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Nanda Octavia
College of Vocational Studies, IPB University
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Social Sciences

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Journal : journal of applied science technology

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Chicken Egg Hatching Optimization with Automatic Control Using Fuzzy Logic Desita Auliafitri; Erry RizkySuro; Tedi Kurniawan; Muhammad Danang Mukti Darmawan; Fiqri Nurfadillah; Nanda Octavia
Journal of Applied Science, Technology & Humanities | JASTH Vol. 1 No. 3 (2024): June 2024
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/0m1ks522

Abstract

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.
Prediction on Target of Underprivileged Scholarships Using Fuzzy Logic Method Afifah Rodhiyatun Nisa; Daffa Adrian Ahmadi Tondang; Fauzan Perdana Ilham; Ghani Trie Aqeela Ramadhani; Muhammad Danang Mukti; Fiqri Nurfadillah; Nanda Octavia
Journal of Applied Science, Technology & Humanities | JASTH Vol. 1 No. 2 (2024): March 2024
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/4bg52465

Abstract

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.
Implementation and Comparison of Coffee Bean Drying Temperature SettingsBased on Fuzzy Logic Mohammad Ghassan Alghifari; Indah Suraswati; Kenji Restan Syahuri; David Zico Rafael Sitorus; Kevin Viriya Halim; Inna Novianty; Nanda Octavia; Ivan De Nerol
Journal of Applied Science, Technology & Humanities | JASTH Vol. 1 No. 5 (2024): November 2024
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/cj817x36

Abstract

This research examines the implementation and measurement of temperature in drying coffee beansusing a fuzzy logic approach. Two main methods, namely the Mamdani Method and the SugenoMethod, were applied and evaluated in this context. Data on temperature, humidity, and water contentof coffee beans are collected during the drying process for use in the implementation of both methods.Implementation is carried out using MATLAB software, with detailed steps for each method. TheMamdani method involves fuzzification processes, inference using fuzzy rules, and defuzzification toobtain concrete values for temperature settings. Meanwhile, the Sugeno Method also involvesfuzzification of input data, but uses a linear fuzzy model for inference, so it does not require adefuzzification stage. The results and discussion of this study highlight the performance differencesbetween the two methods. Evaluation is carried out based on temperature prediction accuracy andenergy efficiency. The Mamdani Method shows good accuracy in predicting temperature, while theSugeno Method highlights efficiency and efficiency in the temperature regulation process. Therefore,this study provides valuable insight into selecting a suitable method for temperature regulation ofcoffee bean dryers
Co-Authors Afifah Rodhiyatun Nisa Daffa Adrian Ahmadi Tondang David Zico Rafael Sitorus Desita Auliafitri Erry RizkySuro Fauzan Perdana Ilham Fiqri Nurfadillah Ghani Trie Aqeela Ramadhani Indah Suraswati Inna Novianty Ivan De Nerol Kenji Restan Syahuri Kevin Viriya Halim Mohammad Ghassan Alghifari Muhammad Danang Mukti Muhammad Danang Mukti Darmawan Tedi Kurniawan