• International Journal of Advanced Culture Technology
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• v.3 no.2
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• pp.118-123
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• 2015

IT environment gets more complicated in terms of open platform, network standards, device design and hardware, etc. Smart network and application are in the fields of corporate as well as national competition for future fusion technology. In development environment focused on computers, the ideas of authoring tool have been presented in terms of improved software productivity. In smart environment where subdividing works are consecutively done, current authoring tool should be effectively updated for effective development of programs and easier access to business works. The basic concept of a new conceptual App development tool, Smart App Authoring Tool, which has been designed in this study and enables to apply on-site requirements to smart phones, is to develop Apps on the level using easy-to-learn Word or Excel in a computer. Therefore, this study is intended to design a conceptual Smart App Authoring Tool to optimize the cost and time for developing and maintaining new application services under various smart phone platform environments. Based on the performance of smart app authoring tool herein, every people can develop a smart app program at moderate level. So this paper have designed a conceptual smart app authoring tool. This study presented educational efficiency of the authoring tool by developing business Apps under various business environments and applying them under university and high school environments.

• Journal of Information Science Theory and Practice
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• v.5 no.2
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• pp.6-16
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• 2017

Populating information-rich online environments through crowdsourcing is increasingly becoming popular. One approach to motivate participation is via games. That is, a crowdsourcing game offers entertainment while generating useful outputs as byproducts of gameplay. A gap in current research is that actual usage patterns of crowdsourcing games have not been investigated thoroughly. We thus compare content creation patterns in a game for crowdsourcing mobile content against a non-game version. Our analysis of 3,323 contributions in both apps reveal 10 categories including those that conform to the traditional notion of mobile content created to describe locations of interest, and those that are social in nature. We contend that both types of content are potentially useful as they meet different needs. Further, the distribution of categories varied across the apps suggests that games shape behavior differently from non-game-based approaches to crowdsourcing.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.276-282
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• 2018

Objectives: Due to the uncontrolled increase of the mobile health applications and their scarce use by elderly for reason of absence credibility of measurements by lack scientific support, the aim of this study was to evaluate the differences between the biophysical measurements based on standard instrument against a mobile application using controlled experiments with elderly to propose an effective validation model of the developed apps. Methods: The subjects of the study (50 people) were elderly people who wanted to check their weight and cardiac status. For this purpose, two mobile applications were used to measure energy expenditure based on physical activity (Activ) and heart rate (SMCa) during controlled walking at specific speeds. Minute-by-minute measurements were recorded to evaluate the average error and the accuracy of the data acquired through confidence intervals by means of statistical analysis of the data. Results: The experimental results obtained by the Activ/SMCa apps showed a consistent statistical similarity with those obtained by specialized equipment with confidence intervals of 95%. All the subjects were advised and trained on the use of the applications, and the initial registration of data to characterize them served to significantly affect the perceived ease of use. Conclusions: This is the first model to validate a health-app with elderly people allowed to demonstrate the anthropometric and body movement differences of subjects with equal body mass index (BMI) but younger. Future studies should consider not only BMI data but also other variables, such as age and usability perception factors.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.1
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• pp.9-16
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• 2019

Smartphones are becoming a portable computer. As a result, even the most sensitive financial application services are now available anywhere on the smartphone. Compared to general PCs, smartphones communicate with external devices through various channels such as wireless internet, mobile communication network, Bluetooth, and NFC, and a wide variety of applications are provided. Therefore, if vulnerabilities exist, the possibility of attack damage increases. In this paper, we analyze the vulnerabilities of dynamic virtual keyboards used in login of banking apps of smartphones with various physical constraints and propose countermeasures.

• Korea Journal of Hospital Management
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• v.26 no.1
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• pp.1-16
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• 2021

Purpose: The purpose of the study is to identify the influence of the hospital mobile app service quality on consumer satisfaction, involvement, and re-use intention of consumers who have experience in hospital mobile app service. Methodology: The survey was conducted on 230 users. The collected data were analyzed using correlation analysis, multiple regression analysis, and the Process Model in Hayes(2013). Findings: (1)The usability, reliability, and medical information provision among the service quality factors of hospital mobile apps had an effect on reuse intention, and consumer satisfaction partially mediated. (2)The usability and the provision of medical information were partially mediated by the involvement, which also affected the intention to reuse. (3)Only reliability showed an age-moderated effect. In reliability and re-use intent, age was a moderated mediating effect that controlled the effect of consumer satisfaction. Practical Implications: The results of this study provide initial data of mobile app services centered on hospitals and prove the type of consumer usage. It suggests that it can be used to attract potential consumers of hospitals and strategies to increase the use of mobile apps.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.121-131
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• 2022

