Garuda - Garba Rujukan Digital

Research on the Application of NLP-Driven Opinion Sentiment Tendency Analysis in Precision Marketing of New Energy Vehicles Tang, Na; Daijie, Li; mulang, Bu; Zhongyuan, Liu; Wenjing, Zhu; Chuanxiang, Yang
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1635

In today's online new media era, online public opinion often influences consumers' purchasing decisions. This dissertation discusses the strategies to promote the development of domestic new energy passenger cars, and combines the comment data of major media platforms, so that enterprises can more accurately understand the public's attitudes and perceptions towards new energy vehicles, and formulate more effective marketing strategies to increase the sales of new energy vehicles. This paper utilizes the nlp sentiment analysis technique, and incorporates 15 original papers to collect nearly 20,000 comments from major websites. It is found that the sales of new energy vehicles continue to rise despite a high proportion of negative online opinions about new energy vehicles, which is closely related to scientific and technological innovations, policy promotion, and consumers' increased acceptance of the concept of green mobility.

Practical Exploration of College Students' Career Planning in the Perspective of Artificial Intelligence - Analysis Based on the GROW Zhao, Lizhu; Liu, Yue
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1636

With the rapid advancement of artificial intelligence technology, college students are facing unprecedented opportunities and challenges in career planning. This paper aims to explore how college students can effectively plan their careers in the context of the artificial intelligence era, and conducts practical exploration based on the GROW model. The GROW model is a widely used framework in coaching and consulting fields for setting goals and solving problems, which covers four key stages: goal (Goal), reality (Reality), options (Options), and will (Will). The article analyzes the impact of artificial intelligence on the job market and discusses how college students should use artificial intelligence for career assessment, how to accurately understand the current situation of themselves and the career environment, how to master the application of artificial intelligence in personalized career planning, and how to combine artificial intelligence for education and training related to job seeking. The research results show that the GROW model can assist college students in organizing their career planning in the artificial intelligence era, thereby enhancing their employment competitiveness and career adaptability. In addition, the theoretical guidance and practical paths of career planning in the artificial intelligence era have significant practical significance and application value for college students.

New Energy Vehicle Brand Sales Trend Forecast and User Evaluation Research Tang, Na; Zeng, Xuefei; Jiang, Ying; Zheng, Haoyu; Zhou, Yiyi; Guo, Yan Lan
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1637

In the context of green economic development, new energy vehicles, as one of the representatives of innovation-driven development and environmental protection and energy conservation, are currently in a leading position in the market. This paper selects eight representative well-known brands, namely BYD, Li Auto, Xiaopeng, Geely, NIO, Changan Automobile, SAIC-GM and ORA, for quantitative analysis, with the aim of identifying future sales trends and conducting a precise business evaluation of new energy vehicles, as well as exploring the key factors affecting sales. The study was empirically tested using ARIMA time series forecasting, principal component analysis, linear regression analysis and neural network models. The results showed that brand identification behavior and personalized products have the most significant positive impact on sales. Therefore, this study believes that car brand collection, forwarding, personalized production and quality control are the key factors and improvement priorities that will affect future sales.

The Innovative Path of AI Technology Empowering Marketing Strategy in Unmanned Supermarkets Tang, Na; Li, Yiding; Liang, Yuting; He, Qiqi; Jiang, Wenxin
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1638

This research , whose research objects are users’ experiences, is a quantitative research t through methods such as literature method, questionnaire survey, and data analysis. The results show that the impact of unmanned supermarket technology on shopping experience, the evaluation of unmanned supermarket service and safety, and the correlation between technical difficulties and shopping frequency are the most important factors affecting user experience. Among them, the diversity of checkout technology and service response speed contribute the most. These analysis results provide important theoretical support and reference for unmanned supermarkets to optimize user experience in the future. At the same time, they are of great significance for optimizing the operation mode of new retail and meeting users' diverse consumption needs. Furthermore, they offer practical insights for enhancing the integration of AI technology to improve service efficiency, operational processes, and customer satisfaction, further supporting the sustainable growth and competitiveness of unmanned supermarkets in the evolving retail landscape.

Depth Study of User Purchase Influencing Factors in Platform E-commerce under the Background of Big Data and AI Tang, Na; Han, Yixuan; Wu, Yanlin; Sun, Fuli; Lai, Xinyue; Huang, Bingyan
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1639

Taking Taobao as a typical platform e-commerce, this study is devoted to exploring how big data and artificial intelligence technology can empower platform e-commerce and affect users' purchase intention. This paper adopts the empirical research method, collects data through online questionnaire, uses spss26 for regression analysis, and adopts the gradient lifting algorithm of machine learning model for data verification. The research results show that marketing activities such as "precise placement", "personal privacy", "product details" and "product ranking", which rely on big data and artificial intelligence technology, are the key factors affecting Taobao users' purchase intention, and their impact coefficients are 0.57, 0.135 and 0.288 respectively. Inventory management, profile building and personalized recommendations are also important factors. This paper takes the Consumer Behavior Analysis Model (AISAS) as the theoretical basis, and puts forward corresponding suggestions for Taobao platform e-commerce to enhance user attention, interest, search, purchase and sharing under the background of big data and artificial intelligence technology application.

