Naddiyanto, Muchammad Fadika (2026) REAL-TIME MONITORING SYSTEM FOR MOISTURE CONTENT OF PRE-ROASTED GREEN COFFEE BEANS USING IOT-BASED ANFIS METHOD. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
This study develops a real-time monitoring system for the moisture content of green coffee beans (pre-roasting) using an Internet of Things (IoT) approach based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. The system is built using an ESP32 microcontroller integrated with SHT31 sensors (temperature and relative humidity), an MH-Z19 sensor (CO₂), and a capacitive moisture sensor as environmental data inputs. Data are transmitted via the MQTT protocol to a monitoring dashboard, which is equipped with alert features such as LEDs, a buzzer, and Telegram notifications.The ANFIS model is employed to predict moisture content in a non-destructive manner and to detect indications of potential fungal growth. Validation is carried out using the oven drying method in accordance with the SNI 01-2907-2008 standard. The experimental results show that the moisture content prediction model achieves an accuracy of 98.082%, while the fungal indication detection model reaches an accuracy of 96.97%.All functional and non-functional testing results indicate that the system operates in a stable and responsive manner. This system offers an effective, efficient, and affordable solution as an alternative to conventional measurement tools, contributing to the improvement of coffee quality in Indonesia.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science | ||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | Muchammad Fadika Naddiyanto | ||||||||||||
| Date Deposited: | 21 May 2026 04:20 | ||||||||||||
| Last Modified: | 21 May 2026 05:29 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/52007 |
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