We look at the initial stage of Meta (previous Facebook)'s new metaverse platform and investigate its platform design in pre-launch and ignition life stage. From the Rocket Model (RM)'s theoretical logic, the results reveal that Meta firstly focuses on investing in key content developers by acquiring virtual reality (VR), video, music content firms and offering production support platform of the augmented reality (AR) content, 'Spark AR' last three years (2019~2021) for attracting high-potential developers and users. In terms of three matching criteria, Meta develops an Artificial Intelligence (AI) powered translation software, partners with Microsoft (MS) for cloud computing and AI, and develops an AI platform for realistic avatar, MyoSuite. In 'connect' function, Meta curates the game concept submitted by game developers, welcomes other game and SNS based metaverse apps, and expands Horizon Worlds (HW) on VR devices to PCs and mobile devices. In 'transact' function, Meta offers 'HW Creator Funding' program for metaverse, launches the first commercialized Meta Avatar Store on Meta's conventional SNS and Messaging apps by inviting all fashion creators to design and sell clothing in this store. Mata also launches an initial test of non-fungible token (NFT) display on Instagram and expands it to Facebook in the US. Lastly, regarding optimization, especially in the face of recent data privacy issues that have adversely affected corporate key performance indicators (KPIs), Meta assures not to collect any new data and to make its privacy policy easier to understand and update its terms of service more user friendly.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.141-149
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• 2023

Repacked mobile apps constitute about 78% of all malware of Android, and it greatly affects the technical ecosystem of Android. Although many methods exist for repacked app detection, most of them suffer from performance issues. In this manuscript, a novel method using the Constant Key Point Selection and Limited Binary Pattern (CKPS: LBP) Feature extraction-based Hashing is proposed for the identification of repacked android applications through the visual similarity, which is a notable feature of repacked applications. The results from the experiment prove that the proposed method can effectively detect the apps that are similar visually even that are even under the double fold content manipulations. From the experimental analysis, it proved that the proposed CKPS: LBP method has a better efficiency of detecting 1354 similar applications from a repository of 95124 applications and also the computational time was 0.91 seconds within which a user could get the decision of whether the app repacked. The overall efficiency of the proposed algorithm is 41% greater than the average of other methods, and the time complexity is found to have been reduced by 31%. The collision probability of the Hashes was 41% better than the average value of the other state of the art methods.

• Journal of Distribution Science
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• v.21 no.7
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• pp.117-129
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• 2023

Purpose: With the number of COVID-19 cases declining and generational differences among how people use mobile apps, including health service apps, the goal of this research is to identify and analyze the factors that affect people's attitudes when using the Halodoc health service app during the third year of the pandemic. Research design, data, and methodology: This study proposes a quantitative analysis method based on PLS-SEM modeling. This study has used a questionnaire survey to collect randomized data from 268 Halodoc users from generations Y and Z in Jakarta. Results: Both the Y and Z generations believe there is a significant usefulness factor in the attitude toward using the application. The start of the pandemic period demonstrates that the urgency of using health service applications is no longer determined by performance expectations, effort, or social panic, but rather by these applications' usability. Conclusions: Even though a health service application is no longer considered an urgent service or a priority need, attitudes, and behaviors in using it emphasize the aspect of long-term benefits. These findings supplement other considerations and understandings in application of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in explaining attitudes and intention behaviors.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.202-209
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• 2023

Android malware is now on the rise, because of the rising interest in the Android operating system. Machine learning models may be used to classify unknown Android malware utilizing characteristics gathered from the dynamic and static analysis of an Android applications. Anti-virus software simply searches for the signs of the virus instance in a specific programme to detect it while scanning. Anti-virus software that competes with it keeps these in large databases and examines each file for all existing virus and malware signatures. The proposed model aims to provide a machine learning method that depend on the malware detection method for Android inability to detect malware apps and improve phone users' security and privacy. This system tracks numerous permission-based characteristics and events collected from Android apps and analyses them using a classifier model to determine whether the program is good ware or malware. This method used the machine learning techniques KNN-SVM, DBN, and GRU in which help to find the accuracy which gives the different values like KNN gives 87.20 percents accuracy, SVM gives 91.40 accuracy, Naive Bayes gives 85.10 and DBN-GRU Gives 97.90. Furthermore, in this paper, we simply employ standard machine learning techniques; but, in future work, we will attempt to improve those machine learning algorithms in order to develop a better detection algorithm.

• Journal of Distribution Science
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• v.22 no.1
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• pp.13-23
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• 2024

Purpose: Within the ever-changing realm of modern e-commerce, this study delves into the complex effects of factors like performance expectations, ease of use, social influence, favorable conditions, and enjoyment perception on users' intentions and usage patterns in online marketplace apps. The research centres on Tokopedia app users in Denpasar City, encompassing a wide and varied demographic. Methods: Utilizing a non-probability sampling method, 200 participants were selected for extensive data collection through surveys. Subsequent rigorous analysis of the gathered data was performed using Structural Equation Modeling-Partial Least Squares (SEM-PLS) techniques. Results: This study aims to contribute substantially to theoretical and practical knowledge regarding marketplace app usage. Theoretical contributions involve enhancing the marketing domain, especially in digital marketing, by revealing the intricate factors influencing user conduct in online marketplaces. From a practical standpoint, this research provides valuable insights for entrepreneurs aspiring to join or improve their positions in the Tokopedia app market. Conclusion: Based on the study, we suggest optimising online shopping apps for a more appealing and user-friendly interface. Enhancing the enjoyment and simplicity of finding desired products can prompt heightened usage of online shopping services, thereby reinforcing distribution management strategies and overall market presence.