Joyopranoto, Vincensius Agung Wibowo
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Penerapan Metode Komparasi Probabilitas Penentuan Penyakit Jantung Joyopranoto, Vincensius Agung Wibowo; Rahardjo, Mikha El Charisto; Baraga, Bernaditus Yordan; Candrasari Hermanto, Diwahana Mutiara
Joined Journal (Journal of Informatics Education) Vol 7 No 1 (2024): Volume 7 Nomor 1 (2024)
Publisher : Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31331/joined.v7i1.3108

Abstract

Heart disease, a major global cause of mortality, necessitates a swift and precise diagnostic approach for effective prevention and management. In the era of information technology, probabilistic comparison methods such as Naïve Bayes and KNN offer a fresh perspective on assessing the risk and diagnosis of heart disease. This research, based on a dataset of 300 records with 14 attributes indicating the presence of heart disease, implements and compares these algorithms. The study reveals that Naïve Bayes, with or without normalization, achieves an accuracy of 92.67%, while normalized KNN outperforms with 93.33% accuracy, compared to 79.33% without normalization. Conclusively, the study supports the significant potential of probabilistic data analysis methods, emphasizing the integration of these techniques in the healthcare system for more accurate risk classification, early detection, and efficient management of heart disease.
Kalibrasi dan Validasi Sensor pH E-201C-Blue dan TDS Meter V1 pada Sistem Hidroponik Otomatis Berbasis IoT di Aswana Hidroponik Rahardjo, Mikha El Charisto; Baraga, Bernaditus Yordan; Joyopranoto, Vincensius Agung Wibowo; Mahendra, Christy
Prosiding Seminar Nasional Teknoka Vol 10 (2025): Proceeding of TEKNOKA National Seminar - 10
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

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Abstract

This study aims to calibrate and validate the pH E-201C-Blue sensor and TDS Meter V1 implemented in an IoT-based automatic hydroponic system at Aswana Hydroponic, Purwokerto. The calibration process was carried out using a multi-point method with standard buffer solutions (pH 4, 7, and 10) and TDS solutions ranging from 500 to 1500 ppm to achieve optimal accuracy. An ESP32 microcontroller was used as the main controller and data transmitter to a cloud-based monitoring dashboard. The results showed that after calibration, the sensor achieved high accuracy with a correlation coefficient (R2) above 0.98 and an average error below 5%. These findings indicate that low-cost commercial sensors can provide reliable performance in automated hydroponic system, supporting time efficiency and improving crop productivity at Aswana Hydroponic, Purwokerto.
Otomatisasi Pengatur pH dan Nutrisi pada Tanaman Hidroponik Berbasis Internet of Things di Aswana Hidroponik Joyopranoto, Vincensius Agung Wibowo; Baraga, Bernaditus Yordan; Rahardjo, Mikha El Charisto; Mahendra, Christy; Lianawati, Yosita
Prosiding Seminar Nasional Teknoka Vol 10 (2025): Proceeding of TEKNOKA National Seminar - 10
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study discusses the design of an automated pH and nutrient control system for hydroponic plants based on the Internet of Things (IoT). The objective of this study to develop a system capable of reading solution conditions and sending data in real time through an IoT platform to facilitate monitoring without manual intervention. The system is designed using an ESP32 microcontroller as the control center, a pH sensor, a TDS meter sensor, and a peristaltic pump for the solution injection process. The sensor reading data is sent to the IoT server using the Blynk platform. The test results show that system is capable of sending valid and consistent pH and TDS data to the Blynk dashboard with an accuracy level ±98%, making it easier for users to monitor the condition of the nutrient solution remotely. This research is the first step towards an efficient and integrated automatic hydroponic control system.