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Buletin Pos dan Telekomunikasi
Published by Kementerian Komunikasi dan Informatika
ISSN : 16930991     EISSN : 24431524     DOI : https://doi.org/10.17933/bpostel
Core Subject : Economy, Science, Social, Engineering,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Social Sciences
Scientific work/Manuscript that can be published in the Buletin Pos dan Telekomunikasi is in the form of academic papers, research reports, surveys, research briefings, and degree theses, analysis of secondary data, thoughts, theoretical/conceptual/methodological reviews in the field of: Post: including policy, technology and standardization of postal equipments and services. Telecommunications: including policy, standardization, market, resources, security, infrastructure and technology either wireless or wired telecommunications, both voice and data communications.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 6 Documents
 1 
Search results for , issue "Vol. 22 No. 1 (2024): June 2024" : 6 Documents clear
Comparison of Supervised Learning Methods for Spatial User Clustering in Downlink NOMA Hurianti Vidyaningtyas; Iskandar; Hendrawan; Pramudita, Aloysius Adya
Buletin Pos dan Telekomunikasi Vol. 22 No. 1 (2024): June 2024
Publisher : Centre for Research and Development on Resources, Equipment, and Operations of Posts and I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17933/bpostel.v22i1.385

Abstract

The performance of Power Domain Non-Orthogonal Multiple Access (PD-NOMA) is affected by the performance of Successive Interference Cancellation (SIC) in decoding user data. The large number of users will cause error propagation in SIC, which results in decreased SIC performance. This research aims to optimize the performance of SIC in PD-NOMA by applying spatial concepts to classify users. This research applies various supervised machine learning classification algorithms, including Decision Tree, K-Nearest Neighbors (K-NN), Support Vector Machine (SVM), Random Forest, Logistic Regression, and Naive Bayes. The experimental results show that Random Forest achieves the highest accuracy in classifying users, followed by Decision Tree. In addition, in performance measurement using ROC (Receiver Operating characteristic) and AUC (Area under the Curve) curves, the Random Forest method achieved the best results. In terms of experimentation process time, a decision tree has a faster time compared to a random forest. Overall, the Random Forest algorithm is suitable for the task of user clustering in the context of PD-NOMA, which utilizes the spatial concept from user to base station (BS).
Using the Eisenhower Matrix to Identify Open Government Data Parameter Towards Information Disclosure in Indonesia Herma Adis; Catur Apriono
Buletin Pos dan Telekomunikasi Vol. 22 No. 1 (2024): June 2024
Publisher : Centre for Research and Development on Resources, Equipment, and Operations of Posts and I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17933/bpostel.v22i1.387

Abstract

The openness of government data is considered essential and is an influential innovation in society to prevent corruption by increasing the transparency of information and data. One of the drivers for the emergence of Open Government Data (OGD) is the Industrial Revolution 4.0 era, which has influenced all aspects of life with all technological advances. Society needs open information to support and monitor the running of Government. However, it still needs to be determined whether the published OGD data is actual data or only data presented to cancel obligations to protect certain powers. From here, the author wants to conduct a study on OGD parameters using the Eisenhower matrix after reviewing several experts in the telecommunications sector as a basis for identifying parameters for the openness of information and government data in Indonesia. From the results of the analysis that we have carried out, it is found that government support is the highest parameter, followed by other parameters, namely policy, data transparency in the OGD portal, and the participation of citizens as the most crucial support in supporting the implementation of quality and quality OGD data publication in Indonesia. So, the final aim of this study is to provide a future view for all policies that will be made by the Government related to OGD to include all parameters that support data transparency that can be used optimally by the general public so that actual data publication is achieved that does not protect authority or specific power.
Hyperparameter Optimization of Random Forest Algorithm to Enhance Performance Metric Evaluation of 5G Coverage Prediction Hajiar Yuliana; Iskandar; Hendrawan; Basuki, Sofyan; Hidayat, M. Reza; Charisma, Atik; Vidyaningtyas, Hurianti
Buletin Pos dan Telekomunikasi Vol. 22 No. 1 (2024): June 2024
Publisher : Centre for Research and Development on Resources, Equipment, and Operations of Posts and I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17933/bpostel.v22i1.390

