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[Analysis of Decision Making Using the Composite Performance Index Method in Improving Product Handling at UMKM Warung Nasi, Bogor City ]]>
<![CDATA[Sesar Husen Santosa]]>;
<![CDATA[Agung Prayudha Hidayat]]>;
<![CDATA[Heryudianto Vibowo]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 3 (2025): June 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/dw43jy09
<![CDATA[Competition for the MSME rice stall business in the city of Bogor is currently very high where business actors are trying to increase consumer loyalty. The problem currently occurring in MSME rice stalls in Bogor City is a lack of knowledge regarding proper handling of food products. This problem means that MSME players only have a limited market share. In this PKM activity, evaluation and implementation of priority improvements are carried out using the Composite Performance Index (CPI). The CPI method uses four alternative options, namely improving service, improving serving facilities, improving food processing methods and improving production layout. The results of determining repair priorities using the CPI method showed that the repair process must be carried out at serving facilities with a value of 106.09. The priority results of this improvement are improvements to the display cases, serving areas and consumer dining tables.]]>
<![CDATA[Implementation of Fuzzy Logic in Determining the Acceptance Status of Fresh Milk Based on pH and Density ]]>
<![CDATA[Ahmad Daffa Naufal Ziddani]]>;
<![CDATA[Fiqri Nurfadillah]]>;
<![CDATA[Muhammad Danang Mukti Darmawan]]>;
<![CDATA[Ester Angeline]]>;
<![CDATA[Nanda Octavia]]>;
<![CDATA[Syahla Aqilah]]>;
<![CDATA[Salsabila Arina Pramudita]]>;
<![CDATA[Wianda Aghnia Salsabila]]>;
<![CDATA[Febby Aurellya]]>;
<![CDATA[Novi Giotta Hutapea]]>;
<![CDATA[Asochia Naomi Sitohang]]>;
<![CDATA[Assadel Zhafif Alwaini]]>;
<![CDATA[Ayu Shakira Nur Riawan]]>;
<![CDATA[Aqila Asysyakur]]>;
<![CDATA[Difa Mukmilatul Kautsar]]>;
<![CDATA[Raisa Fasya]]>;
<![CDATA[Luluah Sabrina Putri]]>;
<![CDATA[Mrr Lukie Trianawati]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 1 No. 3 (2024): June 2024 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/xvycaa24
<![CDATA[Fuzzy logic, known as fuzzy set theory, has become widely used to deal with uncertainty in research data processing. Fuzzy logic methods are known for their ease of implementation in machine language environments and their effectiveness in combining machine language representations with humanlanguage with an emphasis on meaning or importance. Fuzzy logic maps input space to output space, and this concept is closely related to dealing with uncertainty in data. In applying fuzzy logic in this study, the variables pH and density of milk are considered inputs whose value ranges are divided into low, medium, and high categories. The result of the fuzzy system is the acceptability state of fresh milk. By applying this method using MATLAB software, the simulation results show that at a milk pH of 6.2 and a specific gravity of 1.0320, the acceptability state of fresh milk is 30. After the defuzzification process and manual calculation, the final result is 29.30~30. From these results, fuzzy logic provides high accuracy to support progressive decision-making. This allows the system to consider the complexity of milk quality criteria that cannot always be measured in a binary way (e.g., good or bad), resulting in more precise and accurate decisions.]]>
<![CDATA[Quackbot Automated Robot Duck Egg Collector Based on Artificial Intelligence (AI) and Internet of Things (IoT) ]]>
<![CDATA[Analiah Fahlevy Yusuf]]>;
<![CDATA[Muhammad Arif Bagus Dewanto]]>;
<![CDATA[Herlambang Nurasyid Ramadhan]]>;
<![CDATA[Dhiya Rizqi Bagus Wibowo]]>;
<![CDATA[Antonio Banggas Gregory Sinaga]]>;
<![CDATA[Anandito Daffa Wijayanto]]>;
<![CDATA[Afifah Rodhiyatun Nisa4]]>;
<![CDATA[Lathifunnisa Fathonah]]>;
<![CDATA[Gema Parasti Mindara]]>;
<![CDATA[Mohamad Fikih Amar Dani]]>
<![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/hsd3br02
