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All Journal ELINVO (Electronics, Informatics, and Vocational Education) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JURNAL INTEGRASI Journal of Computer, Electronic, and Telecommunication (COMPLETE) Journal of Engineering and Applied Technology Journal of Robotics, Automation, and Electronics Engineering Control Systems and Optimization Letters

Mentari Putri Jati

Universitas Negeri Yogyakarta

Author-ID : 1477257

Aerospace Engineering Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Mechanical Engineering Other

Published : 15 Documents Claim Missing Document

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Benchmark Analysis of Sampling Methods for RRT Path Planning Pratama, Gilang Nugraha Putu; Dhewa, Oktaf Agni; Priambodo, Ardy Seto; Baktiar, Faris Yusuf; Prasetyo, Rizky Hidayat; Jati, Mentari Putri; Hidayatulloh, Indra
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.132

Path planning is a crucial aspect of mobile robot navigation, ensuring that robots can safely travel from their initial position to the goal. In real-world applications, path planning is essential for autonomous vehicles, drones, warehouse robots, and rescue robots to navigate complex environments efficiently and safely. One effective method for path planning is the Rapidly-exploring Random Tree (RRT) algorithm, which is particularly practical in maze-like environments. The performance of RRT depends on the sampling methods used to explore the maze. Sampling methods are important because they determine how the algorithm explores the search space, affecting the efficiency and success of finding an optimal path. Poor sampling can lead to suboptimal or infeasible paths. In this study, we investigate different sampling strategies for RRT, specifically focusing on uniform sampling, Gaussian sampling, and the Motion Planning Network (MPNet) sampling. MPNet leverages a neural network trained on past environments, allowing it to predict promising regions of the search space quickly, unlike traditional methods like RRT that rely on random exploration without prior knowledge. This makes MPNet much faster and more efficient, especially in complex or high-dimensional spaces. Through a benchmarking analysis, we compare these methods in terms of their effectiveness in generating feasible paths. The results indicate that while all three methods are effective, MPNet sampling outperforms uniform and Gaussian sampling, particularly in terms of path length. The mean path length generated, based on a sample size of 30, is 13.115 meters for MPNet, which is shorter compared to uniform and Gaussian sampling, which are 18.27 meters and 18.088 meters, respectively. These findings highlight the potential to enhance path planning algorithms using learning-based sampling methods.

A Simple Modeling of MPPT-based ANN for Photovoltaic System Sholikhah, Evi Nafiatus; Aulia Rahma Annisa; Muhammad Rizani Rusli; Mentari Putri Jati
Journal of Computer, Electronic, and Telecommunication (COMPLETE) Vol. 6 No. 1 (2025): July
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/complete.v6i1.684

This research describes a simple modeling technique for Maximum Power Point Tracking based on Artificial Neural Network (MPPT-based ANN) for photovoltaic (PV) systems. The proposed ANN model utilizes a feed-forward backpropagation architecture. The PV system was developed and tested in a simulation environment under uniform irradiation levels of 1000 W/m², 800 W/m², and 600 W/m², and rapidly varying irradiation changes. The simulation results demonstrate that the MPPT-based ANN accurately tracks the MPP, achieving stable power outputs of 98.36 W, 79 W, and 57.45 W, respectively. Although the system experiences initial transient oscillations during the tracking phase, it stabilizes within 80 milliseconds, showcasing rapid convergence and high steady-state accuracy. Under dynamic conditions, the MPPT-based ANN adapts effectively to fast-changing irradiation, restarting the algorithm to track and maintain the system at the updated MPP accurately. These results highlight the reliability, adaptability, and suitability of the MPPT-based ANN for real-time applications in dynamic environments. Nonetheless, further improvements to the ANN model are suggested to minimize transient oscillations and enhance overall performance.

