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All Journal Jurnal Teliska Jupiter Elkom: Jurnal Elektronika dan Komputer PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Annual Research Seminar JETT (Jurnal Elektro dan Telekomunikasi Terapan) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING AMALIAH: JURNAL PENGABDIAN KEPADA MASYARAKAT Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Jurnal Digit : Digital of Information Technology Journal of Technology and Informatics (JoTI) Arcitech: Journal of Computer Science and Artificial Intelligence Bulletin of Network Engineer and Informatics (BUFNETS) CSRID
Aryanti Aryanti
Politeknik Negeri Sriwijaya
Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering

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SMARTBAND TRACKER UNTUK ANAK USIA DIBAWAH 6 TAHUN MENGGUNAKAN WEMOS D1 DENGAN MONITORING MELALUI SMARTPHONE Dhea Syafitri; Aryanti Aryanti; Muhammad Zakuan Agung
JURNAL TELISKA Vol 18 No III (2025): TELISKA November 2025
Publisher : Teknik Elektro Polsri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.17761317

Abstract

Smartband tracker is designed to monitor the child's location directly through the blynk application on the smartphone. To make this smartband requires several components, namely the Wemos D1 Mini as the brain center of the smartband control device, GPS is used to determine the position point of the child's whereabouts, the battery functions as a power supply so that the smartband can operate independently, the Battery Mangament System functions as a backup battery life and the Switch is used as an On / Off button. This tool works in a way, if the red LED flashes it means the GPS has obtained a coordinate point where the results can be seen in the blynk application which can display the location point of the child's whereabouts, displaying coordinate points such as latitude, longitude, and speed. In this study, testing was carried out at 5 location points. The results of the study showed that speed variations were greatly influenced by the duration and intensity of movement, not only by the distance traveled. High speed is recorded at short distances when fast movement occurs, namely point 1 to point 6, while low speed occurs even though the distance is long, when the movement is slow, namely at point 1 to point 5. After testing the tool, the results show that the smartband can work well and can determine the location point in real-time and the advantage of this tool is that it has a buzzer feature that can be turned on via the blynk application on the smartphone where this buzzer will make a sound when activated. Key words : Smartband, IoT, Wemos D1, GPS Tracker, Children, Smartphone, Monitoring
ANALISIS ARUS DAN TEGANGAN PADA RANGKAIAN KOMBINASI MENGGUNAKAN SIMULATOR LIVEWIRE Jonathan Farrel Akbar; Noval Resti Ardiansyah; Kayla Luna Pasha; Aryanti Aryanti
JURNAL TELISKA Vol 18 No III (2025): TELISKA November 2025
Publisher : Teknik Elektro Polsri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.17761213

Abstract

This article discusses the use of LiveWire software as an interactive simulation medium for analyzing current and voltage in mixed resistor circuits, which are a combination of series and parallel circuits. This study aims to demonstrate how LiveWire can be used as a learning tool to understand basic electrical concepts more effectively and efficiently. Through digital simulation, users can accurately observe the distribution of current, voltage, and power in each resistor without the need for physical measuring instruments in the laboratory. The simulation results are then compared with theoretical calculations based on Ohm's Law, showing a very high degree of conformity with insignificant differences in values. This proves that LiveWire is capable of representing the behavior of electrical circuits realistically. In addition to simplifying the design and analysis process, the use of LiveWire also improves practitioners' understanding of the relationship between current, voltage, and resistance. Thus, LiveWire can be used as an interactive, safe, and efficient digital learning medium to support electronics practicum activities.
SIMULASI RANGKAIAN PENYEARAH SETENGAH GELOMBANG MENGGUNAKAN LIVEWIRE Aryanti Aryanti; Clara Alcahya Palpa; Dimas Iqbal Fahrozy; M.Nabil Ar-Rassya; Nadya Aprilia
JURNAL TELISKA Vol 18 No III (2025): TELISKA November 2025
Publisher : Teknik Elektro Polsri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.17761390