<![CDATA[The development of robotics in various fields is advancing rapidly, especially in the current digital era. In the world of egg retrieval, there are specific procedures to prevent eggs from breaking during collection. Many farms still rely on manual egg retrieval, where workers collect eggs daily. However, there are concerns about dishonest workers who may steal eggs for personal gain, causing worry for farmers. To address this issue, an AI-based egg picker has been designed to act as a system controller and information manager. This system includes AI for egg detection and an IoT system for real-time monitoring, allowing farmers to track daily egg yields. The development of this automatic egg-picking robot involves several stages: data collection, data analysis, block diagrams, planning, needs analysis, device design, implementation, and maintenance. The tool utilizes AI YOLOv8 to detect eggs, which the robot then collects. Once the maximum capacity is reached, the robot returns to the base camp. This innovative approach not only improves efficiency and accuracy in egg collection but also ensures transparency and reduces the risk of theft, providing peace of mind for farmers and enhancing overall farm productivity.]]>
<![CDATA[Implementation of Fuzzy Logic in Management Decision Making Supply of Raw Materials for Pie Production in the Food Industry ]]>
<![CDATA[Alif Permata Gusti]]>;
<![CDATA[Muhammad Faiz Assariy]]>;
<![CDATA[Daffa Zulqisthi]]>;
<![CDATA[Lukie Trianawati]]>;
<![CDATA[Tyara Restiani]]>;
<![CDATA[Rinriani Hanifah]]>;
<![CDATA[Nasya Alivia Cahyaning Putri]]>;
<![CDATA[Muhammad Naufal Denasfi]]>;
<![CDATA[Dinda Anissa Rahmah]]>;
<![CDATA[Alief Riza Candra Dewi Afivah]]>;
<![CDATA[Chika Hayya Sabillah]]>
<![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/xnxxdt92
<![CDATA[Raw material inventory management is a critical factor in the food industry, influencing production efficiency and product quality. Unstable inventory levels can lead to significant challenges, including material spoilage, stock shortages, and quality degradation, ultimately impacting the ability to meet market demand. To address the complexities and uncertainties inherent in inventory management, this study explores the application of Fuzzy Sugeno inference systems. This method allows for the flexible processing of imprecise inventory data, generating accurate numerical outputs that can directly inform operational decision-making. By analyzing production data for pie crusts from April 2023 to May 2024, the study identified significant fluctuations in initial stock, production, and incoming stock levels. To capture the inherent uncertainty in these parameters, Fuzzy Sugeno was employed to categorize them into fuzzy sets. The implementation of the model in MATLAB yielded precise outputs that align with the specific needs of inventory management in the food industry. The results demonstrate that the proposed Fuzzy Sugeno-based approach can significantly enhance inventory prediction accuracy and reduce the risk of stockouts or excess inventory. By adapting to changing market demands and operational conditions, this method contributes to improved production efficiency, cost reduction, and overall business sustainability in the food industry.]]>
<![CDATA[Application of Fuzzy Logic in Tempe Production Using the Tsukamoto Algorithm ]]>
<![CDATA[Daffa Zulqisthi]]>;
<![CDATA[Muhammad Faiz Assariy]]>;
<![CDATA[Mrr Lukie Trianawati]]>;
<![CDATA[Syafira Aristawidya]]>;
<![CDATA[Chandradewi Ekaputri]]>;
<![CDATA[Hafizhah Nur Humairah]]>;
<![CDATA[Gita Aisy Affatunnisa]]>;
<![CDATA[Aliya Fidella]]>;
<![CDATA[Muhammad Ghifari Fazan Putra]]>;
<![CDATA[Chika Hayya Sabillah]]>
<![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/aygmd359
<![CDATA[Fuzzy logic is widely used in various fields to formalize human behavior by considering inaccurate or partial reasoning. This study implements the Tsukamoto fuzzy logic method to analyze tempe production based on demand and inventory data. The research utilizes library research methods and data analysis using MATLAB (Matrix Laboratory). The Tsukamoto method was chosen for its high tolerance for data and flexibility. The system uses two input variables: demand and inventory, with output being production quantity. The fuzzy sets for demand are categorized as "Decrease" and "Increase" with a domain of [1000; 2000], inventory as "Few" and "Many" with a domain of [100; 600], and production as "Decrease" and "Increase" with a domain of [1520; 2100]. Using four fuzzy rules and the defuzzification process, the system can predict optimal production quantities. For example, with a demand of 1500 and inventory of 400, the system calculates a production quantity of 1823 units. This implementation demonstrates the effectiveness of the Tsukamoto method in automating production decisions based on demand and inventory variables.]]>
