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Marlindia Ike Sari, S.T., M.T.
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International Journal of Applied Information Technology (IJAIT) Fakultas Ilmu Terapan Universitas Telkom; Gd. Selaru Lt. 3 - Jl. Telekomunikasi No. 1 Bandung
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IJAIT (International Journal of Applied Information Technology)
Published by Universitas Telkom
ISSN : -     EISSN : 25811223     DOI : https://doi.org/10.25124/ijait
Core Subject : Science,
Computer Science & IT
International Journal of Applied Information Technology covers a broad range of research topics in information technology. The topics include, but are not limited to avionics, bio medical instrumentation, biometric, computer network design, cryptography, data compression, digital signal processing, embedded system, enterprise information system, green energy & computing, interactive programming, internet of things, IT management and governance, IT-business strategic alignment, mobile and ubiquitous computing, monitoring system and techniques, multimedia processing, network security, power electronics, remote monitoring and sensing device, robotics and avionics, signal processing circuits, smart cities and smart grids, telecommunication devices & methods, telecommunication fundamentals.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 122 Documents
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A Comparison of The Predictive Ability between Logistic and Gompertz Model on COVID-19 Outbreak Tita Haryanti; Brian Pamukti
IJAIT (International Journal of Applied Information Technology) Vol 04 No 02 (November 2020)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v4i02.2909

Abstract

A predictive model can be learned using historical information. Thereafter, information about a running case is combined with a predictive model to estimate the case's remaining flow time. The predictive model is based on data from past events, which can be used to make predictions for current operating situations. For example, the case of coronavirus disease 2019 (COVID-19), which is currently infecting the whole world, including Indonesia, have influenced various aspects, ranging from the educational environment, business, economy, to the companies. Data scientists are urgently needed who can help organizations improve their operational processes. Therefore, this journal discusses the prediction of the peak number of COVID-19 cases in Indonesia, using two prediction models, logistic and Gompertz. The results obtained show that the Gompertz model has higher accuracy than the logistic model, with an accuracy of 99.85%. This journal's results are expected to help organizations estimate the time to rebuild themselves after being affected by COVID-19.
Implementation of Roll Control on Mini Remotely Operated Vehicle Andi Sugandi; Simon Siregar; Lisda Meisaroh
IJAIT (International Journal of Applied Information Technology) Vol 04 No 02 (November 2020)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v4i02.3437

Abstract

This paper describes the design and manufacture of an underwater explorer robot. The proposed Mini Remotely Operated Vehicle (ROV) is designed to be controlled remotely using a wireless communication module outside the water. ROV stability is needed to support the operation of ROV when do maneuvering in the water. The design of the ROV is aimed to maintain stability using a PID control system. Moreover, the gain PID values, kP gain, kI gain, and kD gain, must be set to perform roll stability. After performing a fine-tuning of the PID gain values, the experiment result shows that the system can maintain an average error of -1.70 degrees.
Analysis and Evaluation of User Acceptance on the Use of Enterprise Resource Planning (ERP) Systems at PT Trisco Tailored Apparel Manufacturing Alma Syafira; Warih Puspitasari; Wahjoe Witjaksono
IJAIT (International Journal of Applied Information Technology) Vol 04 No 01 (May 2020)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v4i01.2852

Abstract

Enterprise Resource Planning is a system that connects business areas, which benefits companies by increasing productivity, reducing costs, and simplifying business processes. However, it also found a case that considers the use of ERP systems to fail. Therefore, the use of ERP systems needs to be optimized, one of which is in terms of users. This research will be analyzed and evaluated the factors that influence user acceptance using the TAM2 model. The variables used are 11 variables in TAM2, including moderator variables. This research was conducted at PT Trisco Tailored Apparel Manufacturing, with a sample of 43 and an online questionnaire as a data collection method. Data processing using SmartPLS. The analysis conducted in the analysis of inner models such as validity and reliability tests, and analysis of inner models such as the coefficient of determination and path coefficient. The final step is testing the hypothesis with the bootstrapping method. The results obtained are the most significant factor is the image of the perceived usefulness, then the perceived usefulness of the intention to use the system. It has also found that if the system were mandatory, voluntariness would not be significant. Therefore, the results of this study can use as a source of evaluation for the company.
Study of Internet and Social Media Addiction in Indonesia during Covid-19 Setia Juli Irzal Ismail; Toni Kusnandar; Yeni Sanovia; Ratna Mayasari; Ridha Muldina Negara; Dimitri Mahayana
IJAIT (International Journal of Applied Information Technology) Vol 04 No 02 (November 2020)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v4i02.3423

