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Jurnal Telematika
Published by Institut Teknologi Harapan Bangsa
ISSN : 18582516     EISSN : 25793772     DOI : https://doi.org/10.61769/telematika
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal Telematika is a scientific periodical written in Indonesian language published by Institut Teknologi Harapan Bangsa twice per year. Jurnal Telematika publishes scientific papers from researchers, academics, activist, and practicioners, which are results from scientific study and research in the field of telematics and information technology.
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Articles 7 Documents
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Search results for , issue "Vol. 19 No. 2 (2024)" : 7 Documents clear
Moving Asset Tracking Using GPS Sensor and Internet of Things Suakanto, Sinung; Nugroho, Tunggul Arief; Nuryanto, Edi; Lathifah, Syfa Nur; Nuraliza, Hilda
Jurnal Telematika Vol. 19 No. 2 (2024)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v19i2.650

Abstract

Moving assets, such as buses, trucks, and trains, are important productive assets, especially in the transport industry. Effective tracking of these assets is essential to optimize operations, ensure safety, and minimize costs. However, traditional tracking methods often lack real-time monitoring, which leads to inefficiencies and potential risks. This research proposes a mobile asset tracking system with a special focus on railway assets and leverages GPS technology for real-time positioning and IoT for data transmission to a cloud-based data center. A prototype of the system was successfully developed using hardware connected to a GPS device that continuously transmits location data. In this paper, an application for visualization management has also been developed to display asset data and track asset positions in real time. Performance evaluation was conducted using the RAMS (reliability, availability, maintainability, and safety) framework, which showed an average update interval of 49 seconds, a system availability rate of 94% for one month, and better maintainability due to the plug-and-play nature of the GPS-based system. Although long-term safety improvements require further study, the proposed system improves on existing navigation methods by providing real-time tracking and increasing operator awareness. These findings highlight the potential of GPS and IoT integration in improving asset tracking and operational efficiency in the transport sector.
Penerapan You Only Look Once dan DeepSORT untuk Deteksi Plat Nomor Kendaraan Hidayat, Firhat; Billy, Natanael; Permana, Nicholas Russel; Hariady, Matthew Evans
Jurnal Telematika Vol. 19 No. 2 (2024)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v20i2.676

Abstract

Number plate detection is essential in traffic monitoring, law enforcement, and intelligent transport systems. However, existing methods still have difficulty accurately tracking vehicles in heavy traffic conditions. This study addresses this by combining the YOLOv8 detection model and DeepSORT tracking. Using 453 images from Kaggle, this study analyses the effect of batch size variation and an epoch on model performance. The best model achieved 95.5% precision, 95.1% recall, 98.7% mAP50, and 64.5% mAP95. The integration of YOLOv8 and DeepSORT can improve tracking consistency, reduce ID switching errors, and increase the reliability of the automatic number plate recognition system.
Manajemen Risiko dalam Optimalisasi Keberhasilan Proyek Teknologi Informasi Menggunakan Framework ISO 31000 Ahkmad, Farhat Falfalla; Ilham
Jurnal Telematika Vol. 19 No. 2 (2024)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v19i2.712

Abstract

Penelitian ini mengkaji penerapan framework ISO 31000 dalam manajemen risiko teknologi informasi melalui berbagai studi kasus. Fokus penelitian ini adalah pada identifikasi, analisis, evaluasi, dan penanganan risiko di dalam organisasi, khususnya di sektor perbankan, e-commerce, pemerintahan, dan pendidikan. Melalui pendekatan systematic literature review (SLR), penelitian ini menyintesiskan wawasan dari sepuluh studi kasus yang melibatkan penerapan ISO 31000 dalam mengelola risiko, seperti ancaman siber, kebocoran data, dan gangguan operasional. Hasil penelitian menunjukkan bahwa ISO 31000, ketika dikombinasikan dengan metodologi lain seperti COBIT 5 dan FMEA, memberikan pendekatan yang lebih holistik dalam manajemen risiko dengan memprioritaskan risiko dan mengembangkan strategi mitigasi yang disesuaikan. Penelitian ini juga menyoroti pentingnya pemantauan dan evaluasi berkelanjutan untuk memastikan efektivitas perlakuan risiko. Hasil penelitian mengonfirmasi bahwa penerapan ISO 31000 secara signifikan meningkatkan ketahanan organisasi dan pengambilan keputusan dalam mengelola risiko TI dan memastikan kelangsungan bisnis jangka panjang dan kepercayaan pemangku kepentingan. Penelitian ini memberikan wawasan yang berharga bagi organisasi yang ingin meningkatkan strategi dan framework manajemen risiko TI.
Perancangan Sistem Keamanan Komunikasi Data pada Jaringan LoRA Menggunakan Algoritme PRESENT Hikmaturokhman, Alfin; Ramadhani, Eka Hero; Wulandari, Asri
Jurnal Telematika Vol. 19 No. 2 (2024)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v19i2.674