<![CDATA[Nutrition Optimization through the Application of Fuzzy Logic in Determining the Best Packaged Milk Drinks ]]>
<![CDATA[Debby Marsela]]>;
<![CDATA[Briliant Rutmana Siregar]]>;
<![CDATA[Lintang Putri Salshabila]]>;
<![CDATA[Mir’atul Azizah]]>;
<![CDATA[Muhammad Hasan Farid]]>;
<![CDATA[Sabrina Salsabila]]>;
<![CDATA[Umratul Umami]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 4 (2025): September 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/857ewt56
<![CDATA[The application of fuzzy logic in decision making is growing, especially in determining products that meet certain criteria. This study aims to apply the Mamdani fuzzy logic method to recommend the best packaged milk based on protein content and price. Input data in the form of price and protein content are converted into fuzzy sets and processed using MATLAB application. The process of fuzzification, rule determination, inference, and defuzzification produces ideal milk recommendations according to consumer preferences. The results show that products with high protein content and affordable prices have the highest recommendation rate. This method helps consumers in choosing dairy products that suit their nutritional needs and budget.]]>
<![CDATA[Implementation of Fuzzy Logic in Temperature Control Systems for Baking Ovens ]]>
<![CDATA[Andhika Rizky Maulana]]>;
<![CDATA[Chika Hayya Sabillah]]>;
<![CDATA[Muhammad Faiz Assariy]]>;
<![CDATA[Daffa Zulqhisti]]>;
<![CDATA[Rahadian Ilyasa Muhammad]]>;
<![CDATA[Mutiara Ade Rosseta]]>;
<![CDATA[Fairuz Kamilah Ihsan]]>;
<![CDATA[Melati Afdizha]]>;
<![CDATA[Cindy Novitasari]]>;
<![CDATA[Azhar Nasywa Saputra]]>;
<![CDATA[Mrr Lukie Trianawati]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 4 (2025): September 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/8y8g8f28
<![CDATA[To produce bread of the highest quality, it is essential to use the right type of bread oven, especiallygiven the rapid growth of the bread industry. This study investigates the use of fuzzy logic as an automatedmethod for controlling the baking oven temperature. By using fuzzy logic, it is expected that the oven canmaintain an ideal temperature, resulting in consistent bread quality that meets expected standards. Fuzzy controlsystems differ from conventional control systems, which tend to be rigid.The aim of this research is to develop a more efficient automated control system for regulating oventemperature to ensure consistent bread quality throughout the baking process. It is hoped that, with thisautomated control system, bread quality will not only improve but also enhance the production efficiency of thebaking industry as a whole. Additionally, this study considers the type of bread being baked as a factorinfluencing the quality of the final product. Initial trials show that the fuzzy logic design produces satisfactoryresults, with the ability to adjust rules as needed.]]>
<![CDATA[Implementation of Fuzzy Logic to Control Temperature and Incubation Time for the pH of Yoghurt ]]>
<![CDATA[ratna aryanti]]>;
<![CDATA[Chika Hayya Sabillah]]>;
<![CDATA[Muhammad Faiz Assariy]]>;
<![CDATA[Daffa Zulqihisti]]>;
<![CDATA[Ronnauli Lamria Sirait]]>;
<![CDATA[Rizki Laksana Putra]]>;
<![CDATA[Maharshi Kaloka Parahita]]>;
<![CDATA[Fauzan Maula Abdullah]]>;
<![CDATA[Dhiya Ananta Pranadita]]>;
<![CDATA[Delia Noor S]]>;
<![CDATA[Afrida Rif'atul Hanifa]]>;
<![CDATA[Lukie Trianawati]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 4 (2025): September 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/9r33bp20
