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All Journal Transmisi: Jurnal Ilmiah Teknik Elektro Jurnal Ilmiah Dinamika Rekayasa (DINAREK) JURNAL MEDIA INFORMATIKA BUDIDARMA JTERA (Jurnal Teknologi Rekayasa) Jurnal RESISTOR (Rekayasa Sistem Komputer) TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) Journal of Telecommunication, Electronics and Control Engineering (JTECE) IJCOSIN : Indonesian Journal of Community Service and Innovation Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Jurnal INFOTEL
Kholidiyah Masykuroh
Institut Teknologi Telkom Purwokerto
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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Journal : Jurnal INFOTEL

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Sink position analysis of energy efficiency in Wireless Sensor Network (WSN) using routing Stable Election Protocol (SEP) Kholidiyah Masykuroh; Afifah Dwi Ramadhani; Islamianto Hudan Raharjo
JURNAL INFOTEL Vol 14 No 2 (2022): May 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v14i2.767

Abstract

Wireless Sensor Network (WSN) is a wireless network that involves sensors in the network. The sensor node on the WSN will collect data information from the environment around the sensor. However, each sensor node has storage capacity, processing power, communication range, and battery life limitations. The use of energy consumption from these factors is the main problem because each sensor node uses its power consumption from the battery. Stable Election Protocol (SEP) is a type of routing protocol on WSN that uses the clustering method. SEP has a function to extend the time interval before the first node dies. This research was carried out on the SEP protocol with alive node parameters, total initial energy, and stability. This study indicates that on a network that uses 100 nodes with sink positions (0, 100), two nodes are still alive and several nodes that are still alive in several sink positions that use 200 nodes. For networks where there is still a lot of energy remaining in the sink position (0, 100) with the network using 100 nodes and for networks using 200 nodes, the remaining energy is mainly in the sink position (100, 100). The highest stability period is in the sink position (50, 50) for networks using 100 nodes, and for networks using 200 nodes, the highest stability period is in the sink position (100, 50).
Studi Literatur dari Kompresi Video Berbasis Pembelajaran Kholidiyah Masykuroh; Eueung Mulyana
JURNAL INFOTEL Vol 15 No 3 (2023): August 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i3.943

Abstract

Developments in telecommunications technology today, such as cellular with the fifth generation (5G), the development of IoT prototypes, and the migration of analog TV to digital TV starting in 2022. The development of various research using machine learning. The problem with video format information is that the video file size is quite large, so the transmission process requires a large bandwidth. In addition, sharing services such as Video on Demand (VoD) and Video Broadcasting are sensitive to delay. In comparison, the transmission media has limited capacity, such as terrestrial TV, Ethernet/Fast Ethernet, and wireless cellular data such as 2G, 3G HSPA, 4G, etc. Based on reports from Cisco, the development of internet users has increased by 10% per year, with 80% of total traffic using video. Developments in various video compression standards, such as the most recent H.264 and H.265, produce high-quality, low-bitrate video. Much research has been carried out with various proposed compression methods based on machine learning. Either uses singular block learning based or end-to-end. This research focuses on the literature study of video compression with machine learning.
Co-Authors Achmad Ilham Imanuddin Afifah Dwi Afifah Dwi Ramadhani Afifah Dwi Ramadhani Andreas Rony Wijaya Anggih Wisnu Wardana Ariyatno Saputra Bongga Arifwidodo Danny Kurnianto Dini Megawati Eka Wahyudi Eueung Mulyana Farhan Ario Pamungkas Ferdy Rakhman Ibrahim Fikra Titan Syifa Imam Muhammadi Pradono Budi Irmayatul Hikmah Iryani, Nanda Islamianto Hudan Raharjo Izhanggani Izhanggani Mochammad Ikbal Nanda Rizqy Asshauf Muhamad Fahrul Rozi Nanda Iryani Nanda Iryani Novi Melawati Rahmat Widadi Rama Panji Prakoso Ramadhani, Afifah Dwi Retno Agustias Sarah Astiti S.Kom., M.MT Thirafi Dzaky Fadilah Ummi Athiyah