Active Users Research Articles

The Influence of Shopping Lifestyle and Promotion of Nivea Skincare Products On Consumer Buying Interest Through Tiktok Shop

This study aims to investigate the influence of shopping lifestyle and also the promotion of Nivea skincare products on consumer buying interest through TikTok Shop media. Through a quantitative approach, data was collected from the number of respondents obtained were 100 with the balance of people in Cirebon Regency who were aged 18-40 years that at that age they could make a very wise decision and also for people in Cirebon Regency who were wearing Nivea products or were wearing Nivea products. Respondents' answers to a question set out on questionnaires that have been distributed to consumers who want Nivea products, measured by the Likert Scale . respondents who are active TikTok users and also have an interest in skincare products. Various dimensions of product promotion, including visibility, interactivity, content relevance, influencer engagement, as well as brand credibility, were measured as independent variables. Consumer buying interest was measured as the dependent variable in this study. The results of the study prove that visibility, interactivity, and also the involvement of influencers have a positive and significant influence on consumer buying interest. However, the relevance of the content as well as brand credibility does not have a significant influence on consumer buying interest. In addition, this study also found that moderate lifestyle shopping effects of product promotion on consumer buying interest, proving that consumers' shopping lifestyles affect the extent to which product promotion affects their buying interest. Thus, this study fills the existing literature gap by investigating the influence of shopping lifestyle and product promotion on consumer buying interest specifically through TikTok Shop media. The findings provide valuable insights for marketers in developing effective promotional strategies on social media platforms, particularly for brands in the skincare industry.

A Gamified Platform to Encourage Sustainable Behaviours

Abstract. The production, use, and disposal of goods and services require the use of natural resources, resulting in waste and environmental pollution. A growing number of people are embracing more sustainable lifestyles in alignment with the 3Rs (Reducing, Reusing, and Recycling) to counter these effects, but many remain uninformed of their options, or lack the motivation to adopt these practices. The work described in this paper addresses these issues through the development of the Sustainable App, a mobile application incorporating techniques of persuasion and gamification which offers its users eco-friendly alternatives to several types of daily activities, made available via an interactive map. The app employs diverse strategies to improve engagement, including a pet-nurturing game-like feature that responds to user actions related to sustainable transport choices, sustainable retail, and recycling. Additionally, the complete platform associated with the app also delivers Just-In-Time (JIT) messages concerning nearby sustainable choices based on location and time. Upon evaluation of the platform, positive user experience and overall good feedback were noted. Experts also weighed in on the application’s evaluation, offering valuable insights to refine future iterations.

Desain Koridor Jalan Prof. Dr. Ing. B. J. Habibie. Iloheluma sebagai Kawasan Wisata dan Pusat Kuliner Bone Bolango

This report discusses effective and efficient road corridor design in improving the quality of the city and the quality of life of the people on Jalan Prof. Dr. Eng. B. J. Habibie. Iloheluma, District. Bone Bolango. The implementation of this service focuses on the analysis and design of road corridors that meet the needs of each individual and improve the quality of the city. This service uses a livable streets approach which can be taken into consideration in creating a road corridor design that is comfortable and safe for all user activities. The case study location is a culinary area that grows informally. Along the road corridor there are dozens of street vendors who take advantage of the location's beautiful natural views so that they can attract visitors to stop by and have a snack. Based on the results of observations in the field, road corridors were arranged by considering streetscape elements related to road corridor design, such as services and infrastructure, traffic calming, sidewalks, land use, building shape and mass, circulation and parking, open space, pedestrians, supporting activities, advertising boards and preservation.