<![CDATA[This research develops a fuzzy logic-based yoghurt production model by considering incubation temperature and incubation time as the main variables that influence the final pH of yoghurt. In this study, 49 yoghurt samples were produced and tested in two replications to obtain pH data which was then processed through fuzzy modeling. This fuzzy model is for determining fuzzy rules and membership functions. By using two fuzzy sets for each parameter and the Mamdani method, a total of 49 fuzzy logic rules were built to describe the relationship between incubation variables and final pH. Matlab 2015a software was used to process data and assess model accuracy. The results showed that this model was effective for predicting the final pH of yoghurt, which is important for maintaining product quality. In the future, it is hoped that this model can be applied to automated production lines, thereby supporting yoghurt production on an industrial scale with greater consistency and efficiency, especially ini the food sector.]]>
<![CDATA[Using Fuzzy Logic-Based Mamdani to Predict Catfish Larval Rearing ]]>
<![CDATA[Rangga Ardiansyah]]>;
<![CDATA[Daffa Zulqisthi]]>;
<![CDATA[Muhammad Faiz Assarly]]>;
<![CDATA[Sahrul Aidil Adhar]]>;
<![CDATA[Najla Nadashifa Wicaksono]]>;
<![CDATA[Fauziah Siti Khodijah]]>;
<![CDATA[Sili Maysaroh]]>;
<![CDATA[Sofie Saharsa Leilani Katim]]>;
<![CDATA[Nisrina Ratu Hadayani Samosir]]>;
<![CDATA[Razfa Muhamad Zaki Adz Dzikri]]>;
<![CDATA[Muhammad Ikmal Muhaniq]]>;
<![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: 10.62535/24tjgp28
<![CDATA[Catfish (Clarias sp.) larvae are highly sensitive to environmental changes, particularly in water quality parameters such as temperature, pH, and dissolved oxygen (DO), which significantly affect their survival rate (SR). This study aims to design a real-time prediction system for catfish larval survival using Mamdani fuzzy logic to support more accurate and adaptive water quality management. The research was conducted from April to May 2025 at the Hatchery, IPB Vocational School. The methodology involves constructing a Mamdani fuzzy inference system in MATLAB based on secondary data (SNI 6484:3:2014 and previous studies) and field observations. Three main input parameters temperature, pH, and DO. Were categorized into fuzzy sets using triangular membership functions. A total of 84 fuzzy rules were developed to infer SR, which was also divided into three categories: low, moderate, and high. Simulation results using the Rule Viewer and Surface Viewer showed that DO had the strongest influence on SR followed by temperature, while pH had a relatively minor effect. Under low DO conditions (<3 mg/L), SR predictions were consistently low regardless of other variables. In conclusion, the Mamdani fuzzy logic system proves effective in predicting catfish larval SR and can be a valuable tool for optimizing aquaculture practices.]]>
<![CDATA[ESP32-Based Ornamental Fish Feeding Automation System With Sensor Utilisation and Fuzzy Logic Implementation ]]>
<![CDATA[Muhammad Hafidz Fachrezi]]>;
<![CDATA[Darrell Juro Rudy Pradana]]>;
<![CDATA[Aulia Najiha Putri]]>;
<![CDATA[Aisyah Rahmadiniyah]]>;
<![CDATA[Dhaifan Rahadhian]]>;
<![CDATA[Shalfa Hafizh Sulaiman]]>;
<![CDATA[Atikah Safitri Siregar]]>
<![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/wfkftp07
<![CDATA[The efficiency of ornamental fish feeding significantly influences fish health and water quality in aquaculture systems. Manual feeding often results in overfeeding or underfeeding, leading to water pollution and reduced fish productivity. This study aims to design and implement an automated ornamental fish feeding system using the ESP32 microcontroller integrated with temperature, pH, and dissolved oxygen sensors. The system employs Mamdani fuzzy logic to determine feeding quantities based on real-time environmental parameters. Research was conducted at the Aquaculture Production Laboratory and Hardware Laboratory 2, IPB University. The results show that the system is capable of dynamically adjusting feeding amounts, thereby reducing feed waste and maintaining water quality. The fuzzy logic approach allows for adaptive and efficient feeding management, outperforming fixed-timer systems. This automation technology supports sustainable and technology-driven ornamental fish farming.]]>