Abstract

Since February 2020, Indonesia was struck by the Covid-19 pandemic. This led to the imposition of Large-scale Social Restrictions. The government issued a policy of working from home, learning from home, and worshiping at home. To carry out their activities from home, people are becoming increasingly dependent on the internet. With the increasing use of the internet during this pandemic, we are conducting a study on whether there is a phenomenon of internet addiction and social media in Indonesia. A survey of 2309 respondents from 31 provinces in Indonesia using Kimberley Young's Internet Addiction Test (IAT) has been conducted. After the data cleaning process to remove redundant data, only data from 2206 respondents were analyzed further with the binary logistic regression method. 25% of respondents were indicated with Internet addiction. High school students and college students tend to have a 1.7% higher risk of addiction. The length of time accessing e-commerce web and social media also increases the risk of internet addiction. YouTube and Instagram are social media applications that tend to pose a risk of addiction to respondents. A critical analysis of the Internet Addiction Test from a Philosophy of Science perspective was conducted. Finally, we formulate recommendations on strategies the government and society could take in dealing with the problem of internet addiction.
Android-Based Geolocation Technology on a Blood Donation System (BDS) Using the Dijkstra Algorithm Syaiful Ahdan; Setiawansyah Setiawansyah
IJAIT (International Journal of Applied Information Technology) Vol 05 No 01 (May 2021)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v5i01.3317

Abstract

Blood transfusion is an activity that is often carried out in order to save human life. The availability of appropriate bloodstock is crucial for use during special medical conditions. Therefore, the blood collection center must ensure availability; therefore, it needs to recruit active blood donors, difficult patients to find blood stocks, which will be discussed in this study. The contribution of this research is to design an information system that can find blood donors in the Bandar Lampung area with geolocation technology and use the Dijkstra algorithm to determine the closest route, with a system developed on the Android platform. The system can recommend donors to patients who need blood according to the patient's qualifications. Results obtained are an android-based mobile application that can search for geolocation-based blood donors using the Dijkstra algorithm, which can map the location of the nearest blood donor based on the patient's location. Based on data obtained from the results of system testing on functionality and usability, the system can map the location of blood donors and provide blood donor recommendations for patients in need. System testing is carried out using the ISO 9126 standard using the usability aspect, which consists of four test characteristics: the understanding aspect, the learning aspect, the ability aspect, and the operability aspect, and the attractiveness aspect.
Building Private Blockchain For Recording Student Values Data in Environment Faculty of Engineering at Universitas Muhammadiyah, Ponorogo Aslan Alwi; Moh. Bhanu Setyawan; Munirah Munirah
IJAIT (International Journal of Applied Information Technology) Vol 04 No 01 (May 2020)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v4i01.3122

Abstract

Storing student grades in universities is a sensitive issue when it comes to the security of campus computer networks. In this paper, we propose a blockchain model to ensure the secure storage of student grade data. Each record of recording student grades by a lecturer can be seen as a record in a journal or ledger. All records in one of the departments in a faculty can be seen as a student grade journal. Modeling this data by viewing data records as a journal allows us to model a database for all records in an encrypted and distributed manner. Namely, a model that resembles the blockchain model. In this perspective, a blockchain network can be made in which each node is stored in a different direction. So if there are three departments within the faculty, a blockchain with three vertices can be made. Each node keeps a copy of the overall student grade journal data. So that each node can mutually verify the validity of transaction records in each department. Student value journals are structured in such a way that they form a blockchain that builds hashes that lock together. This modeling of student value records answers the problem of being vulnerable to student scores hacked by irresponsible parties both from within the campus and from outside the campus. Security follows the protocols in the blockchain architecture.
Artificial Neural Network Model with PSO as a Learning Method to Predict Movement of the Rupiah Exchange Rate against the US Dollar Eko Verianto; Budi Sutedjo Dharma Oetomo
IJAIT (International Journal of Applied Information Technology) Vol 04 No 02 (November 2020)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v4i02.3381