Ethical keylogger solution for monitoring user activities in cybersecurity networks

This paper presents the development of a software keylogger to monitor user activities within a cyber network, enhancing security and facilitating comprehensive cybersecurity analysis. Guided by the agile methodology, the work adopts a flexible and iterative approach to development, ensuring continuous collaboration, adaptation to evolving requirements, and swift response to feedback. Leveraging the versatility and efficiency of the Python programming language, this work transforms the traditional notion of a keylogger, which is a program that records keystrokes, into an ethical and legally compliant tool. By capturing and logging keystrokes, the system provides valuable insights into user behavior and potential security threats, enabling proactive measures to prevent cyber-attacks and data breaches. Prioritizing transparency and consent, the system design adheres to ethical standards and privacy regulations, ensuring the protection of sensitive information and user privacy. This technical solution offers cybersecurity professionals, system administrators, and organizations a valuable tool for network monitoring while showcasing responsible development practices and contributing to the advancement of ethical cybersecurity solutions.

Tracing Student Activity Patterns in E-Learning Environments: Insights into Academic Performance

In distance learning educational environments like Moodle, students interact with their tutors, their peers, and the provided educational material through various means. Due to advancements in learning analytics, students’ transitions within Moodle generate digital trace data that outline learners’ self-directed learning paths and reveal information about their academic behavior within a course. These learning paths can be depicted as sequences of transitions between various states, such as completing quizzes, submitting assignments, downloading files, and participating in forum discussions, among others. Considering that a specific learning path summarizes the students’ trajectory in a course during an academic year, we analyzed data on students’ actions extracted from Moodle logs to investigate how the distribution of user actions within different Moodle resources can impact academic achievements. Our analysis was conducted using a Markov Chain Model, whereby transition matrices were constructed to identify steady states, and eigenvectors were calculated. Correlations were explored between specific states in users’ eigenvectors and their final grades, which were used as a proxy of academic performance. Our findings offer valuable insights into the relationship between student actions, link weight vectors, and academic performance, in an attempt to optimize students’ learning paths, tutors’ guidance, and course structures in the Moodle environment.

Differences between Active and Passive Social Media Usage on Well-Being in Reference to Adolescents

Today in this fast pacing world and in the age of digital era, internet is easily accessible to every human being. Many researchers in the past have explored that social media is directly or indirectly affecting the physiological and mental health of an individual. Active users are the ones who are actively involved in the social media sites whereas the passive users are the ones who are not actively participating yet observing the other’s profiles and posts. The aim of this paper is to identify the significant difference between genders (male and female) on well-being in reference to adolescents and significant difference between active and passive social media users on the well-being in reference to adolescents. The total sample size taken was N=120, which consists of 60 males and 60 females of both the groups that is active and passive social media users. Random purposive sampling was used for collecting data. The research design for the study is 2x2 factorial design. The independent variables of the study are Active and passive social media users whereas the dependent variables for the study are dimensions of well-being given by Carol Ryff i.e. autonomy, environmental mastery, personal growth, positive relations, purpose in life, self-growth. Self-made online survey was done for collecting the sample for active and passive social media users and Ryff’s well-being scale was used in the study. The analysis of data was done by using descriptive analysis and ANOVA. The findings of the study suggest that there was a significant difference between active and passive social media users on well-being also there was a significant difference between genders (male and female) on well-being in reference to adolescents.

A holistic digital forensic analysis of Discord - Storage, memory, and network perspectives.

In the last decade, the market share and user base of social media applications have witnessed significant growth. However, this surge in popularity has inadvertently drawn the attention of criminals aiming to exploit these platforms for illicit activities. The forensic examination of these applications emerges as a pivotal avenue for uncovering valuable insights into criminal behavior and identifying suspects. Discord, a social media platform, has become a significant focal point for such illicit activities. In this paper, we examine the remnants of Discord on both Windows and Linux operating systems, employing storage, memory, and network analysis techniques to review the remnants of Discord. Our investigation reveals a range of crucial artifacts that have been successfully recovered across all three areas of analysis, including login and payment details, chat history, account information, and much more. Collectively, these artifacts constitute a valuable resource for forensic investigations, allowing the reconstruction of most of the user's activity.

