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All Journal Jurnal Jaringan Telekomunikasi
Yoyok Heru Prasetyo
State Polytechnic of Malang
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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The Implementation of Dispersion Effect on Rise Time Budget and Power Link Budget on Optical Links at PT Telkom Akses Rungkut Surabaya Website Based Rafidatus Sabrina; Abdul Rasyid; Yoyok Heru Prasetyo
Jurnal Jaringan Telekomunikasi Vol 12 No 2 (2022): Vol. 12 No. 02 (2022) : June 2022
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jartel.v12i2.308

Abstract

Along with the development of an increasingly rapid era, it is directly proportional to the development of technology. Optical fiber is a transmission medium used in telecommunications. The quality of information transmissions through this cable transmission medium is influenced by a number of variables, including attenuation and dispersion. The rising time budget value is determined by the dispersion, and the power link budget is determined by measuring the attenuation that influences the light's path during data transmission and causes dispersion. The results showed that the chromatic dispersion value of the measurement results on this optical link was influenced by bending, the length of the distance on the path, the splicing of optical fibers, and due to the deployment of optical fibers. The system still performs at the required levels, i.e., at a power link budget of less than -15 dBm and a rise time budget of less than 70 ps, hence the optical link results have no impact on the system's performance. The results of the implementation of the website in this study display the results of measurements and calculations that were previously carried out where the results of these measurements and calculations can be seen in a table that has been integrated between databases to store data values ??with an online map which is then displayed the value on the map or online maps on the website containing data from the measurement results and parameter calculations on optical fiber owned by PT. Telkom Access.
RTSP and HTTP Protocol Analysis for Streaming Services on Manet Networks in State Polytechnic of Malang Mohamad Iqbal Maulana Firmansyah; Nugroho Suharto; Yoyok Heru Prasetyo
Jurnal Jaringan Telekomunikasi Vol 12 No 3 (2022): Vol. 12 No. 03 (2022) : September 2022
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jartel.v12i3.473

Abstract

To facilitate learning with video streaming, a transport protocol that can send video is needed, such as HTTP (Hyper Text Transfer Protocol) or RTSP (Real Time Streaming Protocol). Both protocols have their respective advantages and disadvantages when sent over a MANET network. One of them is that the throughput on RTSP is greater but the use of memory is more, this is inversely proportional to the RTSP protocol. In this study, the delay value in scheme 1 HTTP and RTSP protocols has an average delay of 23.225 seconds and 19.075 seconds. The throughput has an average value of 699.165 kbps and 802.656 kbps. Packet loss has an average value of 0.428% and 17.9%. For the use of transmit power nodes have an average of -33 dBm and -31.25 dBm. Memory usage has an average value of 108.46 Mb and 149.6 Mb.While in scheme 2 the delay values for HTTP and RTSP protocols are 28 seconds and 26.1 seconds on average. Throughput 1186,803 kbps and 1316,076 kbps. Packet loss has an average value of 0.0325% and 18.69%. On the use of transmit power nodes have an average of -34 dBm and -32 dBm. Memory usage has an average value of 107.525 Mb and 154.275 Mb.
Navigation and Guidance for Autonomous Quadcopter Drones Using Deep Learning on Indoor Corridors Ahmad Wilda Yulianto; Dhandi Yudhit Yuniar; Yoyok Heru Prasetyo
Jurnal Jaringan Telekomunikasi Vol 12 No 4 (2022): Vol. 12 No. 04 (2022) : December 2022
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jartel.v12i4.422

Abstract

Autonomous drones require accurate navigation and localization algorithms to carry out their duties. Outdoors drones can utilize GPS for navigation and localization systems. However, GPS is often unreliable or not available at all indoors. Therefore, in this research, an autonomous indoor drone navigation model was created using a deep learning algorithm, to assist drone navigation automatically, especially in indoor corridor areas. In this research, only the Caddx Ratel 2 FPV camera mounted on the drone was used as an input for the deep learning model to navigate the drone forward without a collision with the wall in the corridor. This research produces two deep learning models, namely, a rotational model to overcome a drone's orientation deviations with a loss of 0.0010 and a mean squared error of 0.0009, and a translation model to overcome a drone's translation deviation with a loss of 0.0140 and a mean squared error of 0.011. The implementation of the two models on autonomous drones reaches an NCR value of 0.2. The conclusion from the results obtained in this research is that the difference in resolution and FOV value in the actual image captured by the FPV camera on the drone with the image used for training the deep learning model results in a discrepancy in the output value during the implementation of the deep learning model on autonomous drones and produces low NCR implementation values.
Co-Authors Abdul rasyid Ahmad Wilda Yulianto Dhandi Yudhit Yuniar Mohamad Iqbal Maulana Firmansyah Nugroho Suharto Rafidatus Sabrina