Abstract

This study discusses the design and analysis of a half-wave rectifier circuit using the LiveWire Circuit application as a simulation medium. The main objective of this research is to understand the working principle of the diode as a rectifying component and to analyze the waveform and output characteristics produced through simulation. The circuit consists of an AC voltage source, a step-down transformer, a 1N4007 silicon diode, and a 1 kΩ load resistor. The simulation results show that the diode conducts current only during the positive half-cycle of the AC signal and blocks current flow during the negative half-cycle, thus producing a pulsating direct current (DC) output. The average DC voltage obtained from the simulation is 0.32 V, which is close to the theoretical value of 0.318 V, with a rectification efficiency of 40.6%. These findings demonstrate that the LiveWire application effectively represents circuit characteristics and provides real-time waveform visualization. The use of simulation through LiveWire not only enhances the understanding of basic electronics concepts but also offers a practical learning approach without requiring physical circuit assembly, making it an efficient educational tool for analyzing half-wave rectifier performance.
Machine Learning for Classifying Priority Areas for School Infrastructure Improvement Funding Aryanti Aryanti; Nurul Mardhiyah; Aulia Syafitri; Muhammad Ghalib; Nabil Alrofi
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 10 No. 1 (2026): Issues July 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v10i1.17789

Abstract

Equitable funding for school infrastructure is often hampered by subjective evaluation methods that lead to inappropriate prioritization. This study develops a data-driven approach that uses machine learning to objectively classify funding priority areas. Using the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework and data from the Indonesian Ministry of Education, a support vector regression (SVR) model with an RBF kernel is developed. This model integrates key facility indicators including laboratory availability, sanitation, and access to utilities to predict infrastructure adequacy. Separate models were built for public and private secondary schools with a 70:15:15 data split. The results demonstrated excellent predictive accuracy, with an R² of 0.9938 for public schools and 0.9969 for private schools, at a minimal error rate (MAE <0.20). By grouping the regression results into priority categories, the model successfully identified twenty high-priority areas that require immediate intervention by 2024. These results demonstrate that the SVR-based framework provides a robust decision support system, enabling policymakers to allocate infrastructure funds more transparently, equitably, and in direct alignment with empirical realities on the ground.
Sosialisasi Aplikasi Mobile Untuk Sistem Antrian Pada Puskesmas Sako Kota Palembang Nurhajar Anugraha; Aryanti Aryanti; Dyah Utari Yusa Wardhani; Pertiwi Nurul Utami; Imas Ning Zhafarina; Muhammad Hanif Fatin; Diah Novita Sari; Yulia Hapsari; Adhelia Febriasari Harahap
Amaliah: Jurnal Pengabdian Kepada Masyarakat Vol 9 No 1 (2025): Amaliah Jurnal: Pengabdian kepada Masyarakat
Publisher : LPPI UMN AL WASHLIYAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32696/ajpkm.v9i1.4545

Abstract

This Community Service Activity aims to provide knowledge about mobile applications for queuing systems that are expected to make it easier for patients who will check their health or seek treatment at the Health Center. The methods used in this activity include interview methods with the Health Center to find out the source of the problem that is the basis for this community service activity. Furthermore, a socialization method is carried out, where in this socialization activity an explanation will be given to both the Health Center and patients about the use of the application that will be designed. The results of this activity are socialization regarding the Mobile application for the patient queuing system along with socialization of the procedures for using the application. Where after the implementation of this activity is carried out, the application that will be designed will make it easier for patients and patients no longer need to sit and queue for a long time when going to the Sako Health Center for treatment.
Yagi-Uda Antennas for Private LTE Band 3 FDD: Simulation, Fabrication, and Measurement Muhammad Rizko Justiano; Aryanti Aryanti; Mohammad Fadhli
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 2 (2026): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i2.4168