Kendali Fuzzy Logic - Interleaved Boost Converter pada Aplikasi Motor DC Jati, Mentari Putri; Basuki, Gamar; Hasnira, Hasnira
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 5 No. 2 (2020): November 2020
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Karakteristik motor DC menjadi hal mutlak yang perlu diketahui dalam proses pengendalian kecepatan penggerak elektrik. Konverter pengemudian elektrik yang sedang berkembang yaitu Interleaved Boost Converter. Pengendali fuzzy logic merupakan kendali yang efektif diterapkan banyak sistem linier maupun nonlinier dengan waktu operasi yang cepat. Hasil penerapan aplikasi motor DC berupa penyiram kecambah dapat berfungsi dengan baik pada variasi nilai setpoint kecepatan yang mana perubahan nilai tegangan keluaran berbanding lurus dengan perubahan kecepatan motor DC (30 Volt sd. 60 Volt â‰ˆ 800 Rpm sd 1500 Rpm). Hal ini dapat membantu para petani kecambah dalam melakukan penyiraman biji kecambah secara otomatis seiring dengan perubahan suhu sekitar tanpa khawatir biji kecambah rusak.

Design and Implementation of Real-Time Health Vital Sign Monitoring Device with Wireless Sensor-based on Arduino Mega Wulandari, Bekti; Jati, Mentari Putri
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 6 No. 1 (2021): Mei 2021
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

This paper discusses the realization of vital sign monitoring devices and knowing their performance. This device is expected to assist medical personnel in measuring and monitoring vital signs without having to have physical contact with patients. The design phase of the patient's vital sign monitoring device with an Arduino Mega-based wireless sensor starts from the identification, needs analysis, design, manufacture, troubleshoot, and testing. Arduino Mega and ESP8266 as the main components that function for the controller and upload data to the server. Then MAX30100, DS18B20, and MPX5700AP sensors which function to detect the vital sign. Android smartphones are used to display measurement results in real-time, save and display vital sign data records. Based on the test results, the patient's vital signs monitoring device has an average difference of 0.67% for temperature checks, 1.19% for pulse checks, 0.77% for SPO2 examinations, 4.78%, and 8.91% for systolic and diastolic blood pressure examinations.

Stake's Countenance Evaluation Method on Occupational Health and Safety Implementation in Electronics Engineering Education's Student Industrial Internship Munir, Muhammad; Jati, Mentari Putri; Wulandari, Bekti; Dewanto, Satriyo Agung
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 7 No. 1 (2022): Mei 2022
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

This paper discusses the evaluation of the implementation of Occupational Health and Safety (OHS) in student industrial internships. Due to the possibility of the risk of work accidents on industrial internship students are prone to occur. Currently, there are still few who discuss the evaluation of OHS implementation as the basis for carrying out sustainable action efforts. Based on the evaluation carried out, the OHS Implementation in Electronics Engineering Education's Student Industrial Internship has been feasible and follows applicable laws and regulations. The results of this evaluation can provide ideas for increasing sustainable action efforts regarding OHS in Student Industrial Internships.

Co-Authors Abdul Mujiburrohman Luthfi Anang Tjahjono, Anang angga wahyu aditya Ardy Seto Priambodo Aries Alfian Prasetyo Aulia Rahma Annisa Bambang Sumantri Bambang Sumantri BASUKI, GAMAR Bayu Praharsena Bekti Wulandari Dewanto, Satriyo Agung Dimas Okky Anggriawan Endro Wahjono Era Purwanto Farid Dwi Murdianto Faris Yusuf Baktiar Ferdiansyah, Indra Gilang Nugraha Putu Pratama Hary Oktavianto Hasnira Hasnira Hasnira Hasnira, Hasnira Indhana Sudiharto Indra Hidayatulloh MOCHAMAD ARI BAGUS NUGROHO Mochammad Ari Bagus Nugroho Mohammad Jauhari Muhammad Munir Novie Ayub Windarko Nurisma Zenita Dewi Oktaf Agni Dhewa Ony Asrarul Qudsi Otniel Andi Hermawan Rizky Hidayat Prasetyo Rusli, Muhammad Rizani Saddam Putra Kunsina Sholikhah, Evi Nafiatus Sutedjo Sutedjo

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