, including pH, temperature, and dissolved oxygen (DO). This research aims to develop a fuzzy logic-based water quality monitoring system to accurately evaluate these parameters. Quantitative methods were used with data collection through literature review and analysis using Matlab. The fuzzification process is applied to convert numerical data into linguistic values that can be processed by the fuzzy system. Results showed ideal temperature ranged from 27-32°C, optimal pH between 4.0-8.0, and good DO levels between 4.0-6.5 mg/L. The developed fuzzy logic system produced ea water quality assessment with a value of 6.61, indicating a fair quality. With high accuracy and average error less than 5%, the system is effective in decision-making for discus fish rearing. The integration of fuzzy logic technology strengthens the continuous monitoring of water quality. This research shows that a fuzzy logic-based approach can improve water quality management and support discus fish welfare.]]>
<![CDATA[Automatic Milkfish Feeding System Based on Fuzzy Logic on Microcontroller ]]>
<![CDATA[Fadhiel Fadhiel Naufal Huda]]>;
<![CDATA[Silvester Ariski Tobi]]>;
<![CDATA[Fadhiel Naufal Huda]]>;
<![CDATA[Khoirul Kodri Nasution]]>;
<![CDATA[Muhamad Ariq Maulana]]>;
<![CDATA[Hanatasya Ramadhan]]>;
<![CDATA[Ahmad Fahrezzi]]>;
<![CDATA[Nailah Azzahra Cinthari]]>;
<![CDATA[Willa Wulandari]]>;
<![CDATA[Bunga Ligar Balebat]]>;
<![CDATA[Muhammad Rayhan Kurniawan]]>;
<![CDATA[Stilo Farrel Ticoalu]]>;
<![CDATA[Muhammad Faiz Assariy]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 4 (2025): September 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/fmwq6f97
<![CDATA[Dear Editorial Team, I hope this message finds you well. Please find attached our manuscript entitled "Automatic Milkfish Feeding System Based on Fuzzy Logic on Microcontroller", which we would like to submit for possible publication in Journal of Applied Science, Technology & Humanities. This paper presents our research on automatic feeding system was designed using fuzzy logic and a microcontroller to adaptively adjust milkfish feed based on water temperature, with the aim of improving feed efficiency and supporting sustainable aquaculture. We believe that our findings could contribute significantly to the field of aquaculture management. The manuscript has not been published elsewhere and is not under consideration by any other journal. Please let us know if any additional information is required. We look forward to your feedback. Thank you for your time and consideration. Best regards,Fadhiel Naufal HudaIPB Universityfadhielnaufal@apps.ipc.ac.id]]>
<![CDATA[Application of Mamdani Fuzzy Logic in Monitoring Dissolved Oxygen, pH, and Temperature in Koi Cyprinus rubrofuscus Raising Ponds ]]>
<![CDATA[Widya Puspita Hapsari]]>;
<![CDATA[Muhammad Faiz Assariy]]>;
<![CDATA[Daffa Zulqitsi]]>;
<![CDATA[Zuliandra Pratama]]>;
<![CDATA[Alwan Maulana]]>;
<![CDATA[Muhammad Sakha Alfaizi]]>;
<![CDATA[Rizki Ismaulana Ar Rasyid]]>;
<![CDATA[Adhietya Try Anggara]]>;
<![CDATA[M Febriyansah]]>;
<![CDATA[Khansa Asrilia Suganda]]>;
<![CDATA[Utari Oktaviani]]>;
<![CDATA[Destia Rahma Nurhaliza]]>;
<![CDATA[Rakha Arya Gautama]]>;
<![CDATA[Elva Vauziyah]]>;
<![CDATA[Naufal Auzan Ramadhan]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 4 (2025): September 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/8j9q1d36
<![CDATA[Water quality is very important for the success of ornamental fish rearing, especially in raising koi fish Cyprinus rubrofuscus. This research develops a water quality monitoring system using the Mamdani fuzzy logic method based on three main parameters, namely temperature, pH, and dissolved oxygen (DO). The system was designed to handle the uncertainty and indecisiveness often encountered in water quality assessment, particularly in aquaculture environments. Temperature parameters are classified into cold, normal, and hot categories; pH into acidic, neutral, and alkaline categories; and DO into low, medium, and high categories. Simulation and implementation of the fuzzy inference system were conducted using MATLAB software. Through the process of fuzzification, rule-based inference, and defuzzification, the system successfully predicts the water quality status from bad, normal and good categories. The system is proven to be effective in evaluating water quality status and has the potential to support smarter and more adaptive management of koi fish farming environments. ]]>
<![CDATA[Fuzzy Logic Model for Evaluating Fresh Milk Quality Based on Protein to Fat Ratio ]]>
<![CDATA[Mula Gabe Ompusunggu]]>;
<![CDATA[Gabby Livia Satria Gani, Gusti Ayu Putu Shintya Saraswati, Helmayanti Pratikasari, Mohamad Jalal Fah]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 2 (2026): March 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/9912q034
