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Eko Fajar Cahyadi
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Jurnal INFOTEL
Published by Universitas Telkom
ISSN : 20853688     EISSN : 24600997     DOI : https://doi.org/10.20895/infotel.v15i2
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal INFOTEL is a scientific journal published by Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) of Institut Teknologi Telkom Purwokerto, Indonesia. Jurnal INFOTEL covers the field of informatics, telecommunication, and electronics. First published in 2009 for a printed version and published online in 2012. The aims of Jurnal INFOTEL are to disseminate research results and to improve the productivity of scientific publications. Jurnal INFOTEL is published quarterly in February, May, August, and November. Starting in 2018, Jurnal INFOTEL uses English as the primary language.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 11 Documents
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Search results for , issue "Vol 15 No 3 (2023): August 2023" : 11 Documents clear
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.
Ekstraksi Informasi Terkait Kebutuhan Perangkat Lunak dari Berita Daring dengan Menggunakan DomText-WMDS Mutia Rahmi Dewi; Indra Kharisma Raharjana; Daniel Siahaan; Nurul Jannah
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.v15i3.950

Abstract

Currently, there are not many studies that assess software requirements extraction from non-software artifacts. Most of the research in these related areas are focuses on software artifacts such as project descriptions or user reviews as a source of requirements extraction. This research aims to identify relevant information to the software requirements from online news using the vector space model. This software requirements-related information can assist systems analysts in discovering the problem domain based on the lesson learned presented by stakeholders in online news. This research proposes DomText-WMDS to extract requirements-related information from online news. We used online news and public software requirements specification dataset to develop software-specific vocabulary using domain specificity technique. Then we expanded the specific vocabulary software to obtain more comprehensive results by building vector space model from online news documents. This updated version of software-specific vocabulary can be used for basic filtering of software requirements-related information that previously extracted using the part-of-speech (POS) chunking. This study improved the performance for extracting software requirements-related information, with precision and recall 61.09% and 60.66% compared to domain specificity approach that only manages to obtain 43.34% and 40.78%.
A proposal for the regulation of the spectrum usage fee in 5G private network using fuzzy AHP Alfin Hikmaturokhman; Kasmad Ariansyah
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.v15i3.959

Abstract

This study evaluates the types of regulation models for The Indonesia Spectrum Usage Fee—the so-called Biaya Hak Pengguna (BHP) Frequency in 5G private network technology that are most suitable for implementation in Indonesia by implementing the Fuzzy Analytical Hierarchy Process (F-AHP) method. This method accommodates the opinions of telecommunications experts from mobile network operators (MNOs), regulators, vertical industries, and telecommunications consultants through a series of scientific steps to produce weights for each type of alternative solution offered. The results obtained show that the proposed model most suitable for implementation in Indonesia, taking into account the given criteria, is the one that uses unlicensed 5G frequencies. This model involves vertical industries not using licensed frequencies established by the government but rather choosing to use unlicensed frequencies to develop 5G technology for their own use. The implementation of this model is expected to encourage the optimization of regulation for Spectrum Usage Fee in 5G private network technology owned by the government, providing opportunities for vertical industries to develop 5G technology on private networks independently without relying on existing MNOs. This can stimulate innovation and technological progress in Indonesia to support Industry 4.0.
Genetic algorithm for finding shortest path of mobile robot in various static environments Dyah Lestari; Siti Sendari; Ilham Ari Elbaith Zaeni
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.v15i3.961

Abstract

In conducting their work in the industry quickly, precisely, and safely, mobile robots must be able to determine the position and direction of movement in their work environment. Several algorithms have been developed to solve maze rooms, however, when the room is huge with several obstacles which could be re-placed in other parts of the room, determining the path for a mobile robot will be difficult. This can be done by mapping the work environment and determining the position of the robot so that the robot has good path planning to get the optimal path. In this research, a Genetic Algorithm (GA) will be used to determine the fastest route that a robot may take when moving from one location to another. The method used is to design a mobile robot work environment, design genetic algorithm steps, create software for simulation, test the algorithm in 6 variations of the work environment, and analyze the test results. The genetic algorithm can determine the shortest path with 93% completeness among the 6 possible combinations of the start point, target point, and position of obstacles. The proposed GA, it can be argued, can be used to locate the shortest path in a warehouse with different start and end points.
Bahasa Inggirs Salwa Salsabila; Rina Pudjiastuti; Levy Olivia Nur; Harfan Hian Ryanu; Bambang Setia Nugroho
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.v15i3.962

