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[Chicken Egg Hatching Optimization with Automatic Control Using Fuzzy Logic ]]>
<![CDATA[Desita Auliafitri]]>;
<![CDATA[Erry RizkySuro]]>;
<![CDATA[Tedi Kurniawan]]>;
<![CDATA[Muhammad Danang Mukti Darmawan]]>;
<![CDATA[Fiqri Nurfadillah]]>;
<![CDATA[Nanda Octavia]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 1 No. 3 (2024): June 2024 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/0m1ks522
<![CDATA[Egg hatching is an important process in the livestock industry to produce quality poultry seedlings. In the hatching process environmental conditions such as temperature and humidity must be carefully regulated to ensure optimal hatching. In an effort to improve the efficiency and accuracy of hatching, this research introduces an egg hatching machine tool that adopts a fuzzy logic approach. The developed machine tool is equipped with temperature and humidity sensors that measure the environmental conditions inside the egg incubator in real-time. The data obtained from the sensors are used as inputs for a fuzzy logic-based control system that regulates the temperature and humidity of the incubator. The hatching machine is built keeping in mind the ideal conditions between 35° - 40° with 70% - 80% humidity. Fuzzy logic allows the system to handle uncertainty and ambiguity in temperature and humidity settings. Based on the fuzzy rules set, the system can adaptively adjust the environmental conditions to achieve optimal conditions for hatching eggs.]]>
<![CDATA[Application of Fuzzy Logic in Air Conditioner Temperature Control in Rooms with Partitions in Boarding Houses ]]>
<![CDATA[Ihda Rahmadaniar]]>;
<![CDATA[Muhammad Karim Bachtiar]]>;
<![CDATA[Ramma Dwi Rachmat]]>;
<![CDATA[Danang Mukti Darmawan]]>;
<![CDATA[Fiqri Nurfadillah]]>;
<![CDATA[Nanda Octavia]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 1 No. 5 (2024): November 2024 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/4bra8966
<![CDATA[This research investigates the application of fuzzy logic with the Mamdani method to regulate room temperature using an air conditioner (AC) in a boarding house environment with a partition at Bogor City, Indonesia. By considering variables such as room size, external temperature (weather), and air conditioner specifications, this research aims to achieve a balance between occupant comfort and energy efficiency. The optimal temperature for each room in the boarding house will be determined through fuzzy logic calculations. This research aims to open up new potentials in intelligent and sustainable temperature regulation in a boarding house or similar environment. This research method uses fuzzy logic for room temperature control using Matlab software.]]>
<![CDATA[Prediction of Water Quality in Ponds Based on Temperature, Water Clarity, pH, and Dissolved Oxygen Using Mamdani Fuzzy Logic ]]>
<![CDATA[Fadly Ramdani]]>;
<![CDATA[Daryn Ramadhani Az Zahra]]>;
<![CDATA[Herlambang Nurasyid Ramdhani]]>;
<![CDATA[Mohamad Fikih Amar Dani]]>;
<![CDATA[Fiqri Nurfadillah]]>;
<![CDATA[Muhammad Danang Mukti Darmawan]]>;
<![CDATA[Nanda Octavia]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 2 (2025): March 2025 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/n729q614
<![CDATA[Water quality is pivotal for successful fish breeding, particularly in pond-based systems. This paper reviews several studies on water quality assessment in fish ponds, analyzing physical and chemical parameters such as temperature, water clarity, pH, and dissolved oxygen (DO). However, existing studies often need help in precisely evaluating water quality due to uncertainties in the obtained values. This study suggests applying fuzzy logic; specifically, the Mamdani method-to produce more accurate and conclusive assessment values to overcome this problem. Fuzzy logic enables the processing of vague information, overcoming existing uncertainties. The study highlights four key parameters; temperature, water clarity, pH, and dissolved oxygen-consistently influencing water quality assessment. By incorporating Mamdani fuzzy logic into water quality evaluation, this research aims to enhance the accuracy and effectiveness of assessment methods, thereby advancing previous research efforts in fisheries cultivation.]]>
<![CDATA[Prediction on Target of Underprivileged Scholarships Using Fuzzy Logic Method ]]>
<![CDATA[Afifah Rodhiyatun Nisa]]>;
<![CDATA[Daffa Adrian Ahmadi Tondang]]>;
<![CDATA[Fauzan Perdana Ilham]]>;
<![CDATA[Ghani Trie Aqeela Ramadhani]]>;
<![CDATA[Muhammad Danang Mukti]]>;
<![CDATA[Fiqri Nurfadillah]]>;
<![CDATA[Nanda Octavia]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 1 No. 2 (2024): March 2024 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/4bg52465
<![CDATA[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.]]>