<![CDATA[The assessment of fresh milk quality plays a crucial role in ensuring food safety and supporting the efficiency of dairy processing. This study aims to develop a fuzzy logic model to evaluate the acceptability of fresh milk based on the protein-to-fat ratio in accordance with the Indonesian National Standard (SNI 3141.1:2011). A qualitative descriptive method was applied using MATLAB software to simulate fuzzy inference with protein and fat contents as input variables and milk quality as the output. Triangular and trapezoidal membership functions were utilized, with the Mamdani inference and centroid defuzzification methods used to obtain precise output values. The results indicate that samples with high and balanced protein and fat contents yield superior milk quality, whereas low levels of both result in poor classification. The fuzzy rule system effectively accommodates natural variations in milk composition, offering a more adaptive and accurate assessment compared to conventional threshold-based evaluations. This model demonstrates strong potential as a decision-support tool for quality control in the dairy industry and contributes to improving the consistency and scientific basis of national milk quality assurance systems.]]>
<![CDATA[Fuzzy Logic Design for Mocaf and Green Bean Flour Substitution Effect on Noodle Protein Content ]]>
<![CDATA[Alysha Revalina Nugraha]]>;
<![CDATA[Adinda Dwi Wahyuni]]>;
<![CDATA[Ananti Nur Mala]]>;
<![CDATA[Arifi Keisya Azahra]]>;
<![CDATA[Aurelia Salsabila]]>;
<![CDATA[Daffa Athallah Umbara]]>;
<![CDATA[Naila Nabiha Fidzri]]>;
<![CDATA[Soelthan Ramzy Kastio]]>;
<![CDATA[Mrr. Lukie Trianawati]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Roma Juliana Arios]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 5 (2025): November 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/ynhzea48
<![CDATA[Wet noodles are widely consumed in Indonesia but have low protein content because they are made from wheat flour. Their nutritional value can be improved by substituting part of the flour with local ingredients such as protein-rich green bean flour and mocaf, which enhances texture. Previous studies showed that green bean flour increases protein, while mocaf has little effect. This study models the relationship between green bean flour and mocaf composition on protein content using Mamdani fuzzy logic, which effectively handles uncertain and non-linear data. Secondary data from three treatments MB2 (50:10), MB4 (30:30), and MB6 (10:50) were used. Two input variables (percentages of mocaf and green bean flour) and one output variable (protein content) were divided into three categories: low, medium, and high. The fuzzy process included fuzzification, rule formulation, inference using the min–max operator, and centroid defuzzification. Results showed that increasing green bean flour raised protein content, while excessive mocaf reduced it. The Mamdani method effectively modeled the relationship between ingredient composition and protein levels in wet noodles.]]>
<![CDATA[Fuzzy Logic System Application for Banana Shelf Life Prediction with Sensor-Based Microclimate ]]>
<![CDATA[Aryo Sumaryanto]]>;
<![CDATA[Roma Juliana Arios]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Mrr Lukie Trianawati]]>;
<![CDATA[Zalfa Cantika]]>;
<![CDATA[Tiara Arelya Priyanto]]>;
<![CDATA[tangkas Patiasmara]]>;
<![CDATA[Nashwa Zahrania Adiputri]]>;
<![CDATA[Khaerun Nisa]]>;
<![CDATA[Kezia Joy Audreyna]]>;
<![CDATA[Fatia Syafana]]>;
<![CDATA[Wulidah Tamsil Barokah]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 1 (2026): January 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/8dap4r21
<![CDATA[Bananas are climacteric fruits with high postharvest loss rates due to rapid ripening and spoilage under uncontrolled microclimate conditions. This study aims to develop a fuzzy logic-based system for predicting banana shelf life using real-time sensor data and a web dashboard interface. The research employed a quantitative descriptive method using the Mamdani fuzzy inference system in MATLAB, with input variables including temperature (°C), relative humidity (%), and ethylene concentration (µL/L). The output variable was shelf life, categorized as Fresh, Starting to Spoil, or Spoiled. Simulation results showed that optimal conditions (temperature 18°C, humidity 85%, ethylene 1 µL/L) yielded a defuzzification value of 0.853, indicating high freshness. Conversely, suboptimal conditions (temperature 20°C, humidity 70%, ethylene 0.1 µL/L) produced a value of 0.493, reflecting moderate freshness. The fuzzy logic system effectively modeled nonlinear relationships and uncertainty in sensor data, enabling adaptive shelf life prediction. These findings confirm that integrating fuzzy logic with microclimate sensors and dashboard visualization enhances decision-making in fruit storage management]]>
<![CDATA[Application of Fuzzy Logic to Determine the Condition of Candy Packaging Seals Based on Temperature, Pressure, and Heat-Sealing Duration ]]>
<![CDATA[Christabel Jayastu Swadana Suhardi]]>;
<![CDATA[Roma Juliana Arios]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Mrr. Lukie Trianawati]]>;
<![CDATA[Sistya Yurizka Zein]]>;
<![CDATA[Shadylla Al-Mahra Granada]]>;
<![CDATA[Resti Herwiyati]]>;