Handling TikTok App Addiction Behavior in Gen Z (Case Study on Three Teenagers in Rumah Tiga Village)

Indonesia is the second country with the most active TikTok users in the world. In April 2022, active TikTok users in Indonesia reached 99.1 million people. revealed in the latest report 'Media State of Mobile 2024' released by Data.AI at the beginning of 2024, Indonesians are also starting to get addicted to TikTok. It was recorded that Indonesian citizens spent 64.8 billion hours on TikTok throughout 2023, an increase of 33%. This proves that many people are addicted to TikTok. Especially Gen Z, which is a generation that is close to technology (digital native), as they were born in the era of cellphones, are smart, grew up with sophisticated computer technology, and have an openness to easier internet access compared to previous generations. So efforts are needed to overcome Gen z who is addicted to the Tiktok application (Tiktok Syndrome). The aim of this research is to answer the problem of how to handle children addicted to the Tiktok application (Tiktok syndrome) in 3 teenagers in Rumah Tiga Village, Teluk Ambon District, Ambon City.

Development of a Stress-Free Algorithm for Control of Running Platforms Based on Neural Network Technologies

The article discusses the task of predicting human speed using neural network technologies and computer vision to minimize lags in treadmill control systems, which pose a health risk to the user. To solve this problem, a stress-free algorithm has been developed, including: predicting the position and speed of the user on the treadmill; calculating the treadmill speed based on the analysis of the user's position and movement characteristics; data collection and processing schemes for training neural network methods; and determining the necessary number of predicted frames to eliminate lags. The scientific novelty of the research lies in the development of a treadmill control algorithm that combines: computer vision technologies for recognizing the user's body model on the platform; neural networks; and machine learning methods to determine the final human speed based on combining data on the person's position in the frame and the current and predicted speed of the person. The proposed algorithm is implemented using Python libraries, and its validation was conducted during experimental studies analyzing the preceding 10 and 15 frames to predict the next 10 and 15 frames. Comparing machine learning algorithms (linear regression, decision tree, random forest, multilayer, convolutional, and recurrent neural networks) at different lengths of analyzed and predicted frames, the RandomForestRegressor algorithm showed the best accuracy in predicting position, while dense multilayer neural networks performed best in determining current speed. Experimental research has been conducted on applying the developed algorithm and models to determine human speed (achieving accuracy when forecasting in the range of 10-15 frames) as well as integrating them into treadmill control systems. Trials have shown the effectiveness of the proposed approach and the correctness of system operation under real conditions. The developed algorithm allows for not using noise-sensitive sensors that require attachment to the user's body but rather forecasting user actions through analyzing all points of the person's body to reduce lags in various human-machine systems.

Evaluasi Pengalaman Pengguna Website Responsif Beyondsultra

Tourism is a crucial sector in the economy of a region, and the use of digital technology in the tourism industry is steadily increasing. The responsiveness of a tourism website is a key factor influencing users' perceptions and experiences with the Beyondsultra website. Beyondsultra is a tourism website for Southeast Sulawesi created by the City of Kendari Regional-Owned Enterprise. The research aims to identify the responsiveness of the Beyondsultra website in influencing user perceptions of the quality of their user experience and to provide appropriate recommendations for the company to enhance user satisfaction with the Beyondsultra website. The selected respondents for the study are potential tourists and active users of the Beyondsultra website. Based on data obtained from user satisfaction observations while interacting with the Beyondsultra website using the User Experience Questionnaire (UEQ) and System Usability Scale (SUS) methods, above-average results were obtained for UEQ. Subsequently, a reevaluation was conducted to delve deeper into the issues faced by users, utilizing Cooperative Evaluation techniques. The research findings indicate an improvement in user satisfaction with the Beyondsultra website using the UEQ method, with a 68% increase in attractiveness, 93% in clarity, 91% in efficiency, 100% in stimulation, and 63% in novelty. However, one aspect, precision, remained unchanged after evaluation. In the SUS method, the average assessment score showed a 15% improvement.

