Article Per Year (5 Year)
p-Index From 2021 - 2026
0.778
P-Index
This Author published in this journals
All Journal PROtek : Jurnal Ilmiah Teknik Elektro bit-Tech Devotion: Journal of Research and Community Service
Juju Juhaeriyah
University Of Swadaya Gunung Jati
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
RANCANG BANGUN HEALTH MONITORING SYSTEM BERBASIS INTERNET OF THINGS (IoT): ESP8266 DAN BLYNK Juju Juhaeriyah; Edo Agung N; Rindi Wulandari
bit-Tech Vol. 6 No. 2 (2023): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v6i2.1036

Abstract

Health monitoring is important for living creatures. There are many things that are important factors in the health of living creatures, especially humans, including heart rate, body temperature and oxygen saturation. IoT technology is very helpful in the development of health technology so that it becomes possible to monitor patient health in real time and patient emergency information can be accessed easily. This research also aims to design an Android-based heart rate monitoring system using ESP8266 as a microcontroller. The sensor used is Max30102. The research method used is applied research, with experimental research methods. The research stages carried out were literature study, software design, hardware design, system testing, and analysis. The results of the research are the design of a patient health monitoring tool with three measured indicators, namely the patient's heart rate, body temperature and oxygen levels. The system can monitor in real time based on Internet of Things and can be accessed by Android and iOS. From the study results, it was found that the Android-based health monitoring system has an accuracy rate of 97.63% and it can be said that the system can be used for patient measurements. With details, 96.71% is the accuracy level for measuring heart rate, 96.45% accuracy level for measuring oxygen levels in the patient's body, and 99.75% accuracy level for measuring patient temperature.
A Comparative Analysis of Sugeno and Tsukamoto Fuzzy Logic for Temperature Stability in SCAMIS Hidayat, Rizky Nugraha; Idris, Fahmi; Juhaeriyah, Juju
PROtek : Jurnal Ilmiah Teknik Elektro Vol 12, No 3 (2025): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v12i3.10514

Abstract

The digital poultry sector faces challenges in maintaining stable incubation temperatures. Comparative evaluation between Sugeno and Tsukamoto methods has not been conducted in real-world IoT systems. This research is essential to identify the most effective fuzzy logic control approach for smart incubators. This study aims to compare the effectiveness of Sugeno and Tsukamoto fuzzy logic methods through implementation in the SCAMIS platform. A comparative experimental design was employed using Sugeno and Tsukamoto models in SCAMIS. Temperature data were collected via DHT22 sensors and analyzed quantitatively. Code validation and sensor accuracy tests ensured data reliability and the credibility of fuzzy decision-making processes. The accuracy level of the DHT22 sensor when detecting temperature is 98.31%. The comparison of response time from initial temperature to target temperature (30°C - 38°C) between the Tsukamoto and Sugeno fuzzy logic methods is 1 : 3. Tsukamoto takes 1 hour 52 seconds (3,652 seconds), while Sugeno takes 3 hours 1 second (10,801 seconds). The response time required by Tsukamoto for each 1°C temperature increase is 1–7.5 minutes, while Sugeno is 1–10.3 minutes. However, in terms of temperature stability, Sugeno is more stable with an accuracy rate of 98.40% approaching the target temperature, while Tsukamoto has an accuracy rate of 96.93%. These results indicate a significant trade-off between the speed of reaching the target temperature and stability at the target temperature. Control method selection should align with specific operational priorities in smart incubation systems. These findings recommend choosing fuzzy methods based on system priorities. Future studies should evaluate energy consumption and hatching success efficiency.
Design and Build an Internet of Things (IoT) Based Wastewater Monitoring System at Cirebon Pelabuhan Hospital Muhaimin, Muhammad; Dony, Abdul Rochman; Juhaeriyah , Juju
Devotion : Journal of Research and Community Service Vol. 6 No. 9 (2025): Devotion: Journal of Community Research
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/devotion.v6i9.25539

Abstract

Wastewater at the Cirebon City Port Hospital that is not treated properly can cause environmental damage. In this case, technological advances are very rapidly developing in the manufacture of sophisticated tools, namely tools that can work automatically and have high precision. Therefore, in this study, we will conduct a prototype for monitoring the Wastewater Management Installation (WWTP), so hereby the author develops his research by directly applying the Wastewater Management Installation (WWTP) at Cirebon Port Hospital. In this prototype we used an esp 8266 microcontroller to read commands, a turbidity sensor to measure water turbidity, a DS18B20 sensor to measure the temperature of the water, a pH sensor to measure the acidity level of the water and an MIT App to read the output that is read by the sensor input that has been read by the firebase in real-time. The calibration results showed that all sensors were able to read the values with fairly good accuracy. The pH sensor shows an average accuracy of about 97.8%. The turbidity sensor shows an average accuracy of about 97.1%. The temperature sensor DS18B20 shows an average accuracy of about 97.7%. In the test results of the samples from the 4 readings in tubs 1 to 3, an error was shown because the results of the turbidity sensor reading were above 30 because the 1 to 3 tubs had not been filtered.
Co-Authors Ariwibowo, Muhamad Riyad Dony, Abdul Rochman Edo Agung N Hidayat, Rizky Nugraha Idris, Fahmi Muhammad Muhaimin Mutaqim, Rendi Nugroho, Edo Agung Rindi Wulandari