<![CDATA[Muhammad Ihsan Sulaiman]]>;
<![CDATA[Fauzan Hilmi]]>;
<![CDATA[Annisa Triananda Dias Putri]]>;
<![CDATA[Adit Napaulana]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>
<![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/pb5qfz87
<![CDATA[The sealing process in candy packaging is crucial for maintaining product safety, quality, and stability. However, variations in temperature, pressure, and sealing time often cause inconsistencies in seal strength and defects when using conventional systems. This study applies the Mamdani fuzzy logic method to optimize temperature, pressure, and sealing duration for consistent seal quality. The input variables are Temperature, Pressure, and Duration, while the output variable, Seal_Conditions, includes “Less tight,” “Optimal,” and “Melt.” The fuzzy inference system consists of fuzzification, rule evaluation, and defuzzification using the centroid method. Nine fuzzy rules were developed to model the sealing behavior based on parameter interactions. The defuzzification result yielded a crisp value of 4.73, indicating a sufficiently tight seal without melting the packaging material. These findings demonstrate that the Mamdani fuzzy logic method effectively manages nonlinear variations in the sealing process, ensuring consistent product quality and minimizing defects and material waste. Therefore, fuzzy logic offers an adaptive and reliable control approach for optimizing the heat-sealing process in candy packaging.]]>
<![CDATA[Fuzzy Logic-Based Model for Predicting Quality of Fresh Tomatoes ]]>
<![CDATA[Balqis Veiruza Syawalanda Putri Sutrisno]]>;
<![CDATA[Roma Juliana Arios]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Daffa Gunadharma]]>;
<![CDATA[Haya Faizah]]>;
<![CDATA[Kayla Azzahra N]]>;
<![CDATA[Alysha Najma Syadzwina]]>;
<![CDATA[Annisa Nurul Zakiyah]]>;
<![CDATA[Zulva Khoirunnisa Rofifah]]>;
<![CDATA[Fatih Shaqliyah]]>;
<![CDATA[Mrr. Lukie Trianawati]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 5 (2025): November 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/00zv5x32
<![CDATA[The quality of tomatoes has become very important since their widespread use and diverse functions, both for fresh consumption and as raw materials for processed products. Conventional assessment of tomato freshness is still based on visual inspection and laboratory tests, which are inefficient. Meanwhile, the use of technology and artificial intelligence (AI), such as fuzzy logic, has been applied to evaluate food quality efficiently, accurately, and non-destructively. Thus, this study aims to design a fuzzy logic-based tomato freshness assessment system with quality-determining variables, which are hardness and color. The fuzzy logic-based tomato quality assessment system involves four main stages, namely fuzzification, rule base formulation, fuzzy inference, and defuzzification. Fuzzy rules are also developed to describe the logical relationship between variables in the form of “if-then”. The application of the fuzzy method can improve the efficiency of tomato quality assessment activities by linking input variables (color and hardness) with outputs in the form of tomato quality levels. This system is similar to the human reasoning process, making it ideal for evaluating agricultural commodities. Therefore, the fuzzy model is an ideal method for determining the freshness quality of tomatoes, which requires a precision control system in diverse and uncertain conditions.]]>
<![CDATA[Optimizing Fresh Orange Juice Production at XYZ MSME Bogor Using Forecasting and Sugeno Fuzzy Logic ]]>
<![CDATA[Yusup Cahyadi]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Mrr Lukie Trianawati]]>;
<![CDATA[Najla Athaya]]>;
<![CDATA[Khaula Amanda]]>;
<![CDATA[Farhana Adinda Zuhro]]>;
<![CDATA[Dinar Lukmanudin]]>;
<![CDATA[Devi Suryani]]>;
<![CDATA[Christine Amara Tirza]]>;
<![CDATA[Azhara Paramita]]>;
<![CDATA[Roma Juliana Arios]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 5 (2025): November 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/ed1av543
<![CDATA[Determining the optimal daily production quantity is a major challenge for XYZ MSME, a small-scale fresh orange juice producer in Bogor, due to fluctuating demand and the perishable nature of its products. The purpose of this research is to forecast daily production using the Sugeno fuzzy logic method to minimize overproduction and underproduction. The study employs a Sugeno fuzzy inference system (FIS) with input variables including previous day sales and available raw materials. A set of fuzzy rules maps these inputs to recommended production quantities. The results show that the Sugeno FIS produces accurate and adaptive forecasts that closely match actual demand patterns, enabling XYZ MSME to adjust production efficiently. This method helps reduce raw material waste, optimize resource use, and improve overall production efficiency. The study concludes that applying the Sugeno fuzzy logic approach is effective for short-term production planning in MSMEs, particularly for perishable food products.]]>
