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All Journal TEKNIK Jurnal Ilmu-Ilmu Kehutanan
Fikri Arkan Maulana
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Decision Sciences, Operations Research & Management Engineering Environmental Science

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Identification of Invasive Understolans in Nganggring Tourism Village, Girikerto Village, Sleman Regency, Special Region of Yogyakarta Alvina Novelinda Kusuma; Fikri Arkan Maulana; Sa’ad Abdul Jabbar; Lia Kusumaningrum
Jurnal Ilmu Ilmu Kehutanan Vol. 8 No. 1 (2024)
Publisher : Jurusan Kehutanan Fakultas Pertanian Universitas Riau

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Abstract: This study identifies and analyzes invasive understory plants posing a threat to the ecological balance in Nganggring Village, Sleman, Yogyakarta Special Region, particularly within the prominent Salak Pondoh plantation. Employing direct observation and interpreting remote sensing imagery from Google Earth, the research collected data using a systematic grid approach at intervals of 10x10 and 5x5 meters. The findings reveal the presence of various invasive species, including Legetan, Elephant Grass, Thunbergia erecta, Israeli Grass, and others. These plants exhibit high adaptability, rapid growth, and competitive capabilities, posing a significant risk to the local ecosystem. The study provides insights into the diversity of invasive understory plants in Nganggring Village, serving as a foundational step in minimizing adverse environmental impacts. Sustainable environmental protection and management efforts are crucial for mitigating invasion risks and preserving ecological balance in the region. This research contributes to a better understanding of invasive flora, supporting environmental sustainability amid the prominent Salak Pondoh plantation.
IoT and Machine Learning-Based Electric Vehicle Development Strategy to Maximize Vehicle Life and Promote Green Mobility Callista Fabiola Candraningtyas; Fikri Arkan Maulana; Alles Anandhita Achmad
TEKNIK Vol 46, No 1 (2025)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/teknik.v46i1.67383

Abstract

This research explores innovative strategies for developing electric vehicles based on the Internet of Things (IoT) and Machine Learning with the aim of maximizing service life and encouraging green mobility. In the face of the climate crisis and the increasing need for sustainable energy, electric vehicles offer a potential solution to reduce carbon emissions in the transportation sector. However, the challenges of optimizing battery life and energy efficiency require new, smarter and more connected approaches. This research integrates IoT technology with machine learning to create a more efficient electric vehicle ecosystem. This technology enables extended battery life through better usage management, increased energy efficiency through operational optimization, and predictive maintenance that reduces vehicle downtime. The research methodology includes testing prototypes of electric vehicles equipped with IoT technology, field trials to collect performance data, comprehensive analysis, and data processing to evaluate the effectiveness of the implemented strategies. The research results show that the integration of IoT and Machine Learning in electric vehicles can significantly increase battery life, energy efficiency, and make a positive contribution to green mobility. This development strategy is expected to advance electric vehicle technology in Indonesia, reduce dependence on fossil fuels, and create a cleaner and more sustainable environment.
Co-Authors Alles Anandhita Achmad Alvina Novelinda Kusuma Callista Fabiola Candraningtyas Lia Kusumaningrum Sa’ad Abdul Jabbar