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Model of Customer Relationship Management systems Evaluation Using Factor Analysis 8

Model of Customer Relationship Management Systems Evaluation...

引用

8th International Conference on information Management and Technology, ICIMTech 2023

作者： Sardjono, Wahyu Kristin, Desi Maya Putra, Gustian Rama Binus Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Pakuan University Computer Science Study Program Faculty of Mathematics & Natural Sciences Bogor Indonesia

ISBN: (纸本)9798350326093

Relationship with customers is one of the most crucial factors in business continuity and development. Many current businesses have started delving into Customer Relationship Management (CRM) to establish and maintain their sales and customer relationships. This research was conducted on one retail company that implements CRM but experiencing a gap in their unit sales performance between their targeted sales and the realization. This study aims to analyze the gaps causing factors using Factor Analysis Method, constructing a suitable regression model, and proposing the company's necessary strategy. The research was conducted quantitatively using a questionnaire from 264 respondents. The result of this study showed that there are five causing factors which are CRM Reliability, Underutilization of CRM, CRM Capability, CRM Unpreparedness, and Customer Relation Quality, as well as forming a regression model of the company's CRM performance. © 2023 IEEE.

关键词： Sales

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Development of Key Performance Indicators in e-Learning Implementation in Higher Education Institutions 8

Development of Key Performance Indicators in e-Learning Impl...

引用

8th International Conference on information Management and Technology, ICIMTech 2023

ISBN: (纸本)9798350326093

Companies or organizations usually use key performance indicators (KPI) as indicators to determine their performance. The company's performance achievements are reflected in the set indicators that will describe the overall performance, as well as higher education institutions can also set key performance indicators, to see their performance achievements. The use of e-learning as a tool to support teaching and learning processes to be more effective and efficient is an example of which performance needs to be measured. This article discusses how the process of developing key performance indicators is carried out through the stages of designing questionnaires and distributing questionnaires to students, data is processed using the method of factor analysis to obtain the main indicators determining performance and the method of regression analysis is also used to build performance models. obtain KPI determinants, and then develop KPI models. The results show that there are indicators of sharing knowledge, managing knowledge, understanding knowledge, and utilization knowledge as performance measurement indicators. © 2023 IEEE.

关键词： Regression analysis

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Factors that Influence College Students in the use of ChatGPT in Indonesia

Factors that Influence College Students in the use of ChatGP...

引用

International Scientific-Professional Conference on information Technology (IT)

作者： R. Silvano A. Gui Information Systems Study Program School of Information Systems Bina Nusantara University Indonesia

This research investigates the characteristics that influence Indonesian college students’ use of ChatGPT, an AI-powered chatbot. Understanding students’ opinions and usage patterns is critical as AI becomes more prevalent in education. This questionnaire data collection was distributed using Google form and filled in by college students who were undergoing their studies. It focuses on three essential factors: trust (TRU), performance (PE), and effort (EE). The students’ trust in ChatGPT’s data security, credibility, and information correctness is critical. Performance Expectancy assesses how ChatGPT helps with job completion and information quality. The ease of use and user-friendliness of ChatGPT are factors in Effort Expectancy. This questionnaire data processing was processed using the SmartPLS 4 application. The data show that trust has a considerable positive influence on ChatGPT usage, implying that higher trust levels correlate with increasing utilization. Students recognize ChatGPT’s usefulness in academic settings, which has a positive impact on usage. The platform’s intuitive design and user-friendly interface are crucial reasons in its acceptance, according to Effort Expectancy. The study sheds light on AI adoption in educational settings, emphasizing the importance of trust, performance, and effort anticipation in changing student views toward technology. These findings can be used to influence the development of AI tools in education, emphasizing the importance of safe, efficient, and accessible designs to improve the learning experience.

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Exploring the Impact of Chatbot Functionality and Interactivity on Chatbot Usage Intention in Higher Education 10

Exploring the Impact of Chatbot Functionality and Interactiv...

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10th International Conference on information Technology, Computer, and Electrical Engineering, ICITACEE 2023

作者： Sartono, Eduardus Steven Wardhana, Calista Syifa Putri Princes, Elfindah Karmawan, I Gusti Made Ikhsan, Ridho Bramulya Gui, Anderes Bina Nusantara University Information Systems Study Program School of Information Systems Jakarta11480 Indonesia Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia Bina Nusantara University Management Department Jakarta11480 Indonesia

ISBN: (纸本)9798350322729

Living in a time when technological advancement is constant makes daily life unavoidably entwined with technology due to the digitalization process. A chatbot is a system powered by artificial intelligence (AI) that supports company operations in the customer care sector of the tourist, commercial, or educational sectors. It establishes the performance of an organization's efficacy and efficiency. Nevertheless, some users find using chatbots uncomfortable. This is a result of their inability to resolve their issues. This study investigates the variables influencing college students' readiness to utilize chatbots. Responses were obtained using a questionnaire and disseminated over social media channels, including Twitter, Instagram, WhatsApp, and Line. Data were then analyzed using Smart PLS 4.0. The findings show that perceived usefulness, perceived ease of use, perceived trust, functionality, interactivity, and attitudes toward technology all positively impact behavioral intention to use chatbot in higher education. The limitation of this study is small sample size and not cover all provinces in Indonesia. © 2023 IEEE.

