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Helmy, S.T., M.Eng
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Journal of Applied Information, Communication and Technology (JAICT)
Published by Politeknik Negeri Semarang
ISSN : 25416340     EISSN : 25416359     DOI : https://doi.org/10.32497/jaict
Core Subject : Engineering,
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.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 95 Documents
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AUTOMATIC MANUAL SMART LIGHT CONTROL SYSTEM WITH STATUS FEEDBACK Samuel Beta; Fahmi Baihaqi; Ivandi Julatha
JAICT Vol 8, No 1 (2023)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v8i1.4452

Abstract

The need for light is one of the main needs for human life today. Advances in technology are very helpful in many aspects of life, especially in terms of light. Thanks to advances in technology, humans do not only rely on sunlight as a means of lighting their daily lives because lamps have been found as a substitute for lighting. Controlling the lights manually certainly has drawbacks as is often the case in this village where the owner often leaves the house with the lights on, this can cause a waste of electricity and short circuits can occur in the lights if they are constantly on. Where researchers use applied research methods which are research methods that are carried out with the intention of implementing, testing, and evaluating the ability of a theory that is applied in solving practical problems. However, researchers also use IoT (Internet of Things) technology and Internet Messenging applications, namely Telegram. Where this IoT technology is a technology that utilizes the internet network connected to a network of lights through a sensor, namely the NodeMCU Esp8266 Microcontroller. While the Telegram application is used as an aid to make it easier to monitor or control both turning on and off the lights remotely using the application, the Telegram application also sends feedback on the status of the lights. From the results of this study, it can be expected that this control system can assist in controlling or controlling lights easily and practically over long distances using the telegram application..
PROTOTYPE AIR CONDITIONING MONITORING AND CONTROL SYSTEM FOR SMART CLASSROOM BASED ON THE INTERNET OF THINGS samuel beta; rindang reynaldi; gisnaya faridatul avisyah
JAICT Vol 8, No 1 (2023)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v8i1.4444

Abstract

Electricity wastage is a growing concern, often resulting from human behavior. One common scenario is the continuous operation of a high-powered air conditioner (AC) even when it's unnecessary. Moreover, extended AC usage can accelerate wear and tear, potentially damaging the unit. To address these issues, a remote monitoring and control device based on the Internet of Things (IoT) concept is crucial. This device can connect to smartphones, allowing users to remotely monitor and control AC usage. Through an AC simulator, the system enables monitoring and control via a telegram system linked to the smartphone. Developed using the waterfall method and utilizing the NodeMCU ESP8266 microcontroller, the prototype proves effective in assisting users in monitoring and controlling AC usage. Particularly useful when users are away from the AC location and inadvertently forget to turn it off, the system mitigates unnecessary electricity wastage. By implementing this solution, energy efficiency is promoted, and the lifespan of AC units is extended. With the potential to reduce electricity wastage, this technology contributes to a more sustainable future.
Cyber-bullying Detection based on Machine Learning Method (Case Study: Instagram Comment Section) Eri Eli Lavindi
JAICT Vol 8, No 1 (2023)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v8i1.4339

Abstract

Social media is popular communication platform for last decade. Social Platform such as Facebook, Instagram, and Twitter provide real-time and efficient way of communication overseas. The ease of using social media does not only provide positive benefits, but can also have a negative impact on its users. One of social media negative impact is cyber-bullying which define as a type of harassment through online media. The effect of cyber-bullying to the victim particularly is mental health disorder. Usually, being the victim of cyber-bullying can increase the stress and anxiety level, lower self-esteem, loneliness, sadness, and disappointment. This study evaluates the comment on Instagram post of Indonesia influencer to determine whether it classified as bullying or non-bullying. This study utilizes count vectorizer as feature extraction and compare several machine learning methods such as Naïve Bayes, SVM, and Random Forest. The evaluation result show that both Naïve Bayes and Random Forest are able achieve 77% accuracy. Moreover, Naïve Bayes method also generate higher percentage compared to other methods. This result indicate that Naïve Bayes are capable in detecting cyber-bullying comment in social media platform.
Optimizing Call Setup Success (CSSR) Parameters In Mobile Communications Using K-Nearest Neighbor (K-NN) Bramantyo, Hutama Arif; Mujahidin, Irfan
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 Mujahidin, Irfan; Putra, Ivandi Julatha
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; Maulana, Much. Rifqi; Al Karomi, M Adib
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 Supriyanto, Eko; Hasan, Abu; Bramantyo, Hutama Arif; Nurrani, Hanny
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 Mujahidin, Irfan
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.
Quick Response Anti-Theft Measures in Jewelry Stores and Banks Utilizing the Internet of Things Widodo, Sarono; Bramantyo, Hutama Arif; Wardihani, Eni Dwi; Yulianto, Taufiq; Helmy, Helmy; Wasito, Endro; Daffa, Muhammad; Yuliana, Lutfi
JAICT Vol. 9 No. 1 (2024)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v9i1.5113

Abstract

The act of theft is a prevalent criminal activity within society, particularly observed in financial institutions and jewelry establishments, owing to the significant economic worth associated with valuable assets like currency, gold, and diamonds. Certain locations lack an integrated security system that interfaces with law enforcement, hence posing challenges for victims to report criminal incidents, particularly in cases involving armed or violent attackers. Hence, the purpose of this final project tool is to streamline and expedite theft reporting by leveraging the capabilities of the Internet of Things. This tool gathers empirical data in the form of visual representations, geographical coordinates, and temporal information pertaining to an incident. The development process employs the waterfall methodology, characterized by an average data transmission speed of 21.5 seconds and a database-to-telegram latency time of around 3.85 seconds. The complete duration encompassing the stages of detection and subsequent notification via telegram amounts to approximately 25.35 seconds. The test results indicate a location tolerance of around 5-10 meters relative to the test spot.
Improving the Accuracy of the C45 Classification Algorithm Using Information Gain Ratio Feature Selection for Classification of Type 2 Diabetes Mellitus Disease Ivandari, Ivandari; Maulana, Much. Rifqi; Kurniawan, Ichwan; Al Karomi, M Adib
JAICT Vol. 9 No. 2 (2024)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v9i2.5845

Abstract

Abstract”” Diabetes is a disease that can cause death. Diabetes can cause heart failure, chronic kidney disease, glaucoma that attacks the eyes and several other diseases. WHO data states that there were more than 2 million deaths due to diabetes in 2019. Data from the International Diabetes Federation shows that around 537 adults are recorded as living with diabetes. This condition must be treated immediately, considering that diabetes is one of the most deadly non-communicable diseases in the world. Patient registration is mostly done in hospitals. A lot of data will only become digital waste if it does not have more benefits. In 2020 Diabetes and Hospital in Sylhet donated patient data for further research. This data contains 520 patient records with 17 attributes that have been validated by specialist doctors. Early stage diabetes risk prediction data is released by the uci repository as public data and can be used for research testing. Research using this dataset has been widely carried out with the previous best accuracy level of 95.96%. In previous studies, all attributes were used in the classification process. The number of irrelevant attributes can affect the performance of the classification algorithm. This study uses the information gain ratio for feature selection of the early stage diabetes risk prediction dataset. The C45 algorithm is used for classification, evaluation using confusion matrix and validation using 10 folds cross validation. The results of this study improve the performance of C45 so that it obtains an accuracy level of 96.15%. This study also produces a decision tree for diabetes..

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