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All Journal Jurnal Pendidikan Lingkungan dan Pembangunan Berkelanjutan Prosiding Seminar Nasional Official Statistics
Junianto, Raihan Rahmanda
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Social Sciences

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Examining the Impact of Energy Use, Economic Growth, and Forest Area on CO2 Emissions: Consequences for Achieving the SDGs Amalia, Mutiara Friska; Junianto, Raihan Rahmanda; Kartiasih, Fitri; Rahmadani, Rizky
Jurnal Ilmiah Pendidikan Lingkungan dan Pembangunan Vol 25 No 02 (2024): PLPB: Jurnal Pendidikan Lingkungan dan Pembangunan Berkelanjutan, Volume 25 Nom
Publisher : Program Studi Pendidikan Kependudukan dan Lingkungan Hidup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/plpb.v25i02.42230

Abstract

Climate change can be caused by both natural and human activities. Human activities are the main factor causing climate change that is getting worse such as deforestation, industrialization, transportation, and so on. Climate change that occurs continuously can cause various health risks, global food security, decreased biodiversity, and environmental damage to economic development. Climate change also needs to be studied in the application of SDGs to realize sustainable development targets. The purpose of this study is to examine the relationship between economic growth, energy consumption, and forest area to CO2 emissions in Indonesia from 1990-2022 and find out what the implications are with the achievement of SDGs on climate change. This study applies the VECM analysis method to get an overview of the long-term balance and short-term relationship of the four variables. The results obtained are that forest area only affects CO2 emissions in the long term, while economic growth only affects CO2 emissions in the short term. Meanwhile, the energy consumption variable affects CO2 emissions in both the short and long term. Therefore, handling from various parties and policies from the government are needed to realize environmentally friendly development to achieve sustainable development goals in the future.
Deteksi Pola Kecelakaan Lalu Lintas dengan Ensemble Learning Berdasarkan Ekstraksi Informasi Berita Online Junianto, Raihan Rahmanda; Yuniarto, Budi
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2484

Abstract

The alleviation of traffic accidents is part of Goal 3 of the Sustainable Development Goals (SDGs). However, the lack of access to information on traffic accidents in areas with high traffic accident rates, such as Central Java, makes controlling these cases ineffective. To date, no publication has provided an overview of traffic accident patterns in Central Java. Therefore, this study aims to utilize ensemble learning in traffic accident pattern detection based on online news information extraction. Online news is chosen as an alternative data source because it is fast, open, and informative. The model developed in this research is Indonesian Bidirectional Encoder Representative from Trasnformer (IndoBERT) for Named Entity Recognition (NER) in extracting online news information, which produces an accuracy of 0.9601. Then, the information extraction results will be used to understand traffic accident patterns using Random Forest with an f1-score of 0.7474. This research also proposes a Decision Tree-based surrogate model to improve the interpretability of the Random Forest model with an average accuracy of 0.8995.
Co-Authors Amalia, Mutiara Friska Fitri Kartiasih Rizky Rahmadani, Rizky Yuniarto, Budi