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All Journal Foristek Indonesian Journal of Electrical Engineering and Computer Science Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering)
Erwin Ardias Saputra
Department Of Electrical Engineering, Engineering Faculty, Tadulako University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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RANCANG BANGUN SOLAR TRACKER DENGAN PENGUKURAN ARUS DAN TEGANGAN SECARA DIGITAL BERBASIS MIKROKONTROLER Erwin Ardias Saputra; Rizana Fauzi; Tan Suryani Sollu; Jurnianto Demmassewa
Foristek Vol. 14 No. 1 (2023): Foristek
Publisher : Foristek

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54757/fs.v14i1.254

Abstract

The design of a solar tracker with digital current and voltage measurements based on a microcontroller is a system that can follow the direction of the sun automatically based on the LDR sensor. The working principle of this tool is to direct the solar panels to follow the direction of the sun automatically and the current and voltage can be monitored digitally based on a data logger. The result of this design is that the solar tracker is programmed using Arduino Uno as the control center, LDR sensor for detecting sunlight as a determinant of the slope of the solar panel to the sun. To drive it, it uses two (2) power window motors which are controlled using the BTS7960 motor driver, and uses the INA219 sensor to measure the current and voltage. The output current and voltage of the solar panel is displayed on the LCD (Liquid Crystal Display) and can be monitored using the PLX-daq data logger.
ZigBee-Based Wireless Sensor Network Topology Design and Comparison in Residential Areas Muh. Aristo Indrajaya; Rizana Fauzi; Erwin Ardias Saputra
Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Vol 10 No 1 (2023): Jurnal Ecotipe, April 2023
Publisher : Jurusan Teknik Elektro, Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/jurnalecotipe.v10i1.3704

Abstract

When designing a wireless sensor network based on ZigBee, it is very important to choose the right network topology, especially in networks with many nodes such as residential areas. Choosing the wrong topology will have an impact on the performance of the wireless sensor network as a whole because it will cause a large delay value. To overcome this, in this study a ZigBee-based wireless sensor network simulation was carried out using an environmental model consisting of several residential units, with one ZigBee device for each house. In addition, three ZigBee network topologies namely mesh, star, and tree are used in this simulation. This is done to determine which topology model will work best in a residential environment. The housing used for the simulation in this study is Citraland Waterfront City Housing which is located in Palu City, Central Sulawesi Province, Indonesia. By using simulations in the Opnet Modeler 14.5 application, it is known that the star topology on the ZigBee network is suitable for application in residential areas with a large number of nodes. This can be seen from the highest throughput values and the lowest media access delay, end-to-end delay, hop number, and packet dropped values compared to tree and mesh topologies.
Classification of weather conditions based on automatic weather station data using a multi-layer perceptron neural network Indrajaya, Muhammad Aristo; Sollu, Tan Suryani; Subito, Mery; Rahman, Yuli Asmi; Saputra, Erwin Ardias
Indonesian Journal of Electrical Engineering and Computer Science Vol 37, No 1: January 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v37.i1.pp540-550

Abstract

Weather is one of the important elements that greatly determines human activities, especially those related to economic factors. Therefore, understanding weather conditions using weather parameters as a reference is important for human life, so a method is needed to classify weather according to its category so that the information produced can be used for various needs. Determining weather conditions in an area will not run well without a reliable method that can analyze existing weather parameters. Therefore, in this study, the weather condition classification process was carried out using the multilayer perceptron algorithm, a type of neural network (NN) algorithm. All data analyzed were weather parameter data collected by mini weather stations placed on land. The weather parameters used were temperature, humidity, air pressure, wind speed, dew point, wind chill, daily rainfall, solar radiation, and UV index. This study was conducted in Palu city, Central Sulawesi Province, Indonesia. The classification process carried out by the multilayer perceptron algorithm was carried out on the Altair AI Studio application and produced an accuracy value of 93.87%, recall of 92.33%, and precision of 91.29%.
Co-Authors Indrajaya, Muhammad Aristo Jurnianto Demmassewa Mery Subito Muh. Aristo Indrajaya Rizana Fauzi, Rizana Tan Suryani Sollu Yuli Asmi Rahman