AI-Enhanced Accessibility Solutions using Chatbot

The "AI-Enhanced Accessibility Solutions" project addresses the real-world challenge of enhancing accessibility for individuals through advanced technologies. Utilizing React.js, Next.js, Tailwind, and AI APIs, this study focuses on generating inclusive content, including text, images, videos, code, and chatbot interactions. The primary objectives are to improve user interfaces, employ AI-driven content generation techniques, and ensure compliance with accessibility standards. The platform allows users to input self-generated prompts to produce customized data, such as text, images, videos, and code, tailored to their needs. An interactive AI-powered chatbot assists users in daily activities, adapting responses based on the quality of prompts provided, ensuring personalized and effective results. Key features include AI-generated content designed for various abilities. This includes alternative text for images, simplified text for cognitive accessibility, and adaptive chatbot responses. The project also focuses on generating accessible code, adhering to best web development practices. Tailwind CSS is used to optimize content presentation, addressing factors like color contrast and readability. The study includes a comparative analysis of accessibility features in popular apps versus those generated by our system. User testing and feedback mechanisms are employed to validate the project's effectiveness in meeting diverse user needs. This project not only advances AI-driven content creation but also represents a significant step towards creating inclusive digital environments. It emphasizes the importance of accessibility in technology, ensuring that digital content is accessible to all individuals, regardless of their abilities. Keywords: AI-Enhanced Accessibility, Inclusive Content, React.js, Next.js, AI APIs, User Interfaces, Accessibility Standards, AI-Powered Chatbot, Cognitive Accessibility

Exploring leadership on Instagram: A visual model for online leadership analysis

Online visual communication is becoming an established and central component of citizens’ everyday life. User activity on large-scale platforms, such as Instagram, can be mapped by tracing the rise and fall of communities of practice that share different visual languages, aesthetic values and forms of leadership. Accordingly, the present study proposes an analytical model for the identification, measurement, and categorization of leadership on visual-based social networks, by asking: how does the digital performance of leaders on Instagram construct different forms of leadership? To answer this question, the Leadership Visual Performance Model (LVPM) will be presented as a theoretical tool to analyze and compare leadership performance on Social Networking Systems. While previous models mostly employed theme-based coding, this analytical tool relies on a set of structural indicators that enable a higher level of comparability across domains. To demonstrate, the LVPM will be employed to investigate the Instagram activity of Jeremy Corbyn and Boris Johnson during the 2019 UK General Election. Findings show how the LVPM indicators enable us to highlight differences in leadership style, compare them and employ them to build a typology.

Longitudinal perceptions of gamified loyalty programs (GLPs): a mix of slot machines and entertainment toys

PurposeThis paper seeks to understand users' perceptions of their experiences in mobile applications (apps) with gamified loyalty programs (GLPs) that use rewards as the primary engagement vehicle. The research focuses particularly on the motivations to further interact with GLPs and the motivational changes occurring after successive interactions.Design/methodology/approachThe authors conducted weekly open qualitative interviews over a month (four rounds of interviews) with five Portuguese active users of the mobile app Yorn Shake It, from Vodafone, which is a relevant case study to illustrate GLPs in mobile apps.FindingsParticipants' motivations to interact with the mentioned GLP are shaped by the reward incentive and users' perceptions of the gamified interactive experience. Motivational changes occur regardless of the presence of external contingencies and depend on contextual changes or perceived results of the gamified experience. This means that rewards also satisfy intrinsic needs, but users may remain connected to the system as long as fun experiences are provided without exhausting perceptions. Also, motivation may turn to reward contingencies when the challenge becomes boring.OriginalityThis is the first qualitative study explaining the perceptions of gamified experiences after continued participation, extending knowledge about the importance of a fair balance between the value and achievement of rewards and the entertainment of the challenge provided after continued exposure. The findings provide insights to GLP marketing managers and developers to better engage target audiences according to their needs and past experience, creating levels of challenges and fair rewards to maintain motivation and prevent abandonment after continued exposure.

