• 유통과학연구
• /
• 제17권9호
• /
• pp.93-102
• /
• 2019

Purpose - Capturing the shifting consumer behavior perspective on online transportation network performance in Indonesia, this study aims to empirically examine the impact of electronic customer relationship management (e-CRM) and e-service quality on customer e-satisfaction and e-loyalty. Research design, data, and methodology - A quantitative approach was applied, and then we determined the respondents who met the predetermined criterion by using purposive sampling method. In total, 167 online transportation customer in Indonesia participated in this electronic questionnaire survey. To tested the collected data, Partial Least Square (PLS) - (SEM) analytical tools were employed. Results and Findings - There are five hypotheses proposed in this study and state that only one hypothesis is rejected, The dominant relationship between variables in the hypothesis is shown in the variable relationship of e-service quality on e-satisfaction. CRM, Service Quality, Satisfaction and Loyalty implemented comprehensively in cyberspace provides a clear picture for academics but also for practitioners who are struggling in the service industry that specifically appoints online transportation business. The findings of this research provide both managerial and theoretical implications to maintain customer e-loyalty in online transportation network business environment in Indonesia.

• International Journal of Computer Science & Network Security
• /
• 제23권11호
• /
• pp.77-82
• /
• 2023

The article considers online discussion as an interactive learning method in the conditions of distance learning. The essence of discussion and the stages of its organization are described. The main objective of discussion in distance learning is defined as the stimulation of interest in learning and the involvement of various viewpoints in an active discussion of the stated problems. The key role in ensuring the efficiency of a discussion is identified. The article develops a model for organizing asynchronous online discussions on the Moodle platform, highlighting the sequence of stages and their content. An experimental study of the use of the discussion method in the training of students in distance learning conditions is carried out. Based on the results of the methodological experiment, conclusions are drawn about student interest in online discussions. The authors conclude that the interest of students of different specialties in asynchronous online discussions varies, and the greatest interest is demonstrated by linguistics students. Nevertheless, the differences in student interest in online discussions by groups (specialties) are more likely attributable to subjective factors, which do not affect the overall picture in a major way.

• International Journal of Computer Science & Network Security
• /
• 제24권3호
• /
• pp.1-11
• /
• 2024

Payment systems are evolving, and this study examines how blockchain and AI improve online transactional security and service quality. The study examines micro and macro payment systems, compares online, and offline methods all over the world. The study also examines how blockchain and AI affect payment system security, privacy, and efficiency globally and rapidly digitizing economy. Digital payment methods are growing all over the world with high literacy and digital engagement, but they face challenges. The research highlights cybersecurity threats and the need to balance user convenience and security. It suggests blockchain and AI improve online payment services, supporting the policies for different countries. In this extensive research survey, we compare and evaluate the strengths and weaknesses of various payment systems, their practicality, and their robustness. This study also examines how technological innovations and payment systems interact to reveal how blockchain and AI could transform the financial sector. It seeks to understand how technology-enhancing service quality can boost customer satisfaction and financial stability in the digital age. The findings should help policymakers, financial institutions, and technology developers optimize online payment systems for a more secure and efficient digital economy.

• Journal of Communications and Networks
• /
• 제12권4호
• /
• pp.375-381
• /
• 2010

A flooding attack, such as DoS or Worm, can be easily created or even downloaded from the Internet, thus, it is one of the main threats to servers on the Internet. This paper presents an online real-time network response system, which can determine whether a LAN is suffering from a flooding attack within a very short time unit. The detection engine of the system is based on the incremental mining of fuzzy association rules from network packets, in which membership functions of fuzzy variables are optimized by a genetic algorithm. The incremental mining approach makes the system suitable for detecting, and thus, responding to an attack in real-time. This system is evaluated by 47 flooding attacks, only one of which is missed, with no false positives occurring. The proposed online system belongs to anomaly detection, not misuse detection. Moreover, a mechanism for dynamic firewall updating is embedded in the proposed system for the function of eliminating suspicious connections when necessary.

• 디지털융복합연구
• /
• 제9권1호
• /
• pp.1-12
• /
• 2011

The power of the internet community as a social network exerts great influence on all areas of our society not only on knowledge creation and knowledge sharing but also on politics, economy, and culture. This study aims to investigate how the diffusion process of information evolves on the internet in the new environment. The focus of the study is particularly on aspects of using information and the process of information production and the types and methods of online communities. It is the goal of the study to clarify aspects of the online community as an important mediator among universal means of communication in our society. Ways of social communication are changing rapidly and thus the reasoning for this change is very important policy issues to form a social consensus.

• International Journal of Computer Science & Network Security
• /
• 제21권12호
• /
• pp.165-174
• /
• 2021

This study aimed to ascertain whether electronic courses at the deanship of electronic learning and distance education at Umm Al-Qura University meet the quality standards developed by the Quality Matters (QM) organization. This endeavor adopted a mixed method of an explanatory sequential research design for an in-depth understanding of the topic under scrutiny. The sample of the study consisted of ten courses designed at the deanship and reviewed using an evaluation form. The results showed that the courses in focus did not meet the criteria of QM. Based on this finding, a semi-structured interview was designed to collect relevant data from the syllabus designers at the deanship. The interviews yielded information on the difficulties the course designers faced when designing QM-criteria-based courses. The results obtained from the interviews showed that the designers experienced administrative, technical, and faculty-member-related challenges that, when producing online courses, intercepted their way to achieving the QM standards. The study closed with some recommendations, the most important of which is a call for re-developing online courses in alignment with the well-recognized QM standards.

