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Chika Hayya Sabillah
IPB University
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Social Sciences

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DETERMINING THE AMOUNT OF TEMPEH PRODUCTION BASED ON DEMAND AND INVENTORY DATA USING FUZZY LOGIC METHOD (CASE STUDY: “MURNI” SOYBEAN TEMPE MSMEs MADIUN) Nazwa Khairunnisa; Muhammad Faiz Assariy; Daffa Zulqisthi; Muhammad Raihan Prasetya; Kanaya Fatimah Madania; Holy Nurani Rabbina; Rifki Oktavia; Siti Hasna Raihana; Astrid Virta Ayu Alzahra; Chika Hayya Sabillah
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 3 (2025): June 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/7pbt8t33

Abstract

Tempeh is a typical Indonesian food that is consumed by almost all people. In the industrial world, companies are required to increase productivity because many competitors are increasingly competitive. The increase in raw material prices makes companies reluctant to buy materials in large quantities, so companies tend to maintain stock or supply of materials in order to meet increasing demand. This research aims to estimate the amount of tempe production using the Mamdani fuzzy logic approach with consideration factors in the form of supply and consumer demand. The research method uses literature reviews, testing with Matlab, and manual calculations to analyze demand and supply of tempeh in the industry. The test results using Matlab and manual calculations on tempe demand and supply obtained data that is in accordance with existing history, where if there is a demand for 6006 units of tempeh with a raw material supply of 6945, then it is predicted that the company will produce 6569 units of tempeh. It is hoped that this research can help the tempe industry in preparing production plans.  
Fuzzy Logic Approach in Palm Oil Production Using the Mamdani Method Bayu Adi Nugroho; Muhammad Faiz Assariy; Daffa Zulqisthi; Mrr.Lukie Trianawati; Sri Diana Sari; Nur Syahla Fatimah; Itsnaini Nur Rohmawati; Huwaida Asha Dhieva; Denisa Nurul Az Zahra; Arifa Fauzia Rahma; Chika Hayya Sabillah
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 2 (2025): March 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/yzempr96

Abstract

This research investigates the application of the Mamdani fuzzy logic method for predicting palm oil production based on consumer demand and supply data. The purpose is to enhance the accuracy of production forecasts critical for optimizing the palm oil industry in Indonesia. The methodology involves data collection on consumer demand and supply, formation of fuzzy sets, rule definition, and inference processing. Results indicate that the Mamdani method effectively correlates demand and supply levels with production outcomes, yielding consistent predictions when compared to manual calculations. The findings conclude that implementing fuzzy logic can significantly improve decision-making in palm oil production, leading to more efficient and sustainable practices within the industry. This study highlights the potential of fuzzy logic applications in agricultural production systems for better resource management.
Mango Quality Measurement System Based on Ripeness, Size, and Spot Area Using Fuzzy Inference System Aziz Rabih Rabbani; Muhammad Faiz Assariy; Daffa Zulqisthi; Chika Hayya Sabillah; Shalinadira Koswara; Lola Amelia; Iofema Malika; Hilda Fitria Hidayah; Fildza Khairunida; Annisa Pertiwi Hakim; Atikah Fahni; Mrr Lukie Trianawati
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 2 (2025): March 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/2d4bfb38

Abstract

Mango (Mangifera indica) quality assessment poses challenges in traditional grading methods, primarily relying on visual inspection, which can be subjective. This research aims to develop a Fuzzy Inference System (FIS) for evaluating mango quality based on parameters such as color, size, and spots. A qualitative data collection approach was employed through literature review and expert opinions, followed by the application of fuzzy logic using MATLAB to analyze the parameters affecting quality. The results demonstrate that mangoes classified as "Good" are characterized by larger size, a high or medium distribution of red color, and small spots. Defuzzification was performed using the Centroid Method to derive a crisp output, which indicated a quality leaning towards the "Well" category with a value of approximately 0.5584. This study highlights the efficacy of fuzzy logic in transforming qualitative assessments into quantitative measures, enhancing the reliability of agricultural evaluations.
Design of Temperature and Humidity Control System for Cocoa Bean Dryer Using Fuzzy Mamdani Method Taufan Taufan Putra ananta; Chika Hayya Sabillah; Muhammad Faiz Assariy; Daffa Zulqisthi; Mariati; Putri Nurhaliza Candra; Audrey Anastasia Silaen; Febrina Disa Cinta Prasetyo; Windy Fadhilah Aprilia; Alifvia Nabila Cesarina Subekti; Mrr Lukie Trianawati
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 1 (2025): January 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/qfzg3m58