Augmenting TikTok shop adoption: The mediating role of KOCs in live streaming, video content, and AI recommendations

There is a growing trend of social media networks transitioning into channels primarily focused on providing entertainment content. This research used the Uses and Gratifications (U&G) theory to examine the manner in which individuals transition from other platforms to TikTok with regards to their engagement in entertainment and self-publishing of videos. Key Opinion Consumers (KOCs) are individuals who provide evaluations from the consumer’s perspective. This emerging trend involves the creation of online review videos, which aligns with the evolving nature of e-commerce platforms. An online survey was administered to enlist a total of 251 individuals who are active users of the social media platform TikTok. The recruitment process included an online network sampling approach. The results of our study indicate that factors such as video lengths, live streaming, and Artificial Intelligence (AI) algorithms for recommendation have a substantial impact on the use of TikTok. The findings indicate that KOCs play a crucial role in mediating TikTok use patterns and uptake. This research enhances the comprehension of media use within the framework of uses and gratification, both in terms of theoretical and empirical aspects.

Place and Independence Are Formed by Moving Furniture

In contemporary architectural design, a noticeable trend emerges in the meticulous planning of common areas, with an emphasis on fostering the free movements of users within these areas. It is important to consider the architectural elements that influence user behavior in these environments. Previous studies have delved into the relationship between architecture and user activity, often through questionnaires and activity surveys conducted in arbitrary spaces. However, such data are discontinuous and only capture a portion of the space. Therefore, in this study, continuous and extensive recordings were performed in an arbitrary space using a video camera to capture the entirety of the area. Consequently, we were able to comprehend the relationship between architecture and people’s activities and observe the formation of user autonomy through their decisions to rearrange furniture. Furthermore, an “Open Pose” system was used to detect people and generate a user stay distribution chart. This was achieved by converting it into a plan view using perspective projection transformation, thereby obtaining objective data automatically. Consequently, we verified the feasibility of conducting visually comprehensible processing using tools like “Open Pose”, which was used in one segment of the experiment.

Integrating Blockchain and Deep Learning for Enhanced Mobile VPN Forensics: A Comprehensive Framework

In an era marked by technological advancement, the rising reliance on Virtual Private Networks (VPNs) necessitates sophisticated forensic analysis techniques to investigate VPN traffic, especially in mobile environments. This research introduces an innovative approach utilizing Convolutional Neural Networks (CNNs) and Graph Neural Networks (GNNs) for classifying VPN traffic, aiding forensic investigators in precisely identifying applications or websites accessed via VPN connections. By leveraging the combined strengths of CNNs and GNNs, our method provides an effective solution for discerning user activities during VPN sessions. Further extending this framework, we incorporate blockchain technology to meticulously record all mobile VPN transactions, ensuring a tamper-proof and transparent ledger that significantly bolsters the integrity and admissibility of forensic evidence in legal scenarios. A specific use-case demonstrates this methodology in mobile forensics, where our integrated approach not only accurately classifies data traffic but also securely logs transactional details on the blockchain, offering an unprecedented level of detail and reliability in forensic investigations. Extensive real-world VPN dataset experiments validate our approach, highlighting its potential to achieve high accuracy and offering invaluable insights for both technological and legal domains in the context of mobile VPN usage.

Secure app-based secondary healthcare clinical decision support to deployed forces in the UK Defence Medical Services

BackgroundModern instant messaging systems facilitate reach-back medical support for Defence Medical Services (DMS) by connecting deployed clinicians to remote specialists. The mobile app Pando (Forward Clinical, UK) has been used...

A qualitative exploration of online forums to support resilience of rural young people in Australia.

