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 Multi-Parameter Fuzzy Logic as a Decision Support System for Monitoring the Safety and Quality Stability of Postharvest Coffee Beans in the Agro-Industrial Storage Chain ]]>
<![CDATA[Nuraeni Latifathul Khasanah]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Mrr Lukie Trianawati]]>;
<![CDATA[Anindya Intan Putri]]>;
<![CDATA[Sherin Emania Putri]]>;
<![CDATA[Nasyaqilah Andrianita]]>;
<![CDATA[Azzahra Kamilia Salam]]>;
<![CDATA[Amanda Dhiya Ardhiningrum]]>;
<![CDATA[Sania Ramadhani]]>;
<![CDATA[Daffa Firdaus Putra]]>;
<![CDATA[Roma Juliana Arios]]>
<![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/pdfpje31
<![CDATA[Coffee is a key agricultural commodity that plays a strategic role in Indonesia’s economy, yet maintaining the safety and quality of post-harvest coffee beans remains a major challenge due to environmental fluctuations during storage. This study aims to apply a multi-parameter fuzzy logic system as a decision support tool for monitoring the temperature, humidity, and CO₂/VOC gas concentration in the agro-industrial coffee storage chain. A qualitative descriptive approach was employed using literature analysis and fuzzy logic simulation with the Mamdani inference method. The simulation results demonstrated that the fuzzy system can effectively classify storage risk levels into safe, moderate, and high-risk categories based on environmental variations. At optimal conditions of 20–25°C temperature and 60–70% relative humidity, the system maintained coffee bean quality in accordance with SNI 01-2907-2008 standards. Conversely, conditions exceeding 30°C and 75% humidity resulted in a high-risk index due to increased moisture, microbial growth, and oxidation. The fuzzy-based monitoring system offers a more adaptive and precise assessment compared to conventional threshold methods, enabling early detection of quality degradation. This research provides a practical reference for developing intelligent control systems to ensure sustainable post-harvest coffee quality management.]]>
<![CDATA[Web Application Using Fuzzy Logic to Assess Recommended Intake Frequency of Extruded Chiki Snacks ]]>
<![CDATA[Bayu Praditya]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Mrr Lukie Trianawati]]>;
<![CDATA[Rinunti Najwa Putri Minanti]]>;
<![CDATA[Nazwa Salsabila]]>;
<![CDATA[Tulus Fernando Sihombing]]>;
<![CDATA[Fairuz Aliyya Khansa]]>;
<![CDATA[Aurellia Avisa Putri Alya]]>;
<![CDATA[Rubina Alleysha Putri Aulia]]>;
<![CDATA[Hanifah Khusnul Syahida]]>;
<![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/nt94t493
<![CDATA[Excessive consumption of extruded snacks, particularly Chiki products high in sugar, salt, and fat, increases the risk of obesity, hypertension, and metabolic disorders. This study aims to develop a web-based fuzzy logic application using the Mamdani inference system to determine the recommended frequency of consumption based on nutrient composition. The research employed a quantitative descriptive approach integrating three main input variables: sugar, salt, and fat, each represented by fuzzy sets of low, medium, and high levels. The output variable, consumption frequency, was classified into three linguistic terms: daily safe, moderate, and limited. A total of 27 fuzzy rules were constructed and simulated using MATLAB. The results showed that the model effectively translated quantitative nutritional data into qualitative recommendations, with higher nutrient concentrations corresponding to lower consumption frequency. The fuzzy Mamdani model provided smooth decision boundaries, demonstrating high interpretability and potential as a nutritional decision support system for consumer health guidance.]]>
<![CDATA[Evaluation of the Effectiveness of the Sterilization Process on the Safety of Low-Acid Canned Food Using a Fuzzy Logic System ]]>
<![CDATA[Nanda Fadilah]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Anisa Raihanah]]>;
<![CDATA[Mrr Lukie Trianawati]]>;
<![CDATA[Salmadillah Dwiswara]]>;
<![CDATA[Muhammad Jundi]]>;
<![CDATA[Tiara Cahya Iman]]>;
<![CDATA[Rafa Anargya Putri]]>;
<![CDATA[Myra Riqqah Widyadhana]]>;
<![CDATA[Fajrina Aulia Naifa]]>;
<![CDATA[Rohmi Rihhadatul ‘Aisy]]>;
<![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/qkzjh318