<![CDATA[Application of Fuzzy Logic to Predict Rice Production Quantity in Bogor Regency ]]>
<![CDATA[Dhia Suhaila]]>;
<![CDATA[Muhammad Hafizh Maulidan]]>;
<![CDATA[Muchammad Alifandhino Satrio]]>;
<![CDATA[Ananditto Daffa Wijayanto]]>;
<![CDATA[Muhammad Danang Mukti Darmawan]]>;
<![CDATA[Fiqri Nurfadillah]]>;
<![CDATA[Nanda Octavia]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 1 No. 2 (2024): March 2024 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/cbrrmp50
<![CDATA[This study aims to understand prediction methods using fuzzy Mamdani logic to conclude the quantity of rice production in the Bogor Regency area. Then in this study, we used quantitative methods and involved interviews with resource persons, namely rice mill workers and farmers. The data obtained from the interview is then fuzzyfication to be used in calculations. The main finding of this study is the elaboration of crop quantity from small, normal, and many, with the range of yields produced ranging from 0 to 3000 KG for little, 3000 to 6000 KG for normal, and 6000 to 10000 KG for many. Weather and humidity observations were found to significantly affect rice yields. The implications of these findings are improved accuracy in yield estimation, and the ability to address uncertainty and complexity in factors affecting crop growth. Despite the limitations of this study, such as limited data and remote study locations, the use of fuzzy logic can make a crucial contribution to determining the quantity of water needed for plant growth based on rainfall and weather conditions. This research is crucial because it can be a reference for future research that uses fuzzy logic to determine the quantity of rice production. ]]>
<![CDATA[Prediction of flood depth detection system from rainfall with normal, alert and hazard levels based on fuzzy logic ]]>
<![CDATA[Arya Prabudi Jaya Priana]]>;
<![CDATA[Itqon Madani]]>;
<![CDATA[Vanya Amanda Lovely]]>;
<![CDATA[Fiqri NurFadillah]]>;
<![CDATA[Muhammad Danang Mukti Darmawan]]>;
<![CDATA[Nanda Octavia]]>
<![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/ba8ygx44
<![CDATA[Floods are natural calamities that frequently transpire and are of primary concern for governmental entities due to their potential for significant losses and casualties. Heavy rainfall and overflowing water stand as the primary triggers for flooding. Many communities lack adequate knowledge to forecast floods, thus necessitating technological interventions for early water depth detection and issuing flood warnings. This study devised a water depth detection system based on fuzzy logic using Arduino as a microcontroller. The system employs ultrasonic sensors for water level detection and a Tipping Bucket for precipitation measurement. Its primary objective is to establish a system capable of issuing early flood warnings through alarms. The outcome of this research entails the implementation of an Arduino Uno-based flood detection system that aids users in monitoring water levels and anticipating floods. Safety considerations are also addressed by incorporating fuzzy logic technology to forecast flood potential based on water level and rainfall data. The utilization of fuzzy logic enables the system to navigate uncertainties and ambiguities in data, thus furnishing more precise and dependable early warnings. Consequently, the findings of this study serve as a groundwork for the advancement of more sophisticated and efficient flood detection systems in the future. ]]>
<![CDATA[Prediction Fuzzy Implementation in Monitoring System Based On Humidity, Soil Quality, And Environmental Conditions ]]>
<![CDATA[Brilliant Sandynigy Fernando]]>;
<![CDATA[Muhamad Rangga Maulana Malik]]>;
<![CDATA[Fauzan Graha Dwi Putra]]>;
<![CDATA[Stivan Hari Sukma]]>;
<![CDATA[Muhammad Danang Mukti Darmawan]]>;
<![CDATA[Nanda Octavia]]>;
<![CDATA[Fiqri Nurfadillah]]>
<![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/fffrrw78
<![CDATA[This research aims to evaluate the quality of soybean plant growth by considering three main factors: moisture content, light intensity, and soil pH. The Mamdani method is used as a system approach to optimize the processing of collected data for plant growth support. Measurements were taken using a sampling method to analyze the data comprehensively. In this experiment, moisture content, light intensity, and soil pH were measured to create optimal conditions for soybean plant growth. The implementation of the Mamdani method in this system is done by classifying inputs, such as data on water content, light intensity, and soil pH used during the planting period, then producing outputs based on experiments conducted according to predetermined criteria. Furthermore, comparisons are made to the samples to get the results of data analysis. This method can provide recommendations for optimizing environmental conditions for plants. By utilizing MATLAB application, accurate data analysis and visualization of results can be done efficiently. This research is expected to provide in-depth insight into the complex interactions between the three factors and their impact on soybean plant growth. This has significant implications for the development of sustainable agriculture and can provide valuable insights for farmers to improve soybean yields.]]>