Prevention and early intervention are crucial strategies for improving young people's mental health and well-being. Building resilience is a key component of these strategies, especially among young individuals in rural areas who face well-documented mental health disparities. This study aimed to investigate how online mental health forums can contribute to enhancing individual resilience in young rural users. A sample of forum posts (n = 1,000) made by Australian rural users (18-25 years) on an online peer support mental health forum were qualitatively analyzed. The analysis was guided by themes derived from the literature on indicators of rural resilience. Analysis of forum posts showed evidence of rural resilience in forum users. Online peer support forums offered a virtual space for individuals to establish social connections, experience a sense of belonging, share information, acquire knowledge, and offer mutual support. There were indications of increased self-efficacy among forum users, as they demonstrated their ability to implement strategies for better managing their mental health. These findings significantly contribute to our understanding of how online forums can enhance resilience factors that are beneficial for young people living in rural communities. In the context of prevention and early intervention, this study illustrates the intricate connections between forum design and user activity with resilience outcomes, providing valuable insights into the underlying causal mechanisms. Consequently, it emphasizes the importance of incorporating such digital interventions as integral components of mental health service ecosystems.

"Menyuarakan Kewaspadaan Terhadap Hoax: Mengenal dan Melawan Penyebaran Informasi Palsu melalui Pengabdian Masyarakat di Sekolah 'MIN 1 Kota Palangkaraya

This community service aims to increase the understanding and awareness of the community, especially students and teachers at 'MIN Satu Kota Palangkaraya' School, about the dangers of spreading hoaxes as well as strategies to identify and deal with them. Hoaxes or false information are increasingly becoming a troubling threat with their ability to spread rapidly through social media and other digital platforms. Through a series of activities such as workshops and discussions, participants will be given an in-depth understanding of the importance of verifying information before disseminating it. In addition, they will also be equipped with critical skills to analyze the content they encounter online. Thus, it is hoped that the community, especially the younger generation who are active users of social media, will become more vigilant and responsible in disseminating information, and be able to distinguish between valid information and hoaxes. By involving schools as the center of education, the project also aims to strengthen digital literacy among students and teachers. As such, they will become effective in combating the spread of hoaxes, and help create a safer online environment filled with accurate and useful information.

Endocannabinoids and related lipids linked to social exclusion in individuals with chronic non-medical prescription opioid use

Opioid-related overdose deaths are still on the rise in North America, emphasizing the need to better understand the underlying neurobiological mechanisms regarding the development of opioid use disorder (OUD). Recent evidence from preclinical and clinical studies indicate that the endocannabinoid system (ECS) may play a crucial role in stress and reward, both involved in the development and maintenance of substance use disorders. Animal models demonstrate a specific crosstalk between the ECS and the endogenous opioid system. However, translational studies in humans are scarce. Here, we investigated basal plasma levels of the endocannabinoids anandamide (AEA) and 2-arachidonoyglycerol (2-AG), and eight endocannabinoid-related lipids, including oleoylethanolamide (OEA) and palmitoylethanolamide (PEA), as well as whole blood fatty acid amide hydrolase (FAAH) activity in chronic non-medical prescription opioid users (NMPOU; n = 21) compared to opioid-naïve healthy controls (n = 29) considering age, sex, and cannabis use as potential confounders. Additionally, the association of endocannabinoids and related lipids with the participants’ response to experimentally induced social exclusion was examined. We found significantly elevated basal AEA, OEA, and PEA levels in NMPOU compared to controls, but no differences in FAAH activity, 2-AG, or other endocannabinoid-related lipids. Within NMPOU, higher AEA levels were associated with lower perception of social exclusion. Robust positive correlations within N-acylethanolamines (i.e., AEA, OEA, and PEA) indicate strong metabolic associations. Together with our recent findings of elevated basal 2-AG levels in dependent cocaine users, present results indicate substance-specific alterations of the ECS that may have implications in the search for novel therapeutic interventions for these populations.