Abstract

Private LTE Band 3 Frequency Division Duplex (FDD) systems require dedicated uplink and downlink antennas to improve channel isolation and communication reliability. However, experimentally validated split-frequency Yagi-Uda antennas for Software Defined Radio (SDR)-based base stations remain limited. This study presents the design, simulation, fabrication, and experimental validation of two four-element Yagi-Uda antennas operating at 1.840 GHz for downlink (DL) and 1.750 GHz for uplink (UL). Each antenna consists of one reflector, one driven element, and two directors fabricated from 6 mm diameter aluminum rods. The antenna dimensions were optimized using the Trust Region Framework in CST Studio Suite 2024 to achieve optimal impedance matching. Simulation results produced S11 values of −35.33 dB (DL) and −30.76 dB (UL), VSWR values of 1.035 and 1.059, and forward gains of 9.10 dBi and 8.38 dBi, respectively. Measurements using a NanoVNA over the 1.4–2.1 GHz frequency range yielded S11 values of −18.98 dB (DL) and −26.92 dB (UL), with corresponding VSWR values of 1.253 and 1.094. The measured resonant frequencies closely agreed with the simulation results, with a maximum deviation of only 1 MHz. The novelty of this work lies in the experimental validation of a low-cost, split-frequency, four-element aluminum-rod Yagi-Uda antenna pair that operates without an external impedance-matching network. These results demonstrate the suitability of the proposed antennas for SDR-based Private LTE Band 3 base station applications.
Sistem Pengenalan Wajah Real-Time Menggunakan YOLOv7 untuk Akses Gedung TVRI Palembang Berbasis Web Fatia Salsabilla Kyara; Aryanti Aryanti; R.A. Halimatussa&#039;diyah
Journal of Technology and Informatics (JoTI) Vol. 7 No. 2 (2025): Vol. 7 N. 2 (2025)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v7i2.1063

Abstract

The development of information and communication technology today has had a significant impact on various aspects of life, including in the field of security. The use of face recognition is one of the facial recognition techniques, where the results of the camera capture will be matched with photos or facial curve textures that already exist in the database. The system is widely applied using various methods and artificial intelligence, one of which is YOLO (You Only Look Once). The purpose of this study is to design, develop, and identify challenges in implementing a real-time facial recognition system using web-based YOLOv7 that can detect the faces of people entering the TVRI Palembang building, then photos and times when a person's face is not detected will be stored in the database. The data used comes from literature studies, data collection obtained from photos of TVRI television station employees' faces, software design with technology selection, user interface design, and algorithm structures that will be used. After going through these stages, a system implementation was carried out for the application of the system and analysis of the data results obtained. The results showed that the face detection system using YOLOv7 showed very good performance. In 100 training epochs, the system achieved 96,6% face detection accuracy and 90% face recognition accuracy, successfully identifying almost all registered faces and detecting faces in real time. This system produces high accuracy in detecting faces and almost all faces that should be recognized are successfully detected.
Implementation of Hybrid ResNet50 and XGBoost Model for Wheat Plant Disease Classification Aryanti Aryanti; Muhammad Aulia Dzikri; Ahmad Rifqi Nugraha; Khumairah Amira Sari; Dea Oktavia
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.13004