<![CDATA[Application of Fuzzy Logic in Prediction to Determine the Value of Water Quality and Environment in Lettuce Hydroponics ]]>
<![CDATA[Gusti Ramdani]]>;
<![CDATA[Ahmadiki Firman Dwi Suryawan]]>;
<![CDATA[Muhammad Raihan Ramadhan Steyer]]>
<![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/m13dqn59
<![CDATA[The need for food such as vegetables and fruits will never stop. Meanwhile, with the times, agricultural land is decreasing. In order to meet food needs, the community needs to make efforts to utilize limited agricultural land by applying hydroponic farming techniques. With hydroponic techniques, people can produce vegetables and fruits to fulfill their food needs. Yields from hydroponics are influenced by several factors, such as water quality and the surrounding environment. In grouping the quality of crops can use the help of fuzzy logic. That way, the application of fuzzy logic in hydroponic farming techniques is useful for assessing the quality of food needs]]>
<![CDATA[Mamdani's Fuzzy Logic-Based Tapioca Optimal Production Amount Prediction System ]]>
<![CDATA[Tiara Safitrah]]>;
<![CDATA[Divo Wibowo Adi]]>;
<![CDATA[Irfan Tigranaufal Nugraha]]>;
<![CDATA[Antonio Banggas Gregory Sinaga]]>;
<![CDATA[Zaki Rafi Athallah]]>;
<![CDATA[Mohammad Akbar Alfa Dirk Steyer]]>;
<![CDATA[Sesar Husen Santosa]]>;
<![CDATA[Muhammad Danang Mukti Darmawan]]>;
<![CDATA[Nanda Octavia]]>
<![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/ws0haa49
<![CDATA[This research focuses on the imbalance between supply and demand in the tapioca industry, especially on the scale of Small and Medium Industries (SMI). Such challenges involve price fluctuations and lack of efficiency in determining the optimal production amount. Using fuzzy logic as an artificial intelligence method, this research aims to develop a system for predicting the optimal amount of tapioca production that can increase efficiency, reduce waste of raw materials and energy, and stabilize prices. The data used in this study was obtained through interviews with resource persons who are involved in the field of tapioca SMI. Furthermore, the data was processed using the Mamdani Fuzzy Inference System method. The results showed that in the case of production when demand is 400 kg and cassava availability is 2000 kg, the optimal production amount of tapioca is 630 kg. This value is also consistent when proven using the Matlab R2015a application. This shows that the model can be relied upon in determining the decision on the amount of tapioca production by considering demand factors and raw material availability.]]>
<![CDATA[Implementation of Fuzzy Logic to Determine the Doneness of Beef Steak ]]>
<![CDATA[Sista Naelly Adzimi]]>;
<![CDATA[Robby Priaji Sakti]]>;
<![CDATA[Aldiyansyah]]>;
<![CDATA[Muhammad Ifan Al Aziz]]>;
<![CDATA[Muhammad Fakhri Alauddin]]>;
<![CDATA[Jimmy Mohamad Alpino Anak Gumay]]>;
<![CDATA[Sesar Husen Santosa]]>;
<![CDATA[Muhammad Danang Mukti Darmawan]]>;
<![CDATA[Nanda Octavia]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 1 No. 4 (2024): September 2024 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/93z2df58
<![CDATA[This study aims to implement fuzzy logic in determining the doneness level of beef steak based on the inputs of roasting time and roasting temperature. The output of the developed system is in the form of maturity levels in the categories of "rare", "medium rare", "medium", "medium well", and "well done". Data for this study were obtained through interviews with experienced beef steak sellers. This research method includes direct calculations as well as the use of MATLAB software to develop fuzzy logic systems. The results of the interview analysis are used as a basis for the formation of fuzzy rules for determining the degree of doneness of steaks. The results showed that in the example case with a roasting temperature of 300°C and a roasting time of 10 minutes, the resulting output value was 70, which placed the doneness of the steak in the "medium well" position. These results have been verified both through direct calculations and the use of MATLAB software. The study concluded that the implementation of fuzzy logic can help in determining the doneness level of beef steak, based on temperature variations and roasting time. ]]>
