Rancang Bangun Fermentor Berbasis Artificial Neural Network Untuk Sistem Monitoring Kesehatan Bakteri Pada Proses Fermentasi

Satriya, Khaithrileya Arethaputri (2025) Rancang Bangun Fermentor Berbasis Artificial Neural Network Untuk Sistem Monitoring Kesehatan Bakteri Pada Proses Fermentasi. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 2042211066-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (5MB) | Request a copy

Abstract

Fermentasi biji kakao merupakan proses penting yang mempengaruhi kualitas dan rasa akhir cokelat sesuai dengan standar mutu biji kakao berdasarkan SNI 2323-2008. Pada penelitian ini, dirancang sebuah fermentor berbasis Artificial Neural Network (ANN) untuk sistem monitoring kesehatan bakteri selama proses fermentasi biji kakao. Sistem memanfaatkan sensor untuk mengukur parameter penting seperti pH, temperature, dan kelembaban yang mempengaruhi kondisi bakteri pada saat fermentasi. Ketiga parameter tersebut bertujuan untuk memenuhi standar mutu biji kakao dengan memiliki pH 4-4,5, temperature ideal 30-45°C dan kelembaban relatif ruang simpan 75%. Data yang dikumpulkan kemudian diolah menggunakan ANN untuk memprediksi dan mengklasifikasikan kesehatan bakteri. Algoritma yang digunakan salah satunya adalah Backpropagation Neural Network (BPNN). Tujuan utama dari sistem ini adalah untuk mengoptimalkan proses fermentasi dengan memantau dan mengontrol kondisi yang ideal bagi perkembangan bakteri yang mendukung fermentasi. Akurasi Artificial Neural Network (ANN) yang didapatkan 68.85%, precission sebesar 95.29%, recall sebesar 70.43%, specifity sebesar 42.8%, dan F1-score sebesar 80.99%.
========================================================================================================================================
Fermentation of cocoa beans is an important process that affects the quality and final flavor of chocolate in accordance with the quality standards of cocoa beans based on SNI 2323-2008. In this research, an Artificial Neural Network (ANN) based fermenter was designed for bacteria health monitoring system during the fermentation process of cocoa beans. The system utilizes sensors to measure important parameters such as pH, temperature, and humidity that affect the condition of bacteria during fermentation. These three parameters aim to meet the quality standards of cocoa beans with an ideal temperature of 30-45°C, a pH of 4-4.5, and a relative humidity of 75%. The data collected is then processed using ANN to predict and classify bacterial health. One of the algorithms used is Backpropagation Neural Network (BPNN). The main objective of this system is to optimize the fermentation process by monitoring and controlling the ideal conditions for the development of bacteria that support fermentation. The Artificial Neural Network (ANN) accuracy obtained was 68.85%, precission was 95.29%, recall was 70.43%, specifity was 42.8%, and F1-score was 80.99%

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Artificial Neural Network, Fermentasi, pH, Temperature, Kelembaban. Artificial Neural Network, Fermentation, pH, Temperature, Humidity.
Subjects:	T Technology > T Technology (General) T Technology > T Technology (General) > T57.62 Simulation T Technology > T Technology (General) > T57.74 Linear programming T Technology > T Technology (General) > T57.8 Nonlinear programming. Support vector machine. Wavelets. Hidden Markov models.
Divisions:	Faculty of Vocational > Instrumentation Engineering
Depositing User:	Khaithrileya Arethaputri Satriya
Date Deposited:	31 Jul 2025 07:32
Last Modified:	31 Jul 2025 07:32
URI:	http://repository.its.ac.id/id/eprint/124278

Actions (login required)

View Item