Abstract

This research aims to develop a fuzzy logic control system for optimizing temperature and humidity during cocoa bean fermentation. The study employs a literature review method and data analysis using MATLAB. A Mamdani-type fuzzy inference system is designed to control the temperature and humidity of a cocoa bean dryer. Input variables include temperature (0-65°C) and humidity (0-100%), while output variables are heater and fan settings. The system's performance is evaluated using a case study, demonstrating its ability to adjust heater and fan operations based on environmental conditions. Results show that for an input of 65°C temperature and 50% humidity, the system recommends turning off the heater (membership value 79.8) and running the fan at high speed (membership value 84.7). This fuzzy logic approach offers a promising solution for maintaining optimal conditions during cocoa bean fermentation, potentially improving the quality and consistency of the final product. Keywords: cocoa fermentation, fuzzy logic control, temperature regulation
Determining Tofu Production Volume Using Fuzzy Logic Mamdani Method Jason Timoty Wijaya; Chika Hayya Sabillah; Muhammad Faiz Assariy; Daffa Zulqisthi; Vira Aulia Puteri; Salsabilla Kansa Ismail; Rizqi Hasna Amalia; Riris Rahayu; Hilda Aulia Ainussyfa; Evy Apriliani; Annisa Royani; Mrr. Lukie Trianawati
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 2 (2025): March 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/yq4pvb02

Abstract

This research focuses on determining the amount of tofu production based on the amount of consumer demand and the amount of raw material inventory. Optimization of daily tofu production is a difficult problem due to uncertainty of supply an demand for tofu. The method used in this research is the fuzzy logic method which is one of the effective rule-based approach methods to determine the volume of tofu production. In this research, the data used is taked based on the results of previous research. The final results obtained in this study, namely the determination of the volume of tofu production based on the amount of consumer demand and the amount of raw material inventory is still less effective. This is because the amount of consumer demand received and the amount of raw material inventory available with the volume of tofu production produced is still not appropriate
Implementation of Fuzzy Logic on Recommendation Levels of Packaged Milk Based on Price and Nutritional Value Qorie Rania; Chika Hayya Sabillah; Muhammad Faiz Assariy; Daffa Zulqisthi; Muhammad Afzaal Abimanyu; Anastasya Gabriella; Nurani Amaliatunnisa; Nurul Alfiani Dewi; Disty Isbiyanti Prananingrum; Aphisa Nahl Fitria; Mrr. Lukie Trianawati
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 3 (2025): June 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/5xmesg44

Abstract

The abundance of packaged milk products in the market requires consumers to consider several factors to obtain high-quality packaged milk at an affordable price. Milk demand in Indonesia showed a slight increase from 2019 to 2020, rising from 16.23 in 2019 to 16.27 in 2020. However, the average milk demand in Indonesia has remained fluctuating, largely due to the increasing prices of milk products on the market. This study aims to determine the recommendation level for packaged milk by considering both price and nutritional content. The method used in this research involves a mathematical assessment of milk products using fuzzy logic. The data for this study is derived from previous research on packaged milk samples as the observation objects. The results indicate that sample 16 is highly recommended due to its low price and very high nutritional content.
Application of Fuzzy Logic in Tempe Production Using the Tsukamoto Algorithm Daffa Zulqisthi; Muhammad Faiz Assariy; Mrr Lukie Trianawati; Syafira Aristawidya; Chandradewi Ekaputri; Hafizhah Nur Humairah; Gita Aisy Affatunnisa; Aliya Fidella; Muhammad Ghifari Fazan Putra; Chika Hayya Sabillah
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 4 (2025): September 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/aygmd359

Abstract

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.
APPLICATION OF FUZZY LOGIC TO DETERMINE DAMAGE LEVELS IN PASTEURIZED MILK BASED ON RAW MILK QUALITY Novianty Fauziyah; Chika Hayya Sabillah; Muhammad Faiz Assariy; Andity Indira Marchiana; Daffa Zulqisthi; Avril Berlian Dima; Nadya Nafilah; Diva Nurina Aurelia; Raissa Nelvandra Putri; Muchammad Adham Nugraha; Mrr. Lukie Trianawat
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 3 (2025): June 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/rvw0e797