Abstract

LoRa is a low-power wireless communication technology capable of transmitting data over long distances. LoRa is widely used in embedded systems and the Internet of Things (IoT) in various sectors, such as agriculture, fisheries, industry, transportation, and smart cities. However, the data transmitted through LoRa is not encrypted, so the confidentiality of the data is not guaranteed because the data can be intercepted and read by hackers at the same frequency. Therefore, data encryption techniques are needed in the LoRa system to maintain data confidentiality when transmitted. In this research, a LoRa system is designed, and an analysis of the lightweight PRESENT block cipher algorithm is carried out to secure data communication on the LoRa system. This research uses a LoRa RFM95W module with a 915 MHz frequency and an ATmega328P microcontroller. This research method consists of the stages of literature study, design, implementation, testing, and analysis. After the design and implementation stages, the LoRa system was tested with data transmission test scenarios with test vectors and data communication interception tests. This research shows that the PRESENT algorithm was successfully implemented on the LoRa communication system, and hackers could not read the data sent from LoRa Tx and Rx. The test results also show that implementing the PRESENT algorithm on the LoRa system does not affect data communication performance based on RSSI values. The results of this research can be used in further research in various fields, such as IoT security in agriculture, fisheries, transportation, industry, and smart cities.
Pelacakan Geometri Segitiga dan Lingkaran di Kawasan Tepi untuk Segmentasi Objek Sucipto, Putra Wisnu Agung; Firasanti, Annisa; Bakri, Muhammad Amin; Ekawati, Inna; Yaqin, Khusnul
Jurnal Telematika Vol. 19 No. 2 (2024)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v19i2.717

Abstract

Segmentation of yellow fish egg spheres in digital images often fails due to the difficulty of determining the boundaries between adjacent or overlapping objects. This research proposes a geometry tracking-based segmentation method to solve the problem. This method uses triangulation of three important edge points around the object to determine the initial segment landmarks. Then, it uses their formation to form a complete circle of candidate segments. The set of pixels enveloped by this circle will be examined for shape and colour to be recognised as segments of an object or not. The method was tested on a fish egg image dataset containing more than 5,473 yellow-orange coloured fish egg spheres in 11 digital images. These egg sphere images vary in size, shape, brightness, contrast, density, shadow, noise, light reflection, and blur. Based on the experimental results, the method was able to correctly segment 4,370 egg spheres with 242 false segments and 1,103 undetected spheres. The performance metrics of this method are precision 94.7%, recall 79.8%, IoU 76.5%, and dice coefficient 86.7%.
Penerapan Model Windkessel Dua Elemen pada Simulasi Denyut Jantung Menggunakan Pendekatan Biomodeling Lutfiyani, Zakia; Fiarni, Cut
Jurnal Telematika Vol. 19 No. 2 (2024)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v19i2.694

Abstract

Berangkat dari pembuatan Simulator CABbaGe (Coronary Artery Bypass Grafting) sebagai sarana media pembelajaran bedah jantung koroner yang berkonsep virtual reality, perancangan biomodeling denyut jantung dimulai dengan pendekatan pada perubahan tekanan pulsa di daerah mesh pembentuk obyek jantung yang mengakibatkan perubahan volume jantung, dan berakhir pada perubahan gaya tekan jantung. Dari perancangan tersebut, dieksplorasi untuk mendapatkan hasil yang lebih baik terkait model denyut jantung dengan menggunakan Model Windkessel  Dua Elemen yang mana model ini menggambarkan dinamika tekanan dan aliran darah dalam sistem kardiovaskular dan lebih akurat dalam menggambarkan dinamika aliran darah yang lebih kompleks. Dari hasil pengujian dapat diperoleh kesimpulan bahwa implementasi Model Windkessel Dua Elemen ini cukup efektif untuk memodelkan dan memahami mekanika dasar dari aliran darah dalam sistem kardiovaskular. Selain itu, algoritme dari pemodelan ini cukup sederhana sehingga memudahkan penerapannya dalam simulasi biomodeling denyut sebagai bagian dari upaya membantu pembelajar bedah kardiovaskular menganalisis kinerja jantung secara lebih baik lagi.
Implementasi Algoritme Long Short-Term Memory untuk Prediksi Harga Saham BBCA dan BBRI Zuzzaifa, Nur; Dwi Sancoko, Sulistyo
Jurnal Telematika Vol. 19 No. 2 (2024)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v19i2.701

Abstract

Berinvestasi dalam instrumen saham memiliki tingkat risiko yang tinggi. Hal ini terjadi karena pergerakan saham pada pasar sulit diprediksi. Analisis data historis dapat menjadi solusi para investor dalam meramalkan pergerakan harga saham di masa mendatang. Selain meningkatkan kesadaran akan pentingnya investasi, teknologi juga membantu dalam pengambilan keputusan. Penelitian ini memprediksi harga saham menggunakan algoritme Long Short-Term Memory (LSTM). Data yang digunakan diambil dari website Yahoo Finance, variabel yang digunakan hanya data penutupan (close) saham. Tahapan-tahapan yang dilakukan, seperti studi literatur, pengumpulan data, pembagian data, preprocessing data, pembentukan model, denormalisasi, dan evaluasi. Dari model yang dibangun didapatkan hasil paling optimal pada PT Bank Rakyat Indonesia, Tbk. (BBRI) dengan nilai RMSE data pelatihan sebesar 37,037 dan RMSE data pengujian sebesar 80,128. Sementara itu, pengujian menggunakan algoritme LSTM pada PT Bank Central Asia, Tbk. (BBCA) didapatkan nilai RMSE data pelatihan sebesar 36,905 dan RMSE data pengujian sebesar 99,9. Selanjutnya, model terbaik digunakan untuk memprediksi harga saham PT BCA dan PT BRI dalam sebulan ke depan.

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