Progress in the Application of Artificial Intelligence in Mental Health Education for College Students in Universities Shuai, Peng; Liu, Yue
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1640

The purpose of this paper is to explore how artificial intelligence technology can help mental health education in colleges and universities, analyse the progress of its application in personalised education, mental health monitoring and evaluation, ecological transient intervention, etc., and analyse its current situation, strengths, challenges, and future development direction.

Research on the Development of Intelligent Financial Education in the Era of Artificial Intelligence Liang, Tingting; Zhang, Hao
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1641

With the continuous progress of the digital era, artificial intelligence is increasingly interwoven with various fields. This paper focuses on the current status of financial management courses, applies the SWOT analysis method to analyze the current situation of the development of financial education, proposes the problems existing in current courses, discusses the limitations of traditional teaching, explores the application of AI technology in financial management education, improves and refines course design, breaks the limitations of traditional teaching methods, emphasizes the integration of theory and practice, enhances students' professional competence, cultivates financial management thinking, and builds an intelligent teaching platform. On this basis, it discusses the specific applications of AI in three parts: designing basic courses, cultivating professional competence and thinking, and building a teaching platform. The aim is to innovate financial management education, promote its sustainable and innovative development, and cultivate high-quality talents who can meet the needs of the future financial industry.

Design of an Academic Services Chatbot at Asia Institute Malang Djawa, Antonio Eka Wadu; Ahda, Fadhli Almu'iini
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1642

This study successfully developed and evaluated an academic services chatbot utilizing Natural Language Processing (NLP) and Artificial Neural Networks (ANN), showcasing a comprehensive methodology that encompassed data collection, preprocessing, model training, and performance evaluation. We meticulously derived the dataset from frequently asked questions at the Asia Institute of Technology and Business Malang, ensuring its relevance and applicability to the target audience. Rigorous preprocessing techniques, including tokenization, stemming, and stop words removal, were employed to enhance the quality of the input data for the ANN model, which significantly improved its performance. The training results revealed a strong correlation between the number of training epochs and the accuracy of the chatbot's responses, indicating that increased training led to enhanced performance. Furthermore, a Cronbach's Alpha coefficient of 0.965 confirmed the validity and reliability of the measurement tool for user feedback, highlighting the robustness of the collected data. User testing involving 37 students indicated a high level of satisfaction with the chatbot's performance, as it achieved a perfect accuracy score of 100%. These findings highlight the potential of NLP-based chatbots to enhance academic information services, effectively addressing student inquiries while significantly reducing the workload on academic staff. This study serves as a valuable model for other educational institutions aiming to implement AI-powered solutions to improve their academic support services and overall student experience.

Telegram FAQ Chatbot Design for Budi Mulia Lawang Junior High School Mahadwija, Adecya Jalu; Ahda, Fadhli Almu’iini
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1643

This study effectively created and assessed an academic services chatbot that employs Natural Language Processing (NLP) and Artificial Neural Networks (ANN). It demonstrates a thorough methodology that includes data collection, preprocessing, model training, and performance evaluation. The dataset was meticulously derived from frequently asked questions at the Institute of Business and Technology Asia Malang, ensuring its relevance and applicability to the target audience. Thorough preprocessing methods, such as tokenization, stemming, and the removal of stop words, were utilized to elevate the quality of the input data for the ANN model, leading to a notable enhancement in its performance. The training outcomes demonstrated a significant relationship between the number of training epochs and the accuracy of the chatbot's responses, suggesting that more extensive training resulted in improved performance. Additionally, the measurement tool employed for user feedback demonstrated confirmed validity and reliability, evidenced by a Cronbach's Alpha coefficient of 0.965, highlighting the strength of the data gathered. A study conducted with 37 students revealed a significant level of satisfaction regarding the chatbot's performance, which attained an impeccable accuracy score of 100%. The results underscore the promise of chatbots powered by natural language processing to improve academic information services, efficiently responding to student questions and markedly alleviating the burden on academic personnel. This study provides a significant framework for educational institutions looking to adopt AI-driven solutions to enhance their academic support services and enrich the student experience.

Review and Prospect of Research on the Application of VR Technology in Education and Teaching Analysis based on citespace knowledge graphs Zhang, Ximu; Liu, Yue
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1644

This paper analyzes 863 China Knowledge Network (CNN) source documents using CiteSpaceV6.3.R1 software, and sorts out the current research status and development trend of VR technology in education and teaching by mapping the relevant knowledge map of keywords, issuing authors, and issuing institutions. It is found that the research on VR technology in education and teaching has experienced a slow growth from its start in 1996 to 2015, and then a significant growth after 2017 with interdisciplinary characteristics. In terms of authors and institutions, as the cooperation on this related topic is still small and very scattered, but there are some research teams cooperating with each other, and the research hotspots cover virtual reality, information technology, vr technology, education and teaching, and teaching tools. In the future, research in this field should show the following trends: deepen interdisciplinary integration and expand VR education applications; strengthen empirical research and verify the effectiveness of the technology; pay attention to ethical privacy and build a responsible education ecology.

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
-

Contact Email
-

Phone
-

Journal Mail Official
-

Editorial Address
-

Location
Kota malang,

Jawa timur

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name -

Contact Email -

Phone -

Journal Mail Official -

Editorial Address -

Location Kota malang, Jawa timur INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
-

Contact Email
-

Phone
-

Journal Mail Official
-

Editorial Address
-

Location
Kota malang,

Jawa timur

INDONESIA