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Zurnawita Zurnawita

Jurusan Teknik Elektro Politeknik Negeri Padang

Author-ID : 429335

Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Social Sciences Other

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The Influence of Physical Tuning Technology on Voice Over LTE (VoLTE) zurnawita, zurnawita; Chandra, Dikky; zulya, fajru ju
JITCE (Journal of Information Technology and Computer Engineering) Vol 8 No 2 (2024): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.8.2.58-66.2024

The Long-Term Evolution (LTE) technology is currently evolving in the cellular communication system. Currently, LTE technology is only used for faster internet data activities. Unfortunately, phone calls still rely on second-generation (2G) or third-generation (3G) networks. To improve the quality of voice calls, one of the ways is through the utilization of Voice Over LTE (VoLTE) technology. The reason for using VoLTE in fourth-generation (4G) networks includes the voice quality based on Internet Protocol (IP). This study analyzes the performance of VoLTE technology networks. Based on the data collected, the Reference Signal Received Power (RSRP) with a percentage of 37.73% falls into the Good category, Signal to Interference Noise Ratio (SINR) with a percentage of 55.32% falls into the Fair category, and Throughput with a percentage of 66.16% falls into the Poor category. In terms of delay, it has a score of 4, categorized as very good, jitter has a score of 3, categorized as good, and packet loss has a score of 4, categorized as very good. The optimization results using physical tuning show that the Reference Signal Received Power (RSRP) falls into the Good category with a percentage of 52.8%, Signal to Interference Noise Ratio (SINR) falls into the Good category with a percentage of 70%, and Throughput falls into the Very Good category with a percentage of 64.50%.

The Influence of Physical Tuning Technology on Voice Over LTE (VoLTE) zurnawita, zurnawita; Chandra, Dikky; zulya, fajru ju
JITCE (Journal of Information Technology and Computer Engineering) Vol. 8 No. 2 (2024)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.8.2.58-66.2024

The Long-Term Evolution (LTE) technology is currently evolving in the cellular communication system. Currently, LTE technology is only used for faster internet data activities. Unfortunately, phone calls still rely on second-generation (2G) or third-generation (3G) networks. To improve the quality of voice calls, one of the ways is through the utilization of Voice Over LTE (VoLTE) technology. The reason for using VoLTE in fourth-generation (4G) networks includes the voice quality based on Internet Protocol (IP). This study analyzes the performance of VoLTE technology networks. Based on the data collected, the Reference Signal Received Power (RSRP) with a percentage of 37.73% falls into the Good category, Signal to Interference Noise Ratio (SINR) with a percentage of 55.32% falls into the Fair category, and Throughput with a percentage of 66.16% falls into the Poor category. In terms of delay, it has a score of 4, categorized as very good, jitter has a score of 3, categorized as good, and packet loss has a score of 4, categorized as very good. The optimization results using physical tuning show that the Reference Signal Received Power (RSRP) falls into the Good category with a percentage of 52.8%, Signal to Interference Noise Ratio (SINR) falls into the Good category with a percentage of 70%, and Throughput falls into the Very Good category with a percentage of 64.50%.

A review of Image Processing Technique for Monitoring The Growth and Health of Cows Zurnawita, Zurnawita; Prabowo, Cipto; Kurnia, Rahmadi; Elfitri, Ikhwana
JITCE (Journal of Information Technology and Computer Engineering) Vol. 7 No. 01 (2023)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.7.01.8-18.2023

In general, monitoring of animal growth and health is done directly by farmers (invasive measurement methods) which can cause cows to be injured or experience stress. To avoid this, several studies have been conducted on non-invasive methods using image processing technology. In this study, we systematically reviewed several works of literature to identify and synthesize published articles on image processing technology and image processing applications related to weight estimation and individual cattle identification. Analysis of image processing technologies used for weight estimation and individual cattle identification is the main objective of this article. Articles were searched through several databases and studies that met the inclusion criteria were analyzed and used in the review. The studies were divided into three main themes: image processing technologies, applications using image processing, and image processing research on cattle growth and health. It can be concluded that deep learning approaches are increasingly being studied, tested and considered as a viable and promising approach to monitor cattle weight and health in several aspects

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Journal : Journal of Information Technology and Computer Engineering