Abstract

A hybrid artificial intelligence (AI) system was successfully developed in this study, combining the ResNet50 architecture as an image feature identifier and the XGBoost algorithm for final classification. This model was used to detect six disease variations using 5,505 wheat leaf photographs. To ensure model stability, rigorous testing was conducted using two methods: Stratified 5-Fold Cross-Validation on the entire data set and independent testing using 300 images (equally divided into 50 samples per class).The test results demonstrated very solid performance. The model recorded an average global accuracy of 94.66% (±0.21%) using the K-Fold method, and an accuracy of 94.67% and a Macro F1-Score of 0.9445 in the independent testing. Through confusion matrix mapping, the model successfully classified the Healthy, Black Rust, and Septoria categories perfectly (a score of 1.00). However, there was still a minor error in the case of eight samples being confused between Brown Rust and Yellow Rust due to the visual similarity of the orange-yellowish coloration early in the infection period. Furthermore, the Feature Importance assessment demonstrated that the XGBoost decision base is transparent (Explainable AI). This AI accurately focuses on clinical signs of plants such as chlorosis symptoms and spot texture, while ignoring background objects such as weeds and soil. This combination of methods creates a stable, efficient system with a response time of only 18.5 milliseconds per photo, and a biologically valid decision base.
Design of a Hybrid SVM Ensemble and Large Language Model Chatbot for Multi-Class Intent Classification in Clinic Information Services Vina Rahmadiany; Lindawati Lindawati; Aryanti Aryanti
Bulletin of Network Engineer and Informatics Vol. 4 No. 1 (2026): BUFNETS (Bulletin of Network Engineer and Informatics) April 2026
Publisher : PT. GWEX NET PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59688/a3kdjj55

Abstract

Clinical information service chatbots require an accurate multiclass intent classification mechanism to handle informal language variations, medical abbreviations, service-related inquiries, and health complaints in Indonesian. This study aims to develop a hybrid chatbot architecture that integrates a Support Vector Machine ensemble for intent classification with Meta-Llama-3.1-8B-Instruct to generate relevant, natural, and context-aware responses. The dataset consisted of 3,293 utterance patterns across 66 intent classes. The proposed approach employed an 80:20 stratified split; semantic augmentation on the training data; preprocessing via abbreviation normalization, stopword removal, and Sastrawi stemming; TF-IDF feature extraction using unigram and bigram word n-grams and character n-grams; chi-squared feature selection; and hyperparameter optimization via grid search. The classification model was constructed by combining three calibrated LinearSVC classifiers via probability-based soft voting. Experimental results achieved an accuracy of 89.83%, a weighted F1-score of 89.90%, a kappa of 0.8966, a macro AUC of 0.9942, and an average response time of 61.87 ms. McNemar's test indicated statistically significant improvements over Complement Naïve Bayes, Logistic Regression, and Decision Tree, while no significant difference was observed compared with Single SVM. Therefore, the proposed architecture is effective at supporting multiclass intent classification and delivering fast, relevant chatbot responses for clinical information services.
Co-Authors Ade Silvia Handayani Adhelia Febriasari Harahap Ahmad Rifqi Nugraha Amanda Tsabita Putri Aqilla Khairunnisya Asriyadi Asriyadi Asriyadi Asriyadi Aulia Syafitri CIK SADAN Clara Alcahya Palpa Dea Oktavia Devi Indah Pujiana Dhea Syafitri Diah Novita Sari Dimas Iqbal Fahrozy Dyah Utari Yusa Wardhani Fatia Salsabilla Kyara Fifteen Angelina Hari Ramadhan Hj Lindawati Hj. Lindawati Ibnu Asrafi Ikhsan Yuda Pratama Ikhthison Mekongga Imas Ning Zhafarina Irma Salamah Jonathan Farrel Akbar Juriawan Raja Saputra Kayla Luna Pasha Khumairah Amira Sari M. A. Racka Eratama M.Nabil Ar-Rassya Mohammad Fadhli Muhammad Aulia Dzikri Muhammad Ghalib Muhammad Hanif Fatin Muhammad Rizko Justiano Muhammad Zakuan Agung Nabil Alrofi Nadya Aprilia Noval Resti Ardiansyah Nurhajar Anugraha Nurul Mardhiyah Pertiwi Nurul Utami Putri Nabila Putri Nur Azizah R.A. Halimatussa&#039;diyah Roni Suhermawan Sarjana, Sarjana Siti Salwa Nurhadiva Sulistia Sulistia Taufik Permana Vina Rahmadiany Yulia Hapsari