<![CDATA[The sterilization process for low-acid canned foods is a crucial step in ensuring food safety and preventing the growth of harmful microorganisms such as Clostridium botulinum. Inappropriate sterilization temperature or time can affect product and safety. Therefore, a reliable evaluation system is needed. This study aims to assess the effectiveness of the sterilization process for low-acid canned foods using the Mamdani fuzzy logic system. The method used in this study is a systematic literature review of various previous studies on the sterilization process for products such as tuna, pineapple, button mushrooms, gudeg, and canned rendang. Data show that sterilization temperatures range from 110 to 126°C, with processing times between 10 and 50 minutes, resulting in F₀ values between 3.80 and 10.00 depending on the product type. Temperature and time variables are classified into three fuzzy inputs. Food safety outputs are determined based on if-then (F₀ > 3) and unsafe (F₀ < 3) categories. The results of this study indicate that the use of the Mamdani fuzzy logic system can provide a more flexible and accurate evaluation of the sterilization process. This approach can assist in determining appropriate sterilization parameters to ensure the quality and safety of low-acid canned food products]]>
<![CDATA[Assessment of Chicken Egg Appearance Using Mamdani Fuzzy Logic with Weight and Sphericity Inputs ]]>
<![CDATA[Muhammad Arkan Rabbani]]>;
<![CDATA[Annisa Raihanah]]>;
<![CDATA[Wuliddah Tamsil]]>;
<![CDATA[Lukie Trianawati]]>;
<![CDATA[Rahma Hanan Hafizhah]]>;
<![CDATA[Layla Hawa Sahda Zabrina]]>;
<![CDATA[Suci Nur Rahmadhani]]>;
<![CDATA[Azzahra Azifatuzzikri]]>;
<![CDATA[Jeany Permana]]>;
<![CDATA[Assyifa Ul Walidatul Arifin]]>;
<![CDATA[Diana Fitri]]>;
<![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/sbwr9205
<![CDATA[This study aims to design an egg appearance assessment system using fuzzy logic with input parameters of weight and sphericity. Manual egg sorting based on physical characteristics such as size and shape is often time-consuming and subjective, necessitating an automated classification system. The Mamdani fuzzy inference system was implemented using MATLAB Fuzzy Logic Toolbox to simulate the decision-making process. Triangular and trapezoidal membership functions were used for the input variables (weight and sphericity) and output variables (appearance quality), with linguistic terms such as light, normal, heavy, and abnormal, normal, round. The rule base consisted of nine if–then statements, with the defuzzification process using the centroid method. The system produced a crisp output value of 31.67, which falls into the “good” category, indicating that eggs weighing 55 g and with a roundness of 0.85 are classified as good quality eggs. Visualization through Surface Viewer and Rule Viewer shows that this model is capable of capturing nonlinear relationships between variables and providing adaptive classification results. The results of this study indicate that Mamdani fuzzy logic can assess egg quality accurately and efficiently, and serve as a reliable basis for the development of intelligent automatic sorting systems in the poultry industry.]]>
<![CDATA[Early Detection of Pasteurized Milk Spoilage Using Fuzzy Logic Based on Storage Temperature and pH ]]>
<![CDATA[Muhammad Fakhri Hakim]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Mrr Lukie Trianawati]]>;
<![CDATA[Syahrial Ramadhan]]>;
<![CDATA[Khalisa Nisrina Putri]]>;
<![CDATA[Huaida Nuraeni]]>;
<![CDATA[Anisa Fitri Gunawan]]>;
<![CDATA[Siti Nur Fauzia Rahmah]]>;
<![CDATA[Anggita Alit Pratiwi]]>;
<![CDATA[Alya Nur Ismiyati]]>;
<![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/ncctb626
<![CDATA[Pasteurized milk is highly susceptible to spoilage due to its rich nutritional content and sensitivity to temperature fluctuations during storage. Conventional methods for detecting milk spoilage are often time-consuming and require laboratory testing. This research aims to develop an early detection model for pasteurized milk spoilage using the Sugeno fuzzy inference system based on storage temperature and pH parameters. The model applies two input variables, namely temperature and pH, and one output variable that classifies the milk condition into three categories: safe, warning, and spoiled. Data were obtained by storing pasteurized milk at different temperature conditions while monitoring pH changes over time. The Sugeno fuzzy model was implemented using MATLAB to process the data and generate numerical output representing spoilage risk levels. The results show that the Sugeno fuzzy inference system can effectively classify the milk condition with a prediction accuracy of 86.7 percent. The model indicates that higher storage temperatures and lower pH values significantly increase the risk of spoilage. Therefore, the Sugeno fuzzy logic model can be applied as an efficient, quantitative, and reliable method for real time quality monitoring and early detection of pasteurized milk spoilage.]]>
