cover
Contact Name
Helmy, S.T., M.Eng
Contact Email
jaict@polines.ac.id
Phone
+62811278186
Journal Mail Official
jaict@polines.ac.id
Editorial Address
Program Studi Teknik Telekomunikasi Jurusan Teknik Elektro Politeknik Negeri Semarang Jl. Prof. H. Soedarto, S.H. Semarang
Location
Kota semarang,
Jawa tengah
INDONESIA
Journal of Applied Information, Communication and Technology (JAICT)
ISSN : 25416340     EISSN : 25416359     DOI : https://doi.org/10.32497/jaict
Core Subject : Engineering,
Focus of JAICT: Journal of Applied Information and Communication Technologies is published twice per year and is committed to publishing high-quality articles that advance the practical applications of communication and information technologies. JAICT scope covers all aspects of theory, application and design of communication and information technologies, including (but not limited): Communication and Information Theory. Mobile and Wireless Communication, Cognitive Radio Networks. Ad Hoc, Mesh, Wireless Sensor Network, Distributed System and cloud computing Computer networking and IoT Optimization Algorithms, Artificial intelligence, Machine Learning, and Adaptive System.
Articles 5 Documents
Search results for , issue "Vol 8, No 2 (2023)" : 5 Documents clear
Optimizing Call Setup Success (CSSR) Parameters In Mobile Communications Using K-Nearest Neighbor (K-NN) Hutama Arif Bramantyo; Irfan Mujahidin
JAICT Vol 8, No 2 (2023)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v8i2.5084

Abstract

The evaluation of the mobile communication network inside the cellular communication system, often known as the Global System for Mobile Communication, is crucial to achieve optimal call quality. The Call Setup Success Rate (CSSR) is a measure that plays a significant role in determining the performance of the mobile network, alongside various other factors. The mobile network's performance may decrease if the Call Setup Success Rate (CSSR) number is below the expected standard. The CSSR outcome is influenced by multiple variables that lack a specific formula or exhibit no discernible relationship with one another. The individual responsible for optimizing decisions in the real case is an operator or an engineer who relies on their experience to inform their choices. Nevertheless, even those with previous expertise in this domain may encounter difficulties determining the most effective approach for optimizing CSSR parameters since they must consider the interconnections among the many inherent values in these parameters. In order to achieve this objective, it is necessary to employ pattern recognition algorithms, among which the k-nearest Neighbor (k-NN) technique is included. In this study, the k-nearest Neighbor method will be employed to assist novice engineers in determining the optimization method for enhancing CSSR performance. Certain data from the OMC-R are utilized for the purpose of enhancing the performance of the CSSR and determining the feasibility of employing the k-NN pattern recognition approach to improve the CSSR. The efficacy of the k-Nearest Neighbors (k-NN) algorithm in providing an optimal solution, as determined by the operator or engineer on behalf of the telecommunication service provider, serves as a key indicator of the system's overall success. The implementation of CSSR optimization utilizing the k-NN algorithm decision has achieved a successful outcome, with 89.65% of the total data being accurately processed.
Wireless Network Channel Interference for Mobile Communication: a Systematic Literature Review and Research Agenda Irfan Mujahidin; Ivandi Julatha Putra
JAICT Vol 8, No 2 (2023)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v8i2.4671

Abstract

The development and renewal of wireless technology is currently a necessity. Wifi technology has now reached wifi 6. Network infrastructure is currently the main thing in the process of distributing data using wireless media to mobile phone or laptop users. By looking at the need for wireless in offices, schools, public places, hospitals, and indoor or outdoor buildings that use a large number of access point devices. Based on a review of existing research obtained problems and opportunities for development, this literature study taken from 25 journal articles aims to be able to plan the construction of wireless network infrastructure so that channel interference does not occur. Research on wireless network channel interference has been carried out in several scenarios, for example, by increasing the number of wireless networks in adjacent areas, providing obstacles, and managing different channels. The eight most common methods used in wireless network channel interference research are descriptive analysis, comparative study, method analysis, model development, case studies, regression models, literature studies, and optimization. Research related to wireless network channel interference can still be further developed by using the latest wireless technology which can simultaneously test existing channel interference
Classification of Type 2 Diabetes using Decission Tree Algorithm Ivandari Ivandari; Much. Rifqi Maulana; M Adib Al Karomi
JAICT Vol 8, No 2 (2023)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v8i2.4835

Abstract

Diabetes is a disease that causes many deaths. According to data from WHO, in 2019 there were 2 million deaths due to diabetes. The recording of the patient's condition has been carried out for medical purposes. The large number of records that are only used as stored data will only later become digital waste. Data mining offers a classification process to process data into new knowledge. The recognition of new patterns from existing data results from algorithmic calculation processes as well as statistics. This study uses the type 2 diabetes dataset from the uci repository which was released in 2020. Previous research was conducted using the KNN algorithm with an accuracy rate of 92.5%. For numerical datasets, the decision tree algorithm is proven to be superior and can represent it in a language that is easy for humans to understand. One of the best and widely used classification algorithms for high-dimensional datasets is the decision tree. The results showed that the accuracy of the decision tree algorithm for type 2 diabetes data classification was 95.96%. Another output of this study is a decision tree from the early stage diabetes risk prediction dataset.
Design of VHF Directional Antenna on Class B Automatic Identification System (AIS) for Vessel Traffic Monitoring Eko Supriyanto; Abu Hasan; Hutama Arif Bramantyo; Hanny Nurrani
JAICT Vol 8, No 2 (2023)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v8i2.5017

Abstract

The majority of Automatic Identification System (AIS) equipment used on ships, harbormasters, and monitoring stations utilizes antennas that possess an omnidirectional beam pattern, covering all directions in a 360-degree range. One limitation inherent to omnidirectional antennas is their susceptibility to signal dispersion, resulting in suboptimal signal gain in certain directions. In the context of using omnidirectional antennas at Port AIS stations or other Monitoring Stations situated in expansive terrestrial regions, it is observed that the monitoring range is reduced. The objective of this study is to develop a prototype of a directional antenna capable of enhancing the monitoring range of ship traffic monitoring stations in alignment with the specific direction requested by land-based monitoring stations. The approach being utilized is the prototype method. This methodology encompasses the sequential steps of data collection, material and issue identification, planning, modeling, building, testing, and implementation.
Performance Evaluation a High gain 16dB Square 4x4 Array design Microstrip Antenna for Communication System Irfan Mujahidin
JAICT Vol 8, No 2 (2023)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v8i2.5080

Abstract

The increased gain in the antenna of the directional radiation pattern microstrip design using the 4x4 element array method was proposed in this study. The proposed antenna is designed to work in the frequency range of 11300 – 11650 MHz for wearable communication systems using microwave radio transmission channels. To increase gain, the proposed antenna in optimization uses an array with 4x4 elements. From the results of the design structure, a return loss value of -35.61 dB and a VSWR of 1.1227 was obtained. The resulting bandwidth of a 4x4 element array antenna is 250. the impedance of 50.77 + h 2.88 Ω at a working frequency of 11.5GHz. The gain of the 4x4 element array antenna is 16.25 dB at a working frequency of 11500 MHz, and its maximum gain is 16.5 dB at a working frequency of 11700 MHz. Optimization with the 4x4 element array method managed to increase Gain up to 65.76% compared to the 2x2 element array design. The proposed antenna is suitable as a candidate for use in microwave radio communication systems, IoT, and Wearable antennas.

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