Abstract

Massive MIMO Antenna Design results in a very large antenna size that hinders the design process. The arrangement of Massive MIMO Antennas which consists of many antenna elements is a challenge in the design process due to the limited capability of the simulation software and the complicated process. Thus, a scalability technique is used to predict the specification results produced by a Massive MIMO Antenna array with a certain configuration based on a simple MIMO Antenna array with a 2x2, 4x4, 8x8, 16x16 MIMO element configuration scheme, etc. exponential increments. This research will discuss the scaling process to predict the specifications of a Massive MIMO Antenna array. The designed MIMO antenna arrangement is based on the design of a rectangular antenna with a truncated corner and a circular antenna with an X slot for further design with various types of configurations that work at a frequency of 3.5 GHz.
Prediction of patient length of stay using random forest method based on the Indonesian national health insurance Aini Hanifa; Yogiek Indra Kurniawan; Jati Hiliamsyah Husen; Arief Kelik Nugroho; Ipung Permadi
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.v15i3.963

Abstract

Inpatient care is the largest component of healthcare service expenditure. Healthcare management plays a role in reducing expenditure costs and improving healthcare services. Identification of factors related to patient length of stay and accurate prediction of how long patients will be hospitalized becomes important to support stakeholder decision making. In this study, the length of stay for patients using BPJS insurance services was predicted using the random forest method. An experiment has been conducted to compare different numbers of trees and candidate split attributes in a prediction model. The experimental results showed that increasing the number of trees and candidate split attributes can improve prediction performance and reduce the resulting error rate. The optimal value was found when the number of trees was 100 with the MSE/Variance value of 0.3805. The main determinant variables for predicting patient length of stay were found to be the patient's disease diagnosis, participant segment, and healthcare facility type.
Klasifikasi Citra Medis Tumor Otak Menggunakan Algoritma Convolutional Neural Network Alwas Muis; Sunardi Sunardi; Anton Yudhana
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.v15i3.964

Abstract

Brain tumor is a disease that is very dangerous for humans where this disease really needs faster and more accurate treatment. This disease requires early detection because it requires fast and accurate medical treatment. Machine learning helps solve problems by leveraging deep learning technology in the branch of machine learning. Deep learning is a technology that can detect, classify, and segment various problems in machine learning. One of the methods used in deep learning is the Convolutional Neural Network. This method is most often used in performing image processing where this method has various types of feature extraction. The purpose of this study was to test the accuracy of using the Convolutional Neural Network method in classifying brain images. The brain image used in this study is an image scanned by Magnetic Resonance Imaging. The dataset in this study was downloaded from the Kaggle website as many as 7023 data consisting of four classes of brain image data, namely glioma, notumor, meningioma, and pituitary classes. The results of this study obtained an accuracy value of 84% so that this research can be used by medical personnel to diagnose brain tumors easily, quickly, precisely, and accurately.
Design of a microcontroller-based quadcopter prototype module Fly Sky XL163RX take off and landing Saragih, Yuliarman; Ibrahim, Ibrahim; Satrio Hadikusuma, Ridwan; Handayana, Kayat; Elisabet, Agatha
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.v15i3.966

