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All Journal Jurnal Teknologi Informasi dan Pendidikan Electron: Jurnal Ilmiah Teknik Elektro Majalah Ilmiah Teknologi Elektro
Setiawan, Putu Ayu Citra
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering

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Tinjauan Literatur: Deteksi Anomali Berbasis Analisis Waktu pada CAN Bus Kendaraan Listrik Setiawan, Putu Ayu Citra; Giriantari, Ida Ayu Dwi; ER, Ngurah Indra
ELECTRON Jurnal Ilmiah Teknik Elektro Vol 6 No 1: Jurnal Electron, Mei 2025
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/electron.v6i1.282

Abstract

The development of modern automotive technology emphasizes the importance of vehicle connectivity and autonomy, with the aim of enhancing safety and comfort. Due to its role in managing critical vehicle functions and its vulnerability to security threats, the automotive industry has developed two primary approaches to address CAN Bus security. Therefore, the automotive industry has developed two main approaches to address this security issue. First, passive defense through security protocols that include encryption, authentication, and message verification, and second, anomaly detection using advanced technologies. Several anomaly detection methods have been introduced, including K-Means clustering, Support Vector Machines, and Deep Learning, each offering advantages in detecting specific attack patterns. However, one increasingly popular approach is time analysis, which leverages message inter-arrival patterns and clock skew on the CAN Bus to identify suspicious behavior and detect anomalies in real-time. Although this method has shown effectiveness in detecting various types of attacks, the main challenge lies in its ability to identify highly concealed attacks that may not be visible to traditional methods. This research provides an understanding of various anomaly detection approaches on electric vehicle CAN Bus networks, with a primary focus on time analysis. By reviewing several approaches, this study offers valuable insights into improving the security of electric vehicles and the overall smart transportation ecosystem. The results show that time-based analysis methods can detect various types of attacks, such as spoofing, replay attacks, and denial-of-service, with high efficiency.
Potensi Metode Regresi Kuat dalam Pengukuran Skew Jam Setiawan, Putu Ayu Citra; Saputra, Komang Oka; Wiharta, Dewa Made
Jurnal Teknologi Informasi dan Pendidikan Vol. 18 No. 1 (2025): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v18i1.962

Abstract

Clock skew, defined as the difference in clock rates between digital devices, serves as a unique and stable fingerprint for device identification and authentication, particularly in distributed network environments. Traditional clock skew estimation techniques, such as linear regression, are effective under stable conditions but often fail in the presence of data disturbances, such as latency, jitter, and asymmetric delays, which introduce outliers. This study explores the application of robust regression methods to enhance the accuracy and stability of clock skew estimation under such conditions. Three robust techniques are comparatively analyzed: Least Median of Squares (LMedS), Random Sample Consensus (RANSAC), and S-Estimators. LMedS offers high resistance to outliers by minimizing the median of squared residuals, though it is computationally demanding for large datasets. RANSAC achieves a practical balance between robustness and efficiency through iterative model fitting and inlier maximization, while S-Estimators provide strong statistical resistance to both outliers and high-leverage points, albeit with increased implementation complexity. The comparative evaluation considers key parameters such as estimation accuracy, computational cost, and robustness to anomalies. Results indicate that RANSAC is generally preferred for clock skew measurement in distributed systems due to its efficient performance and explicit outlier detection capabilities. However, LMedS and S-Estimators remain valuable in scenarios with more complex anomaly structures or higher noise levels. This study contributes to the selection of appropriate robust regression methods for reliable clock skew estimation in dynamic and error-prone network environments.
Pertanian Vertikal Pintar: Peran IoT dalam Mewujudkan Keberlanjutan dan Efisiensi Sumber Daya Setiawan, Putu Ayu Citra; Indra ER, Ngurah; Sukadarmika, Gede
Majalah Ilmiah Teknologi Elektro Vol 24 No 1 (2025): ( Januari - Juni ) Majalah Ilmiah Teknologi Elektro
Publisher : Study Program of Magister Electrical Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.205.v24i01.P03

Abstract

The rapid growth of population and urbanization poses significant challenges to global food security, particularly in urban areas. The conversion of agricultural land into residential and infrastructure zones reduces local food production capacity, while climate change exacerbates uncertainties in crop yields. To address these challenges, IoT-based vertical farming has emerged as an innovative solution to enhance efficiency and sustainability in food production systems. IoT technology enables vertical farming systems to monitor and control environmental variables such as temperature, humidity, lighting, and nutrient levels in real-time through sensors connected to artificial intelligence. The collected data is analyzed to optimize plant growth, minimize resource waste, and maximize crop yields while reducing energy consumption. Additionally, integrating IoT with automated irrigation systems and energy-efficient LED lighting further enhances water and electricity efficiency. From a sustainability perspective, IoT-based vertical farming allows for year-round food production without relying on vast land areas or favorable weather conditions.  This research further explores how IoT contributes to improving resource efficiency, environmental sustainability, and the economic and social impacts of vertical farming. . Based on the research findings, the implementation of IoT in vertical farming has proven to be highly beneficial in enhancing sustainability and resource efficiency in urban food production.  Through real-time monitoring and automated control systems, IoT enables precise regulation of key environmental factors such as temperature, humidity, lighting, and nutrient levels, ensuring optimal plant growth with minimal resource wastage.
Co-Authors Dewa Made Wiharta Gede Sukadarmika Ida Ayu Dwi Giriantari Ngurah Indra ER Saputra, Komang Oka