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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Reconfigurable and Embedded Systems (IJRES) TELKOMNIKA (Telecommunication Computing Electronics and Control) Telematika Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Jurnal Teknik Elektro dan Komputer TRIAC Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Informatika (JUTIF) JURNAL ABDIKARYASAKTI RENATA Jurnal Pengabdian Masyarakat Kita Semua Molekul: Jurnal Ilmiah Kimia
Retno Supriyanti
Jenderal Soedirman University
Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Other

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Design of mobile application for communication and user interface of ESP32 potentiostat system Supriyanti, Retno; Widanarto, Wahyu; Dwi Susanto, Putra; Ardi Wicaksono, Madya; Rais Akhdan, Syafrudin; Alqaaf, Muhammad
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 3: November 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i3.pp725-733

Abstract

The potentiostat utilizing the ESP32 has a 12-bit analog-to-digital converter (ADC), meaning the maximum value for ADC voltage readings on the ESP32 is 4095. These ADC readings are then converted into actual voltage units, ensuring more accurate measurements on the potentiostat. To facilitate the use of the ESP32 potentiostat, a mobile application must be designed as a user interface for data communication. The application will be developed on a mobile platform using a Bluetooth low energy (BLE) communication channel for easier access. The development process will utilize visual studio code as the code editor and programming languages like Dart and Flutter. The resulting application will feature a user-friendly dashboard, display data in a cyclic voltammetry graph, and store data in comma-separated values (CSV) files or images in the phone’s memory. This stored data will simplify observing results obtained from the ESP32 potentiostat.
Enhanced Microwave Absorbing Characteristics of Cerium Barium Ferrite Composite: Effect of Sintering Temperature Variation Widanarto, Wahyu; Tamtowi, Tomy; Effendi, Mukhtar; Rahmawati, Dina; Supriyanti, Retno; Ghoshal, Sib Krishna; Kurniawan, Candra; Jatmika, Jumaeda; Handoko, Erfan; Umar, Lazuardi; Alaydrus, Mudrik
Molekul Vol 20 No 3 (2025)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jm.2025.20.3.17825

Abstract

ABSTRACT. Cerium barium ferrite composites (CeBFCs) with improved microwave absorbance in the X-band spectral region are advantageous for varied advanced applications. Thus, the influence of various sintering temperatures on the microwave-absorbing traits of CeBFCs was evaluated. The main objective was to enhance the selective microwave absorption of BFC by modifying its magnetic properties through the substitution of Fe³⁺ with Ce³⁺ in the lattice structures. Four composites of CeBF were synthesized via mechanical alloying and sintered at 600, 800, 1000, and 1100°C. The produced samples were analyzed using XRD, VSM, and VNA to determine their microstructures, magnetic properties, and microwave reflection loss at X-band frequencies. XRD results revealed a significant promotion in forming a more pure crystalline barium hexaferrite phase at sintering temperatures higher than 800°C. This structural enhancement could directly influence the magnetic properties of the specimens with a progressive increase in the saturation magnetization with rising sintering temperature. In addition, the sintering temperature variation effectively modulated the electromagnetic properties (complex relative permeability and permittivity) that are vital for impedance matching and optimal wave absorption. The composite sintered at 1000°C displayed an optimal microwave absorption, indicating the lowest reflection loss within the X-band. The obtained products were shown to attenuate and dissipate surplus electromagnetic energy within the 8-12 GHz frequency range. The observed superior performance of the composites was ascribed to a balanced interplay between the magnetic and dielectric losses, leading to efficient impedance matching. It was affirmed that careful tuning of the sintering temperature can improve the crystalline phases, magnetic, electromagnetic, and microwave absorption properties of the proposed CeBFCs. Keywords: Cerium barium ferrite, Microwave absorption, Reflection loss, Sintering temperature, X-band
Mobile application for diagnosing alzheimer's based on clinical dementia rating Supriyanti, Retno; Putra Yubiksana, Muhammad; Mahardika Wijonarko, Bintang Abelian; Ramadhani, Yogi; Syaiful Aliim, Muhammad; Irham Akbar, Mohammad; Budi Widodo, Haris; Widanarto, Wahyu; Alqaaf, Muhammad
Indonesian Journal of Electrical Engineering and Computer Science Vol 40, No 3: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v40.i3.pp1607-1617

