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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan Journal of Information Technology and Computer Science Jurnal Teknik Industri Terintegrasi (JUTIN) Kawanua International Journal of Multicultural Studies PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Journal of Embedded Systems, Security and Intelligent Systems Journal of Mathematics and Applied Statistics POLIGRID
Fajerin Biabdillah
Poilteknik Negeri Samarinda
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering

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Hybrid Regression–Simulation Model for Evaluating Emission Policies in Oversaturated Urban Corridors: A Case Study of Jakarta Fara Triadi; Arsan Kumala Jaya; Fajerin Biabdillah; Abdul Hanif
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i4.10595

Abstract

Urban traffic emissions continue to escalate in Southeast Asian megacities, particularly along oversaturated central business district corridors where chronic congestion amplifies pollutant accumulation. Previous research often separates statistical emission modelling from microscopic simulation, limiting the ability to evaluate policy impacts under real-world saturation conditions. This study aims to assess whether lane-level transport interventions specifically bus-only lanes and motorcycle restrictions can reduce emissions in a hyper-congested Jakarta corridor through an integrated analytical approach. A hybrid regression–microsimulation framework was developed by combining multiple linear regression with SUMO-based traffic simulation. An hourly dataset of traffic flow and CO emissions (n = 8,760) from the Thamrin–Bundaran HI corridor was used to construct a regression model enriched with temporal and lagged predictors. The resulting emission profiles were embedded into SUMO to simulate baseline, bus-lane, and motorcycle-restriction scenarios. The regression model achieved strong predictive performance (R² = 0.692, RMSE = 0.252), with CO_lag1 confirmed as the dominant predictor. Simulation results showed fully overlapping CO₂ emission trajectories across all scenarios, indicating that lane-based interventions do not alter traffic states or emissions under oversaturated conditions. Structural congestion constrains the effectiveness of lane-level policies. Meaningful emission reductions require systemic strategies such as demand management, modal shift, or network redesign. The proposed hybrid framework provides a replicable tool for evaluating transport policies in dense urban corridors
Sentiment-Aware Transformer for Cryptocurrency Volatility Prediction Using Multi-Source Market and News Sentiment Fajerin Biabdillah; Fara Triadi; Aeltri Jeacfky Gozal Go; Muhammad Cahyo Putra Ramadhan
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i4.10604

Abstract

The cryptocurrency market has grown into a multi-trillion-dollar domain with extreme volatility. This paper addresses the forecasting of crypto price movements and volatility by integrating market metrics with sentiment analysis. We identify a gap in existing studies, which often ignore multi-source sentiment and thus miss early warning signs of volatility. We propose a Sentiment-Aware Transformer model inspired by the Temporal Fusion Transformer (TFT). The model ingests daily price, volume, and market cap features from CoinMarketCap alongside aggregated sentiment scores from Twitter, Reddit, and financial news (extracted via FinBERT). We train and evaluate the model on 5 years of data for 10 major cryptocurrencies (2020–2024), comparing performance against LSTM and GRU baselines with identical inputs. The proposed Transformer achieves 83.2% volatility prediction accuracy with an F1-score of 0.81, exceeding the LSTM (79% accuracy) and GRU (80%) baselines. It also shows the lowest RMSE in price forecasting and a higher return correlation (0.72) with actual prices, indicating improved trend alignment. These gains are statistically significant (p<0.01). We also discuss how attention weights offer interpretability, as the model focuses on sentiment spikes during impending volatility.
Implementasi Sistem Komunikasi Otomatis untuk Data Logger Sensor Salinitas di Sungai Wain Balikpapan dengan Solusi Reverse SSH Tunnel pada Lingkungan CGNAT Agus Triyono; Fajerin Biabdillah
PoliGrid Vol. 7 No. 1 (2026): Juni 2026
Publisher : Jurusan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46964/poligrid.v7i1.197

Abstract

Pemantauan salinitas di kawasan konservasi Sungai Wain, Balikpapan, memerlukan saluran komunikasi data yang tetap hidup walau perangkat dipasang jauh dari infrastruktur jaringan tetap. Persoalan muncul saat data logger kami sambungkan lewat modem 4G LTE: operator seluler di Indonesia umumnya menerapkan Carrier Grade NAT (CGNAT) sehingga Raspberry Pi di lapangan tidak memperoleh alamat IP publik. Akibatnya port forwarding tidak bisa diandalkan dan akses balik dari pusat kendali jadi terhambat. Penelitian ini merancang dan menguji solusi reverse SSH tunnel berbasis autossh yang dijaga oleh systemd, kemudian mengukur perilaku sistem di lab dengan SIM komersial yang berada di balik CGNAT. Selama 24 jam pengujian, sistem berhasil mengirim 1.440 titik data tanpa kehilangan paket, uptime tunnel tercatat 99,5%, dan rata-rata waktu pemulihan setelah pemutusan jaringan berada di kisaran 6 sampai 9 detik. Akses SSH balik (port 2222 di server pusat) terbukti stabil dengan latensi rata-rata 150 ms. Konsumsi daya komputasi tetap rendah, ~5% CPU saat idle dan ~15% saat transfer file. Hasil tersebut memperlihatkan bahwa pendekatan tunneling berbasis perangkat lunak bebas terbukti layak menjadi pengganti VPN komersial atau paket IP publik statis untuk proyek monitoring lingkungan skala menengah-kecil di Indonesia.
Co-Authors Abbizar Mulia Abdul Hanif Aeltri Jeacfky Gozal Go Agus Triyono Agusma Wajiansyah Agusma Wajiansyah, Agusma Arsan Kumala Jaya Awaluddin A., Muhammad Fara Triadi Fara Triadi Fitra Abdurrachman Bachtiar Hanif, Abdullah Hartanto, Subhan Herman Tolle Ismayanti, Rika Jeacfky Gozal Go, Aeltri Maesaroh, Dwi Titi Maknuniah, Jauharatul Muhammad Cahyo Putra Ramadhan Mulia, Abbizar Raimundus, Jonathan Ramadhan, Muhammad Cahyo Putra Syahidi, Aulia Akhrian Tajuddin, Muhammad wa ode denada mar ella