关键词： Students

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Harnessing Machine Learning for Sentiment Analysis: A Comparative study of Classification Models on Discord User Reviews

Harnessing Machine Learning for Sentiment Analysis: A Compar...

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IEEE International Conference on Internet of Things and Intelligence System (IOTAIS)

作者： Joseph William Indarto I Gusti Ketut Edrick Felix Antonis Liu Evaristus Didik Madyatmadja Information Systems Study Program School of Information Systems Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331521219

ISBN: (纸本)9798331521226

This research conducts a comparative analysis of machine learning models to gauge user sentiment in Google Play Store reviews of Discord over the past year. As Discord broadens its scope beyond gaming to become a versatile communication tool, understanding user emotions is crucial, particularly in dynamic markets like Indonesia. We evaluated the performance of five classification models-Naive Bayes, Support Vector Machine (SVM), Random Forest, Neural Network, and AdaBoost-using metrics like accuracy, precision, recall, and F1 score. Our findings reveal that SVM and Random Forest lead the pack, offering superior accuracy and robustness in sentiment analysis, while Neural Networks also perform well but fall slightly short. Naive Bayes and AdaBoost deliver reliable results but are less efficient. This study uncovers key sentimental trends: positive reviews often praise features and performance, while negative feedback highlights issues with login and verification. Ultimately, our research underscores the critical role of choosing the right model to enhance user experience and inform strategic improvements on platforms like Discord. Future work should explore real-time sentiment analysis to boost user engagement and satisfaction.

关键词： Support vector machines Sentiment analysis Analytical models Adaptation models Accuracy Reviews Neural networks Robustness Bayes methods Random forests

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The Security of Mobile Banking in Industrial Revolution 4.0

The Security of Mobile Banking in Industrial Revolution 4.0

引用

Emerging Trends in information Technology and Engineering (ic-ETITE), Conference on

作者： Andi Alkila Aurellia Firjatullah Muzakkir Anderes Gui Information Systems Study Program School of Information Systems Bina Nusantara University Jakarta Indonesia

The phenomenon of globalization has had a significant impact on various sectors of society, such as ideology, politics, economics, socio-culture, defense, and security. This influence is particularly notable in the paradigm shift observed in these areas, with a particular emphasis on the role of a 4.0 society has prompted a profound transition across several industrial sectors, as they integrate digital technology and internet networks. Hence, this study employs a methodology for assessing questionnaire readability that incorporates validity and reliability assessments. The questionnaire consists of 24 items, encompassing nine distinct topics: social influence, reward, effort expentancy, facilitating conditions, security, risk and trust. The respondents were asked to provide their responses using a Likert scale ranging from 1 to 5, where 1 represents severe disagreement and 5 represents strong agreement. The findings of this study consisted of a total of 414 participants, with a significant proportion originating from Greater Jakarta, Java, and North Sumatra. The data will be analyzed with statistical software packages such as SPSS and SMART PLS. The objective of this study is to assess the degree of customer satisfaction in relation to the utilization of the mobile banking application, including service quality, information quality, and system quality. This research has the potential to provide valuable theoretical and technological insights, while also making a significant contribution to the literature in the subject of informatics engineering and information systems. It can serve as a valuable reference for future research endeavors.

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Analysis of Factors Affecting Behavioral Intention to Use QRIS

Analysis of Factors Affecting Behavioral Intention to Use QR...

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Emerging Trends in information Technology and Engineering (ic-ETITE), Conference on

作者： Gregorius Michael William Widjaya Anderes Gui Information Systems Study Program School of Information Systems Bina Nusantara University Jakarta Indonesia

QRIS strives to provide affordable payment options and promote financial inclusion for small and midsize businesses. Adopting the modified Unified Theory of Acceptance and Use of Technology (UTAUT), this research analyzed the factors influencing customers’ behavioral intention to utilize QRIS within financial applications and aim to identify the factors within variable that has influence behavioural intention for adopting the QRIS payment method. Data collected from 491 respondents in Indonesia who have used QRIS was processed using SmartPLS 4 with PLS-SEM to examine the relationships between variables that were used to analyze factors influencing customers’ behavioral intention toward QRIS. The findings showed that performance expectancy, effort expectancy, and personal innovativeness positively affect attitude towards QRIS. In addition, behavioral intention is also affected by social influence, habit, personal innovativeness, and attitude. The result of this research also provides better understanding and valuable insights for developing strategies to increase QRIS adoption in promoting the cashless society in Indonesia.