Abstract

Alzheimer's is a neurodegenerative disease characterized by memory loss, impaired thinking abilities, and changes in behavior. It is the most common form of dementia, significantly affecting a person's ability to carry out daily activities. Statistics indicate that the number of individuals suffering from Alzheimer's worldwide continues to rise as the population ages. Diagnosing Alzheimer's is a complex process that typically requires a skilled medical team. One diagnostic tool that can be utilized is an MRI machine. Previous research focused on extracting features from MRI images taken from three different cross-sections: axial, coronal, and sagittal. Based on these three types of cross-sectional images, we developed a system to classify the severity of Alzheimer's. This paper focuses on creating an Alzheimer's classification system accessible through a mobile application. The results indicate that our system has a performance accuracy of 90% in classifying the severity of the disease.
Deep learning-based cervical cancer detection via colposcopy images integrated into an Android mobile application Supriyanti, Retno; Anzil, Arsil Kultura; Ramadhani, Yogi; Suroso, Suroso; Widanarto, Wahyu; Alqaaf, Muhammad; Dwi Hapsari, Kartika; Diana Kartika, Futiat
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp338-349

Abstract

Cervical cancer is a form of cancer that develops in the cells of the cervix, the lower part of the uterus that connects the uterus to the vagina. Early detection is essential for improving the chances of recovery from cervical cancer. One method for early detection is colposcopy image analysis, a medical procedure that examines the cervix and captures images for evaluation. These images were analyzed to observe color changes after the visual inspection with acetic acid (VIA) process. However, this analysis requires experienced and specially trained medical personnel. To address this challenge, a system that can automatically classify cervical cancer images is needed. Therefore, researchers proposed designing and developing an Android mobile application to enable early detection of cervical cancer using the convolutional neural network (CNN) algorithm. The CNN model was tested using test data to evaluate its performance. The optimized CNN model utilizing the ResNet50 architecture achieved 86% test accuracy, 85% precision, and 87% recall. The test results indicate that the model's accuracy is consistent before and after its implementation on the mobile application, confirming the effectiveness of both the model and its implementation as diagnostic tools.
Co-Authors Ahmad Fariz Akbar, Mohammad Irham Akbar, Muhammad Irham Alfin Chrisanty Aliim, M. Syaiful Alqaaf, Muhammad Anugerah Kevin Marchel Anzil, Arsil Kultura Ardi Wicaksono, Madya Ari Fadli Ariep Soelaiman Setiadi Aryanto, Andreas S. Candra Kurniawan Diana Kartika, Futiat Dina Rahmawati Dita Dayu AW Dwi Hapsari, Kartika Dwi Susanto, Putra Eko Murdyantoro Elvin Pranata Eman Sutrisna Erfan Handoko Fadlola, M. Gus Solhan Fibra R. Firmanda Ghoshal, Sib Krishna Hari Siswantoro, Hari Haris B. Widodo Haris Budi Widodo Haris Budi Widodo Haris Budi Widodo Haris Budi Widodo, Haris Icuk Rangga Bawono, Icuk Rangga Irham Akbar, Mohammad Jatmika, Jumaeda Lazuardi Umar Mahardika Wijonarko, Bintang Abelian Mudrik Alaydrus Muhammad Alqaaf Muhammad Alqaaf Muhammad Rifqi Kurniawan Muhammad Syaiful Aliim Mukhtar Effendi Pangestu F. Wibowo Putra Yubiksana, Muhammad Rais Akhdan, Syafrudin Rifda Naufalin Riyanto, Arif Pujo Rumpoko Wicaksono Subkhi Adhi Priyono Suroso Suroso Suwitno Suwitno Syadzwina Luke Dzihniza Tamtowi, Tomy Teddy Septiana Trishardian, Rachmat Tutik Ida Rosanti Wahyu Siswandari Wahyu Widanarto, Wahyu Winasis Winasis Yogi Ramadhani Yogi Ramadhani Yogi Ramadhani