Abstract

The movement of currency exchange rate can be predicted in the next few days, this is used by economic actors to get profit. Artificial Neural Network with the backpropagation learning method is good enough to use for forecasting time series data, it's just that in its application this method was considered to have shortcomings such as a long training time to achieve convergence. The purpose of this research is to form a Multilayer Perceptron Artificial Neural Network model with the Particle Swarm Optimization (PSO) algorithm as a learning method in the case of currency exchange rate prediction. This research produced a model that can predict the movement of the Rupiah exchange rate against the US Dollar, while the model formed was the MLP-PSO model with an error rate of 5.6168 x 10-8, slightly better than the MLP-BP model with an error rate of 6.4683 x 10-8. These results indicated that the PSO algorithm can be used as a learning algorithm in the Multilayer Perceptron Artificial Neural Network.
Survey Paper on User-Centric Service Composition Henry Rossi Andrian; Wardani Muhamad
IJAIT (International Journal of Applied Information Technology) Vol 04 No 01 (May 2020)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v4i01.3213

Abstract

Service composition combines several services to complete more complex tasks and get increased service value. The service user determines the task be completed. Several standards have been presented to support the composition of services, including BPEL and WSCDL. However, existing standards can only be used or operated by IT professionals who understand software design and development well. The number of end-users who do not have specific skills is far greater than that of IT professionals. Therefore, to improve service composition capabilities, end-users must be given the opportunity to interact directly with the service composition system to obtain the new services they need. To create a user-centered service composition, some general needs must be met, namely: making it easier for users to obtain appropriate services, guaranteeing the fulfillment of Quality of Service (QoS), and visualizing composite services that are generated instantly. The resulting services meet external requirements submitted directly by users and pay attention to user preferences as internal (implicit) requirements. This paper presents various studies that have been produced to support the composition of user-centered services and problems that are still open as to research challenges in the future. This study's results are exspected to help service composition platform developers understand the various approaches to developing user-centered service composition.
Adaptation Atomic Design Method for Rapid Game Development Model Rickman Roedavan; Agus Pratondo; Bambang Pudjoatmodjo; Yahdi Siradj
IJAIT (International Journal of Applied Information Technology) Vol 04 No 02 (November 2020)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v4i02.3658

Abstract

Prototyping a game is a process to build the core game mechanics for use in the final game. This process is essential because it can save cost, time and reduce the potential for errors. There is a lot of study and research on the Game Development Life Cycle (GDLC). Some existing GDLC's were developed based on the waterfall model, while others were developed based on prototyping models. However, most of these models are not considered the cost and time factor. This research proposes a new Rapid Game Development (RGD) model, adapted from our previous work in developing the Game Mechanic Framework for Unity Game Engine. The experiment result showed that this method could be used to create a game faster while keeping the budget in mind during the development process.
Sign Language Recognition using Principal Component Analysis and Support Vector Machine Astri Novianty; Fairuz Azmi
IJAIT (International Journal of Applied Information Technology) Vol 04 No 01 (May 2020)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v4i01.3015

Abstract

The World Health Organization (WHO) estimates that over five percent of the world's population are hearing-impaired. One of the communication problems that often arise between deaf or speech impaired with normal people is the low level of knowledge and understanding of the deaf or speech impaired's normal sign language in their daily communication. To overcome this problem, we build a sign language recognition system, especially for the Indonesian language. The sign language system for Bahasa Indonesia, called Bisindo, is unique from the others. Our work utilizes two image processing algorithms for the pre-processing, namely the grayscale conversion and the histogram equalization. Subsequently, the principal component analysis (PCA) is employed for dimensional reduction and feature extraction. Finally, the support vector machine (SVM) is applied as the classifier. Results indicate that the use of the histogram equalization significantly enhances the accuracy of the recognition. Comprehensive experiments by applying different random seeds for testing data confirm that our method achieves 76.8% accuracy. Accordingly, a more robust method is still open to enhance the accuracy in sign language recognition.

Page 5 of 13 | Total Record : 122

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