• 한국콘텐츠학회논문지
• /
• 제9권8호
• /
• pp.178-189
• /
• 2009

게임 산업은 멀티미디어 콘텐츠형 지식산업으로 세계적으로 지속적인 성장을 보이고 있다. 전체 게임 산업 중에서 큰 비중을 차지하고 있는 분야가 온라인 게임 분야이며 전체 게임 산업의 약 43%를 차지하고 있다. 온라인 게임은 대부분 월별 정액 요금제를 적용하는 만큼 제품이라기보다 서비스에 가까우므로 고객의 유지가 바로 기업의 현금흐름에 크게 기여하기 때문에 사용자의 만족도와 충성도가 매우 중요하다. 이렇듯 온라인 게임에서 사용자가 중요함에도 불구하고 온라인 게임 자체에 대해서는 기존에 많은 연구가 이루어진 반면, 사용자 중심의 연구, 그 중에서도 사용자의 커뮤니티에 대한 연구는 부족한 실정이다. 본 논문은 온라인 게임의 특징과 그 속성을 선행연구를 통하여 조사하고 온라인 게이머의 커뮤니티 의식과 소셜네트워크 형성에 영향을 미치는 요인을 파악하고자 한다. 또한, 온라인 게이머의 만족과 고객 충성도에 커뮤니티 의식과 소셜네트워크가 영향을 미치는 지를 검증하여 온라인 게임을 개발하고 서비스하는 기업에게 영업 전략을 제시하고자 한다.

• 한국정보통신학회논문지
• /
• 제24권5호
• /
• pp.567-575
• /
• 2020

온라인 소셜 네트워크가 현대인의 정보 공유 및 교류의 핵심적인 매체로 사용됨에 따라, 그 이용자는 매해 급격하게 증가하고 있다. 이는 단순히 사용량 증가뿐만 아니라 정보의 신뢰성에서도 기존 언론 매체를 능가하기도 하는데, 최근 등장하는 마케팅 전략들은 이 점을 노리고 교묘하게 소셜 네트워크를 공격하고 있다. 그에 따라 자연스럽게 형성되어야 할 여론이 온라인 공격으로 인해 인위적으로 구성되기도 하고, 이를 신뢰하는 사람들도 많아지게 되었다. 따라서 온라인 소셜 네트워크를 공격하는 주체들을 탐지하고자 하는 연구들이 최근 많이 진행되고 있다. 본 논문에서는 이러한 온라인 소셜 네트워크 공격자들을 탐지하고자 하는 연구들의 동향을 분석하는데, 그 중 소셜 네트워크 그래프 특성을 이용한 연구들에 집중하고 있다. 기존의 contents-based 기법이 사생활 침해 및 공격 전략 변화에 따른 분류 오류를 나타낼 수 있음에 반해, 그래프 기반 방법은 공격자 패턴을 이용하여 보다 강건한 탐지 방법을 제안하고 있다.

• 한국언론정보학보
• /
• 제56권
• /
• pp.194-218
• /
• 2011

이 연구는 온라인 토론 과정에서 메시지 품질과 토론 연결망 구조, 그리고 여론지도력의 관계를 탐색했다. 서울시 무상급식 논란이 벌어진 온라인 커뮤니티의 실제 토론사례를 분석한 결과, 메시지 품질과 연결망 지수, 주목과 반응이 모두 밀접한 관련을 맺고 있었다. 메시지 품질이 높은 토론자는 활발한 의견 교환을 유도해 토론 연결망에서 중심위치를 차지하면서 다른 토론자의 주목과 반응을 이끄는 여론지도력을 행사했다. 그러나 메시지 품질이 주목과 반응을 직접 유인하기보다 연결망 위치와 역할이 메시지 품질의 효과를 매개하고 있어 온라인 여론지도력이 토론자의 메시지 품질과 구조적 위치의 복합적 영향력임을 알 수 있었다. 한편, 여론지도층의 높은 메시지 품질에도 불구하고 연결망의 구조적 효과가 전체 토론의 합리성을 제약해 고립된 숙의와 여론 극화를 유인했다. 마지막으로, 메시지 품질의 여론지도력을 매개하는 연결망 구조와 여론지각의 상호작용 효과는 여론을 주도하는 다수여론집단에서 강하게 관찰됐다. 분석결과를 토대로 온라인 여론지도력 연구에서 토론 연결망의 구조적 효과가 지니는 함의를 논의했다.

• International Journal of Computer Science & Network Security
• /
• 제22권9호
• /
• pp.316-326
• /
• 2022

The prompt development in the field of video is the outbreak of online services which replaces the television media within a shorter period in gaining popularity. The online videos are encouraged more in use due to the captions displayed along with the scenes for better understandability. Not only entertainment media but other marketing companies and organizations are utilizing videos along with captions for their product promotions. The need for captions is enabled for its usage in many ways for hearing impaired and non-native people. Research is continued in an automatic display of the appropriate messages for the videos uploaded in shows, movies, educational videos, online classes, websites, etc. This paper focuses on two concerns namely the first part dealing with the machine learning method for preprocessing the videos into frames and resizing, the resized frames are classified into multiple actions after feature extraction. For the feature extraction statistical method, GLCM and Hu moments are used. The second part deals with the deep learning method where the CNN architecture is used to acquire the results. Finally both the results are compared to find the best accuracy where CNN proves to give top accuracy of 96.10% in classification.