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All Journal JETT (Jurnal Elektro dan Telekomunikasi Terapan) JEECAE (Journal of Electrical, Electronics, Control, and Automotive Engineering) Specta Journal of Technology Jurnal Teknik Elektro dan Komputasi (ELKOM) PIKAT
Barokatun Hasanah, Barokatun
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Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Energy Engineering Environmental Science Mechanical Engineering Other

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Journal : Specta Journal of Technology

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State Of Charge Estimation on Lithium ION Batteries Using Quantum Neural Network Situmorang, Raftonado; Dewanto, Muhammad Ridho; Hasanah, Barokatun; Deliasgarin, Kholiq; Oktafian, Bagus Gilang
SPECTA Journal of Technology Vol. 9 No. 2 (2025): Specta Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v9i2.1305

Abstract

Battery applications can be found in electric vehicles, renewable energy power plants and various other portable devices. In this final project research, the author uses the Quantum Neural Network (QNN) method to estimate the State of Charge (SoC) on a lithium-ion battery designed using PYTHON. This research includes the design of a prototype SoC estimation system on lithium-ion batteries using the QNN method, real-time SoC data collection, and comparison of SoC estimation performance using QNN with real-time data. The results of real-time testing of lithium-ion batteries using ACS712 voltage and current sensors for five cycles show the following voltage results: first cycle 10.70 V to 12.68 V, second cycle 10.56 V to 12.66 V, third cycle 10.60 V to 12.69 V, fourth cycle 10.60 V to 12.00 V, and the fifth cycle 10.41 V to 12.07 V. Meanwhile, the current sensor results for five cycles showed a range of 0.1 A to 0.5 A. Each test result per cycle showed a higher increase, although there were small fluctuations, and the overall trend line showed the consistency of the voltage sensor's performance without significant degradation during repeated tests, indicating good stability of the voltage sensor. Then, methods with qubit rotation, linear entanglement, and Neural Network were tested. SoC prediction results using QNN with qubit rotation showed MAPE and RMSE values of 0.14 and 61%, respectively. Furthermore, testing the SoC prediction results on QNN with linear entanglement shows MAPE and RMSE values of 0.08 and 29%, respectively. While the SoC prediction results.
Sistem Monitoring Air Conditioner (AC) Pada Ruang Kelas Institut Teknologi Kalimantan Berbasis Internet of Things (IoT): Sistem Monitoring Air Conditioner (AC) Pada Ruang Kelas Institut Teknologi Kalimantan Berbasis Internet of Things (IoT) Utami, Amalia Rizqi; Hasanah, Barokatun; Firsen, Muhammad Iqbal Sep; Fikri, Ryan
SPECTA Journal of Technology Vol. 10 No. 1 (2026): Specta Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v10i1.1018

Abstract

This research discusses the implementation of a monitoring system based on Internet of Things (IoT) technology to monitor air conditioning usage in the form of a website. This system is designed to collect data about air conditioner usage in real time and monitor the on/off conditions of the air conditioner. Several components are used such as the DHT11 module as a temperature sensor which functions to read room temperature, the PZEM- 004t module which functions to read voltage, current and power which operates on AC when it is off or on, the Arduino UNO microcontroller to process input/output data, ESP8266 for connecting to a wi-fi network. In addition, software is used to support the research process such as Arduino to program the Arduino UNO microcontroller, XAMPP to create a database, and Visual Studio Code to create programs on websites. In this study, there are several stages such as analysis of user needs, system design, system testing, data analysis, and conclusions. Then after testing and data collection, the current and power values were obtained when the AC was off, namely 0.4 A and 1.7 Watt – 1.8 Watt. When the AC is on, the current and power values are 1.08 A – 1.19 A and the power is 216.8 Watt – 244.6 Watt.
Co-Authors Anifah, Eka Masrifatus Aprillia, Happy Basransyah, Basransyah Deliasgarin, Kholiq Dewanto, Muhammad Ridho Fatimatuz Zahrah, Annisa Felecya Sitinjak, Joyce Firsen, Muhammad Iqbal Sep Fitriyani, Risma Haqqi, M Hibatul Harun, Rayna Fitra Khairunnisa Ariani, Ismi Marliana, Nanda Martin Sinambela, Johannes Medianto, Felix Na’Im, Andiko Oktafian, Bagus Gilang Puspita Sari Rachman, Dendy Januari Ramadhani, Riski Saskia Rika P, Prasetyan Riza Hudayarizka Rozul Faza, Muhammad Ryan Fikri Saroh Qarini, Ayuk Situmorang, Raftonado Slamet . Utami, Amalia Rizqi Vicky Andria Kusuma Wahyu Yusariarta Putra Parmita, Ade Wibisono, Adam Ashabil