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A Comparative study of Traditional and Deep Learning Models Using Emotional Customer Data in Automotive Sales Forecasting

A Comparative Study of Traditional and Deep Learning Models ...

引用

Advancement in Data Science, E-learning and information systems (ICADEIS), International Conference on

作者： Gempar Bambang Godata Irmawati Information Systems Study Program Universitas Multimedia Nusantara Banten Indonesia

ISBN: (数字)9798331513320

ISBN: (纸本)9798331513337

This study investigates the effectiveness of traditional and deep learning models in predicting automotive sales outcomes using customer acoustic and emotional parameters extracted from sales call recordings. A primary dataset of sales conversations was processed using an internal tool, which converts audio into numerical data based on 11 acoustic features such as pitch, volume, and speech rate. Traditional machine learning models, including AdaBoost, Support Vector Machine (SVM), and Random Forest, were compared with deep learning models like Dense Neural Networks (DNN) and TabNet. The optimized DNN model achieved the highest performance, with an F1-Score of 0.7298, balancing precision and recall effectively. TabNet provided competitive results with an F1-Score of 0.7237, offering additional benefits of feature interpretability through its attention mechanism. These findings suggest that while traditional models, particularly AdaBoost, perform adequately, deep learning models, especially DNN and TabNet, are better equipped to capture the complex, non-linear relationships in acoustic and emotional data. The results provide actionable insights for optimizing sales strategies through data-driven decision-making. It offers a foundation for future advancements in predictive analytics within automotive industries using voicebased datasets.

关键词： Deep learning Support vector machines Neural networks Predictive models Feature extraction Data models Acoustics Numerical models Recording Automotive engineering

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A study on Student's Satisfaction of using E-learning System During the COVID-19 Pandemic 26

A Study on Student's Satisfaction of using E-learning System...

引用

26th International Conference on information Technology, IT 2022

作者： Nicholas, N. Hartono, K.M. Vincent, V. Gui, A. Bina Nusantara University Information System Program Indonesia School of Information Systems Bina Nusantara University Lecturer Specialist-S3 From Information Systems Study Program Indonesia

ISBN: (纸本)9781665421270

The e-learning system, is usually defined as a teaching and learning activities that is done with a computer, which evolves alongside with the evolution of the web. During the COVID-19 Pandemic, schools are forced to make a switch to the distance learning methods. With some previous research on studies about satisfaction using TAM, ECM and ISS, a conceptual framework was created to create a further study on Satisfaction. A total of seven hypotheses were created on this research that connects six variables from TAM, ECM, and ISS. As the survey was conducted to 400 high school students in Indonesia who uses the e-learning, the data was processed and calculated using SmartPLS using the PLS and Bootstrapping calculation. After the convergent and discriminant validity and the path analysis were conducted, it was found out that all of the hypotheses were accepted. However, there are some limitations in this study, which include sample and variable limitations. © 2022 IEEE.

关键词： E-learning

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Citrus Limon L. Ripeness Identification Using Feature Extraction of Mean RGB, HSV, LBP and K-Nearest Neighbor

Citrus Limon L. Ripeness Identification Using Feature Extrac...

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2023 International Seminar on Application for Technology of information and Communication, iSemantic 2023

作者： Priyo Utomo, Ade Cahyo Sari, Christy Atika Rachmawanto, Eko Hari Hadi, Heru Pramono Mostafa, Salama A. Al-Dayyeni, Wisam Subhi Talib University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology Johor Malaysia Ada University School of Information Technologies and Engineering Baku Azerbaijan

ISBN: (纸本)9798350339215

Citrus Limon L. (Lemon) is a type of fruit that is currently widely consumed, because it contains abundant vitamin C, fiber, and antioxidants. This fruit have high potential in the agribusiness sector and is widely cultivated by traditional farmers. However, during harvest time, traditional farmers generally still use manual methods using the human eye in distinguishing the maturity level of lemons which is less efficient because it has a low accuracy. Digital image processing is one solution to this problem. In the research on the classification of lemon maturity levels using digital image processing with the feature extraction method of the Mean RGB, HSV, and LBP methods and the K-Nearest Neighbor classification algorithm in this study, a total of 120 lemon images were used which were divided into 80 training image data and 40 image data. testing. The results of model performance measurements in the form of the highest accuracy level in the Mean RGB method of 100%, the highest accuracy in the HSV method of 98%, and the highest accuracy in the LBP method of 82.5%. © 2023 IEEE.

关键词： Citrus fruits

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