PERANCANGAN SISTEM SMART GRID BERBASIS INTERNET OF THINGS (IOT) UNTUK PENGELOLAAN LISTRIK YANG EFISIEN

The use of energy in Indonesia is influenced by various factors, including history, economics, and geography, with a high dependence on fossil fuels despite declining oil reserves. The transition to clean energy sources, particularly solar energy through solar panels, has become a primary focus. Solar panels, which use semiconductor-based photovoltaic cells, serve to convert sunlight into electrical energy. The need for sustainable electricity drives the implementation of smart grid systems based on IoT technology, which enhances the efficiency and reliability of electricity distribution. This research explores the use of solar panels as an alternative power source by assessing the power output and efficiency of the system. The application of IoT allows for better automation and energy management. The research methods include needs analysis, system design, and the implementation of IoT technology for real-time monitoring. From the test results, the power generated by the solar panel varies depending on the time and intensity of sunlight. At 07:00 AM, the generated power was 15.99 W, increasing to 83.79 W at 11:00 AM, and then decreasing to 52.17 W at 05:00 PM. Overall, the power efficiency of the solar panel fluctuated, with an increase of up to 424% from morning to midday before declining in the afternoon.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-11
DOI
https://doi.org/10.5281/zenodo.15860175
Primary Topic
Evolution and Paleontology Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PERANCANGAN SISTEM SMART GRID BERBASIS INTERNET OF THINGS (IOT) UNTUK PENGELOLAAN LISTRIK YANG EFISIEN

Zenodo (CERN European Organization for Nuclear Research)
Evolution and Paleontology Studies
article

PERANCANGAN SISTEM SMART GRID BERBASIS INTERNET OF THINGS (IOT) UNTUK PENGELOLAAN LISTRIK YANG EFISIEN

article en

Abstract

The use of energy in Indonesia is influenced by various factors, including history, economics, and geography, with a high dependence on fossil fuels despite declining oil reserves. The transition to clean energy sources, particularly solar energy through solar panels, has become a primary focus. Solar panels, which use semiconductor-based photovoltaic cells, serve to convert sunlight into electrical energy. The need for sustainable electricity drives the implementation of smart grid systems based on IoT technology, which enhances the efficiency and reliability of electricity distribution. This research explores the use of solar panels as an alternative power source by assessing the power output and efficiency of the system. The application of IoT allows for better automation and energy management. The research methods include needs analysis, system design, and the implementation of IoT technology for real-time monitoring. From the test results, the power generated by the solar panel varies depending on the time and intensity of sunlight. At 07:00 AM, the generated power was 15.99 W, increasing to 83.79 W at 11:00 AM, and then decreasing to 52.17 W at 05:00 PM. Overall, the power efficiency of the solar panel fluctuated, with an increase of up to 424% from morning to midday before declining in the afternoon.

Zenodo (CERN European Organization for Nuclear Research)
Sriwijaya University (ID), Politeknik Negeri Sriwijaya (ID)
Industry, innovation and infrastructure
Openalex Percentile: Top 53%
Evolution and Paleontology Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.