Abstract

Utilizing of 5G technology has become a major focus in the development of more advanced and efficient telecommunications networks. In this context, 5G coverage prediction becomes an important aspect in network planning to ensure optimal user experience. In this study, we explore the use of Random Forest algorithm to predict 5G coverage, with special emphasis on the hyperparameter optimization process to improve model performance. We conduct experiments with various hyperparameter combinations, including 'max_depth', 'max_features', 'min_samples_leaf', 'min_samples_split', and 'n_estimators', using hyperparameter optimization techniques. The results show that by paying attention to the optimal combination of hyperparameters, we managed to significantly improve the performance of the model. The optimized model produces a Minimum Root Mean Squared Error (RMSE) of 0.6, which is much better than the Random Forest model without hyperparameter optimization which has an RMSE of 1.14. The result of this study confirms the importance of the hyperparameter optimization process in improving the accuracy and consistency of the Random Forest model for 5G coverage prediction. The results have important implications in supporting the development of a successful 5G network infrastructure in the future.
Accurate, Fast and Low Computation Cost of Voice Biometrics Performance using Model of CNN Depthwise Separable Convolution and Method of Hybrid DWT-MFCC for Security System Haris Isyanto; Ibrahim, Wahyu; Samsinar, Riza
Buletin Pos dan Telekomunikasi Vol. 22 No. 1 (2024): June 2024
Publisher : Centre for Research and Development on Resources, Equipment, and Operations of Posts and I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17933/bpostel.v22i1.393

Abstract

Identity theft, a pervasive criminal risk in the digital realm, particularly in online transactions, demands innovative security solutions. Voice biometrics, a cutting-edge technology, have been developed to ensure the protection of one's identification. This study, a significant step forward, focuses on the development of voice biometrics using deep learning, specifically CNN Depthwise Separable Convolution (DSC) and CNN Residual. The research on these two systems was conducted to determine accuracy, performance evaluation, computing load, and training process time for effectively, rapidly, and accurately verifying user voice for banking transaction security. The initial CNN residual test yielded a high validation accuracy of 98.6345%. However, the large number of CNN residual parameters resulted in a training time of 7.37 seconds, increasing the computational workload. The second CNN DSC test exhibited a high validation accuracy of 98.3542%. The CNN DSC was successful in decreasing the parameter count, resulting in a reduction of 5.12 seconds in training time. Upon analyzing the test results, it is clear that the CNN DSC has superior performance, resulting in faster training times and less memory consumption. This effectively addresses the problem of high computational costs and significantly enhances user identity security in banking transactions, a crucial aspect of modern banking.
The Implementation of PWA (Progressive Web App) Technology in Enhancing Website Performance & Mobile Accessibility Ahyar Muawwal
Buletin Pos dan Telekomunikasi Vol. 22 No. 1 (2024): June 2024
Publisher : Centre for Research and Development on Resources, Equipment, and Operations of Posts and I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17933/bpostel.v22i1.395

Abstract

The implementation of PWA as a necessary feature aims to provide added value and enhance website performance. This is intended to address several common issues in websites, such as limitations in displaying pages offline and the cost of developing native applications across various operating system platforms, both for desktop and mobile devices. Data collection methods involve literature studies and direct measurements using various tools. Testing conducted includes installation testing, evaluation of PWA criteria, performance, size of transferred resources, and offline mode. Components used in PWA include the web app manifest, service worker, and cache storage. PWA implementation involves creating a web app manifest, service worker registration, service worker configuration, adding script tags, creating specific routes within the website using Express.js, and PWA testing. Test results indicate that the website can be installed and used effectively on various types of devices, both mobile and desktop, and can be accessed in offline mode or with unstable connections.
Reconfigurable Intelligent Surface-Assisted RF Wireless Power Transfer for Internet of Things System: Modeling and Evaluation Arif Abdul Aziz; Istiqomah; Suratman, Fiky
Buletin Pos dan Telekomunikasi Vol. 22 No. 1 (2024): June 2024
Publisher : Centre for Research and Development on Resources, Equipment, and Operations of Posts and I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17933/bpostel.v22i1.396

Abstract

This work studies the utilization of reconfigurable intelligent surfaces (RIS) for assisting radiofrequency (RF)-based wireless power transfer (WPT) in the Internet of Things (IoT) system. The RIS device in this system is utilized to provide the line of sight (LOS) path when an obstacle blocks the direct power transmission from the transmitter to the receiver. This work presents a comprehensive modeling of the RIS-assisted RF WPT for IoT systems, which includes the spatial model, the RIS-assisted RF WPT model, and the total receiver power model. The performance of RIS-assisted RF WPT is evaluated by simulation matched to the IoT system. In all simulation tests, the obstacle is located between the transmission and the receiver, eliminating direct power transfer. By simulation, it has been verified that the RIS device can assist the RF WPT in the IoT system. The receiver can achieve 0,4714% power transfer efficiency at a distance of 1 meter from the RIS device. Meanwhile, 0,0290% power transfer efficiency is achieved within a 15-meter distance from the RIS device. Furthermore, the performance of RIS-assisted RF WPT with various numbers of unit cells in the RF WPT system is investigated. It has been found that increasing the number of unit cells in RF WPT after a certain number is ineffective for the RF WPT in an IoT system

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