<![CDATA[Analysis of the Effect of Protein Content and Preheating Temperature on the Hardness of SPC Biscuits Using the Fuzzy Logic Method ]]>
<![CDATA[Muhammad Alpiansyah]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Mrr Lukie Trianawati]]>;
<![CDATA[Syifa Fauziyah]]>;
<![CDATA[Nida Qotrunnada]]>;
<![CDATA[Naura Alissa Davellitha]]>;
<![CDATA[Meylani Awaliyah]]>;
<![CDATA[Izza Afkarina Umar]]>;
<![CDATA[Davina Baiza Radityaputri]]>;
<![CDATA[Akmal Kayru Raid]]>;
<![CDATA[Rome Juliana Arians]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 1 (2026): January 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/6h6fq558
<![CDATA[This study aimed to analyze and model the non-linear effect of protein content and preheating temperature on the hardness of Soy Protein Concentrate (SPC)-based biscuits using the Sugeno fuzzy logic method. A descriptive quantitative approach was employed, utilizing the Sugeno-type Fuzzy Inference System (FIS) designed and implemented using MATLAB software. The inputs were protein concentration (7-16%) and preheating temperature (70-90°C), with biscuit hardness (747.5-2176.5 gf) as the output. The system successfully mapped the complex interactions through nine fuzzy if-then rules. The results showed that increasing protein content generally increases hardness, particularly at higher preheating temperatures. However, excessive heating at medium protein content led to a decrease in hardness due to structural degradation. The defuzzification surface indicated that the preheating temperature has a relatively stronger influence on the final hardness than protein content. The developed fuzzy model provides accurate and interpretable predictions (e.g., 11.5% protein and 80°C yields a medium hardness of 1.45 x 10³ gf), proving its effectiveness as an adaptive decision-support tool for optimizing high-protein biscuit production.]]>
<![CDATA[Evaluating the Quality Grade of Cookies through Crispness and Baking Temperature Analysis Using a Fuzzy Inference System ]]>
<![CDATA[Raihan Vivardian]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Mrr. Lukie Trianawati]]>;
<![CDATA[Arisya Putri Hanifah]]>;
<![CDATA[Tausy Fadilla]]>;
<![CDATA[Salma Anjela]]>;
<![CDATA[Fransiska Yulia Chandra]]>;
<![CDATA[Octari Rahmawati]]>;
<![CDATA[Pelita Sari]]>;
<![CDATA[Kayana Devin Bazzani Karo Karo]]>;
<![CDATA[Roma Juliana Arios]]>
<![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/p44bqb37
<![CDATA[Cookies are one of the most popular processed food products due to their distinctive taste, long shelf life, and variety of textures ranging from soft to crisp. Physical properties such as crispiness play an important role in determining consumer preferences and acceptance. These characteristics are influenced by several factors, one of which is the baking temperature that determines the quality of soft cookies. Advances in computing technology have enabled objective food quality analysis through artificial intelligence approaches. This study aims to evaluate the suitability of cookies based on crispiness and baking temperature parameters using the Fuzzy Inference System (FIS) method. The research was conducted using a fuzzy system designed with input variables of temperature and crispiness, and output variables of product quality categorized as poor, moderate, and good. Each variable was represented in the form of a triangular membership function. The results showed that fuzzy logic was able to effectively integrate parameters, making it a smart and objective quality assessment method.]]>
<![CDATA[Fuzzy Logic Approach to Determine Apple Maturity for Harvesting Decision ]]>
<![CDATA[Muhammad Rafi Andika Wijaya]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Mrr Lukie Trianawati]]>;
<![CDATA[Syadza Afifah Nuri]]>;
<![CDATA[Senja Surya Gama]]>;
<![CDATA[Putri Nurbaiti]]>;
<![CDATA[Nisrina Fatin Nadra]]>;
<![CDATA[Fional Alvina Nirmala Putri]]>;
<![CDATA[Ayu Nur Fadhila]]>;
<![CDATA[Anindya Salsabila Hamdani Putri]]>;
<![CDATA[Roma Juliana Arios]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 1 (2026): January 2026 ]]>
Publisher : <![CDATA[Batrisya Education ]]>
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DOI: 10.62535/2awk4n51