Abstract

This research paper presents the design and development of a microcontroller-based quadcopter prototype module, named Fly Sky XL163RX, with the capability of take off and landing. The objective of this study is to design a reliable and efficient quadcopter module that can be utilized for various applications, such as aerial photography, surveillance, and delivery services. The proposed quadcopter module is equipped with the Fly Sky XL163RX microcontroller, which serves as the control unit for managing the flight operations. The design process involves several key steps, including the selection of appropriate components, integration of sensors and actuators, and the development of control algorithms. The quadcopter module utilizes a combination of sensors, including gyroscopes, accelerometers, and altimeters, to gather real-time data and stabilize the flight. The control algorithm employs a proportional-integral-derivative (PID) controller to adjust the motor speeds and maintain stability during take off and landing. The Fly Sky XL163RX microcontroller offers a user-friendly interface and supports various communication protocols, allowing for easy customization and control of the quadcopter module. Additionally, the module incorporates safety features, such as emergency landing capabilities and collision avoidance systems, to enhance flight security and prevent potential accidents. The performance of the Fly Sky XL163RX quadcopter module was evaluated through extensive flight testing. The results demonstrate the module's capability to achieve stable take off and landing operations, as well as its responsiveness to user commands. The module's compact size and lightweight design make it suitable for indoor and outdoor applications. In conclusion, this research presents the design and development of the Fly Sky XL163RX microcontroller-based quadcopter module, which exhibits reliable and efficient take off and landing operations. The module's integration of sensors, control algorithms, and safety features contribute to its overall performance and usability. Future work may focus on enhancing the module's capabilities, such as implementing autonomous flight modes and improving battery efficiency.Quadcopter, Microcontroller, FlySky XL163RX, Take Off, Landing, Control Algorithm, Sensors, Actuators, PID Controller, Flight Testing, Aerial Applications.
Design of machine learning-based water quality prediction system with recursive feature elimination cross-validation James Julian; Annastya Bagas Dewantara; Fitri Wahyuni
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.v15i3.977

Abstract

Lack of clean water has become a problem in the world, and it is estimated that by 2025 there will be 2.8 billion people who will experience a shortage of clean water. The high demand for clean water and the limited water sources with proper potency is one of the main reasons for the need for a device capable of measuring the potability level of water that is flexible to carry and does not require high costs in the manufacturing process. In this paper, the design of machine learning-based potability devices with recursive feature elimination with cross-validation (RFECV) is carried out as a guide in making the design of a water potability detection system, and the results obtained from RFECV with the Random Forest (RF) algorithm have a higher accuracy value. 15.71% better than the RF model, 6.85% better than the Support Vector Machine (SVM) model, and 8.57% better than the Artificial Neural Network (ANN) model trained without RFECV. The water potability prediction system's design selection is based on feature elimination results in the RFECV process. It is based on a literature review on device selection. The proposed water potability detection system consists of ESP32 as the primary computing device, electrochemical spectroscopy-based Al/PET sensor to detect sulfate values with a sensitivity of 0.874 Ω/ppm, PH4502C as a pH measuring instrument with an accuracy of up to 98.10%, WD-35802-49 electrode. as a device for measuring hardness in water with a measurement range of 0.4 – 40,000 ppm, a total dissolved solids sensor to determine the solids content in water with an accuracy of up to 97.80%, as well as a carbon-based sensor for measuring chloramines with a reading capacity of 186 nA/ppm.
Penyempurnaan Sistem Inkubator Bayi Berbasis FLC Menggunakan Algoritma Genetika Setiyo Budiyanto; Lukman Medriavin Silalahi; Dadang Gunawan; Erry Yulian Triblas Adesta
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.v15i3.991

Abstract

This research problem focuses on treating premature babies due to hypothermia so that the baby must be put in an incubator for several days. Conventional intensive care method in premature babies, namely skin-to-skin care method between mother and child. Meanwhile, the latest technological developments, the method is already based on electrical-Internet of Things (IoT) engineering. This research proposes the design of an IoT-based prototype known as a smart incubator. This prototype has been equipped with a real-time monitoring system and system settings using the mamdani fuzzy inference system control method and combined using the Genetic Algorithm (GA) method. The results showed that the ideal temperature range in the smart incubator was 33° C with an accuracy of 99.97% and was in accordance with the fuzzy membership degree in the range of 29° C ≤x≤ 37° C. Furthermore, the ideal relative humidity range in the smart incubator was 60% with an accuracy of 98.60% and was in accordance with the fuzzy membership degree in the range of 59 ≤x≤ 65. Then, the noise range in the smart incubator is 37.9dB to 56.8dB with an accuracy of 96.44% and has been appropriate at the fuzzy membership degree. At a maximum distance of 50cm, it takes 8 seconds for the prototype to detect movement as a safety measure.

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