Abstract

Milk is a highly nutritious food obtained from milking animals. One way to process milk so that it lasts a long time is by pasteurization. This study aims to develop a pasteurized milk damage level assessment system based on fuzzy logic based by considering factors such as temperature, storage time, pH, and the number of social cells. The method used in this study is a qualitative descriptive method with a literature study approach to collect secondary data from various relevant sources. The milk damage assessment system is designed using Fuzzy Inference System Mamdani, where each input variable is regulated by a trainee membership function. The results show that the system can provide a more accurate and adaptive assessment in determining the risk of milk damage, specified through the fuzzy rule evaluation designed for each combination of input conditions. This system is expected to support better decision making in maintaining the quality of pasteurization.
Implementation of Fuzzy Logic in Temperature Control Systems for Baking Ovens Andhika Rizky Maulana; Chika Hayya Sabillah; Muhammad Faiz Assariy; Daffa Zulqhisti; Rahadian Ilyasa Muhammad; Mutiara Ade Rosseta; Fairuz Kamilah Ihsan; Melati Afdizha; Cindy Novitasari; Azhar Nasywa Saputra; Mrr Lukie Trianawati
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 4 (2025): September 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/8y8g8f28

Abstract

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.
Computational Analysis of Mamdani Fuzzy Logic on Microcontrollers for Broiler Coop Microclimate Status Fathir Gunadireja; Ghina Rania; Revan Abdillah; Rhaqim Putra Alrusdi; Muhammad Faiz Assariy; Chika Hayya Sabillah; Rizki Achmad Rifa'i Dwi Warno
Journal of Applied Science, Technology & Humanities | JASTH Vol. 3 No. 3 (2026): June 2026
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/eraczj69

Abstract

This research investigates the critical necessity of microclimate regulation within broiler poultry housing by constructing a computational framework grounded in the Mamdani Fuzzy Inference System. Thermal fluctuations, relative humidity shifts, and ammonia accumulation are significantly correlated with poultry mortality rates. The proposed computational model acquires three input parameters (Temperature, Humidity, and Ammonia) to generate two decision variables (Fan Intensity and Coop Safety Status) through the evaluation of 27 logical rules. To ensure system reliability prior to hardware implementation on microcontrollers, the algorithm was validated using the MATLAB commercial simulator. The defuzzification process was executed utilizing the Center of Gravity (COG) approach, which was comparatively analyzed between theoretical mathematical calculations and software projections. The investigative results revealed a fundamental level of accuracy; manual computation recorded a value of 22.62, whereas the simulation instrument projected 22.60. The recorded margin of deviation was extremely reduced, standing at merely 0.088%. These findings confirm that the designed computational architecture is highly precise and strongly recommended for integration into Internet of Things (IoT) ecosystems for real-time agricultural automation.
Co-Authors Alifvia Nabila Cesarina Subekti Aliya Fidella Anastasya Gabriella Andhika Rizky Maulana Andity Indira Marchiana Annisa Pertiwi Hakim Annisa Royani Aphisa Nahl Fitria Arifa Fauzia Rahma Astrid Virta Ayu Alzahra Atikah Fahni Audrey Anastasia Silaen Avril Berlian Dima Azhar Nasywa Saputra Aziz Rabih Rabbani Bayu Adi Nugroho Chandradewi Ekaputri Cindy Novitasari Daffa Zulqhisti Daffa Zulqisthi Denisa Nurul Az Zahra Disty Isbiyanti Prananingrum Diva Nurina Aurelia Evy Apriliani Fairuz Kamilah Ihsan Fathir Gunadireja Febrina Disa Cinta Prasetyo Fildza Khairunida Ghazy Hassan Ghina Rania Gita Aisy Affatunnisa Hafizhah Nur Humairah Hilda Aulia Ainussyfa Hilda Fitria Hidayah Holy Nurani Rabbina Huwaida Asha Dhieva Iofema Malika Itsnaini Nur Rohmawati Jason Timoty Wijaya Kanaya Fatimah Madania Lola Amelia Mariati Melati Afdizha Mrr Lukie Trianawati Mrr. Lukie Trianawat Mrr. Lukie Trianawati Mrr.Lukie Trianawati Muchammad Adham Nugraha Muhammad Afzaal Abimanyu Muhammad Faiz Assariy Muhammad Ghifari Fazan Putra Muhammad Raihan Prasetya Muhammad Sulthan Alfriansyah Mutiara Ade Rosseta Nadya Nafilah Nazwa Khairunnisa Novianty Fauziyah Nur Syahla Fatimah Nurani Amaliatunnisa Nurul Alfiani Dewi Putri Nurhaliza Candra Qorie Rania Rahadian Ilyasa Muhammad Raissa Nelvandra Putri Revan Abdillah Rhaqim Putra Alrusdi Rifki Oktavia Riris Rahayu Rizki Achmad Rifa'i Dwi Warno Rizqi Hasna Amalia Salsabilla Kansa Ismail Setya Mega Bagaskara Shalinadira Koswara Siti Hasna Raihana Sri Diana Sari Syafira Aristawidya Taufan Taufan Putra ananta Vira Aulia Puteri Windy Fadhilah Aprilia