<![CDATA[This study aims to develop a fuzzy logic–based system for determining the maturity level of Anna apples as a basis for harvest decision-making. Five key parameters were used as input variables: Flesh Firmness (FF), Soluble Solid Content (SSC), Starch Pattern Index (SPI), Total Acidity (TA), and Hue°, with one output variable representing the maturity level (unripe, ripe, and overripe). The research employed a literature review method with a qualitative descriptive approach by collecting data from scientific journals and relevant documents discussing apple maturity and the application of fuzzy logic in agriculture. Data analysis was conducted using MATLAB through processes including fuzzification, formulation of If–Then rules, Mamdani inference, and defuzzification to produce a crisp output value representing apple maturity. The results indicate that the fuzzy logic system effectively models apple maturity parameters and provides accurate, objective, and efficient decisions compared to conventional subjective methods. The application of fuzzy logic offers a non-destructive classification method that assists farmers in determining the optimal harvest time, improving post-harvest quality, and maintaining product consistency.]]>
<![CDATA[Evaluation of Cassava Chip Crispness Using a Fuzzy Logic System Based on Temperature and Vacuum Pressure Variables ]]>
<![CDATA[Arya Rafly Maulana Sopyan]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Mrr Lukie Trianawati]]>;
<![CDATA[Riza Safira]]>;
<![CDATA[Riyatin Tsani Fatikhah]]>;
<![CDATA[Nisa Akmala Sidik]]>;
<![CDATA[Luthfitah Sys Febriana]]>;
<![CDATA[Hikma Hijrianita Putri Lesmana PS]]>;
<![CDATA[Chiara Kalyla]]>;
<![CDATA[Aulia Zahwa Gharini]]>;
<![CDATA[Roma Juliana Arios]]>
<![CDATA[ Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 1 (2026): January 2026 ]]>
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DOI: 10.62535/cz87d281
<![CDATA[The study evaluates cassava chip crispness using a fuzzy logic system based on temperature and vacuum pressure variables. Fuzzy logic system is applied to objectively assess crispness, modeling the relationship between frying variables and chip texture. The application of fuzzy systems as a quality control tool can help optimize the production process so that chips meet standards. This study employs a literature review combined with an expert-based approach to design a fuzzy logic system for evaluating the crispiness of cassava chips based on temperature and pressure variables. For input and output variables, we use temperature and vacuum pressure. The temperature range used is 140-200°C and for pressure variable, we use -65, -68, -72 CmHg. Sensory values for the three crispness categories show that the undercooked category received an average score of 3.76 ± 0.52, the crisp (optimal) category received 3.72 ± 0.88, and the overcooked category received 3.85 ± 0.11. Combination of temperature 170°C and vacuum pressure -68.5 CmHg yields the best crispness result, showing that the chips reach the desired texture, not too hard and not too soft. This demonstrates that the centroid method provides a representative defuzzified value that closely reflects actual frying conditions, ensuring consistent product quality.]]>
<![CDATA[Application of Fuzzy Logic For Feasibility Evaluation of Pasteurized Milk Consumption Based On Processing Temperature and pH ]]>
<![CDATA[Nauval Artyasta]]>;
<![CDATA[Wuliddah Tamsil Barokah]]>;
<![CDATA[Annisa Raihanah Maimun]]>;
<![CDATA[Mrr. Lukie Triniawati]]>;
<![CDATA[Phasya Laila Safitri]]>;
<![CDATA[Indah Puji Lestari]]>;
<![CDATA[Fawziya Nusa Hrishita]]>;
<![CDATA[Priskila Margaretha Sibagariang]]>;
<![CDATA[Fila Adida Pranata]]>;
<![CDATA[Fathan Ahmad Munawwar]]>;
<![CDATA[Roma Juliana Arios]]>
<![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/fkxacz02
<![CDATA[This study utilizes a fuzzy logic approach to analyze the consumption feasibility of pasteurized milk, focusing on the interplay between temperature and pH as key quality indicators. Given milk's perishable nature and the inherent imprecision of conventional monitoring methods, fuzzy logic provides a more adaptive and realistic assessment system. The Mamdani fuzzy system employed involves fuzzification, inference, and defuzzification to convert temperature and pH data into a quantifiable crisp output. Results, validated by the Fuzzy Control Surface and Centroid calculation (Sample 1: Temp 63, pH 5.4), demonstrate that the highest risk of damage occurs when low temperature combines with acidic (low) pH, leading to an "Not Acceptable" classification. Conversely, maintaining a neutral or high pH significantly mitigates the risk, even under cold conditions. In conclusion, the fuzzy logic approach proves effective for automated quality monitoring, accurately identifying high-risk conditions based on the simultaneous relationship between temperature and pH.]]>
