International Journal of Science, Technology & Management (IJSTM)
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Analysis Of E-Servqual Dimensions Influencing E-Customer Satisfaction Of My First Media Application Users
Get PDFThe internet's growth in Indonesia has reshaped lifestyles and opened new avenues for businesses. This study examines the impact of e-service quality dimensions on e-customer satisfaction among users of the myFirstMedia application—an innovative digital service ensuring 24/7 customer connectivity. However, there is a noticeable gap between service quality and user expectations. The research, utilizing a quantitative method, combines primary data from Google Forms surveys with secondary data from news articles and previous research. Employing non-probability purposive sampling, the study involves 385 respondents and applies Structural Equation Modeling (SEM) using SmartPLS 4.0 software. Statistical tests reveal that (1) the reliability dimension significantly influences e-customer satisfaction, (2) the responsiveness dimension positively impacts e-customer satisfaction, (3) the security/privacy dimension has a significant positive effect on e-customer satisfaction, (4) the fulfillment dimension significantly contributes to e-customer satisfaction, and (5) the efficiency dimension positively affects e-customer satisfaction. The R-Square coefficient of determination indicates a 52.6% influence of electronic service quality dimensions on e-customer satisfaction. Statistical analysis results confirm the impact of the reliability dimension on e-customer satisfaction. Descriptive analysis highlights that the fulfillment dimension exhibits the lowest percentage value, particularly concerning information on package prices, promotions, and other content within the My First Media application
The Influence of Financial Literacy, Lifestyle and Financial Planning on Consumptive Behavior In Millennials and Generation Z
Get PDFThis research aims to examine the influence of financial literacy, lifestyle, and financial planning on consumptive behavior in the millennial and Generation Z. The instruments in this study have passed validity and reliability tests, where these instruments are used as data collection tools. The number of respondents involved in this research is 95 people, dominated by [insert information about the dominant group]. Data collection technique uses random sampling, which falls under probability sampling. The data analysis technique used is descriptive analysis and regression analysis with the assistance of SPSS version 26. Out of the four hypotheses in this research, all are supported by empirical data. The findings of this research explain that financial literacy, and financial planning not influence on consumptive behavior in the millennial and Generation Z. Meanwhile lifestyle have an impact on consumptive behavior in the millennial and Generation Z. What sets this research apart from previous studies is the use of the evaluated objects, which influences the design of specific and unique research instruments. This research conducts descriptive hypothesis testing that was not present in previous studies. Meanwhile, the sample size, sample determination technique, and data analysis technique can be adjusted by future researchers based on the evaluated objects. The results of this research are also beneficial for the managers of the evaluated objects concerning the design of relevant strategies or programs to improve the quality attributes of the evaluated objects
Decentralized Trusted Storage of Audio-Video Log Data Based on Blockchain Technology and IPFS
Get PDFThe development of communication and information technology has affected the world of television broadcasting in Indonesia. With the emergence of a new phenomenon, the convergence of digital media industry. The migration of analogue to digital television broadcasting has impacted various industries related to broadcasting. Especially for the sustainability of the television broadcasting community in the country. Station Tv x is one of the television communities, on the other hand the media industry has challenges in managing storage media consisting of audio and video data that has a large capacity. Audio video logs are needed as information on recording audio video files. Blockchain-based Interplenary File System (IPFS) technology is expected to be one of the alternatives that can be applied in the world of broadcasting, storage media and audio video file data distribution methods, data library security and data flexibility are one of the challenges faced in the television broadcasting industry. The purpose of this research is as an effort to decentralise audio video data in distributed storage media to be more optimal and secure. The results of this research can be used to distribute audio video data files in the data library at tv station x
Sentiment Analysis of Twitter towards the 2024 Indonesian Presidential Candidates Using the Naïve Bayes Algorithms
Get PDFThe increasing use of social media (Twitter) has made it a platform for the public to express their views on the Indonesian presidential candidate in the 2024 elections. The sentiment expressed through comments on Twitter provides important insights into the public perception of the candidates. However, given the volume and speed at which information is disseminated on social media, manual analysis of this sentiment becomes impractical. Therefore, the use of the Naïve Bayes algorithm for automatic sentiment analysis is considered essential to understanding voter support and preferences. The study aims to analyze Twitter users' sentiments towards three Indonesian presidential candidates in 2024, Anies, Ganjar, and Prabowo, using the Naïve Bayes algorithm. We categorize the results of this analysis into three sentiment categories: positive, negative, and neutral. The methods used in the study involved collecting Twitter comment data related to the three candidates, pre-processing data, labeling data, applying the Naïve Bayes algorithm for the classification of sentiment, and evaluation of the performance of the algorithm performed by calculating the level of accuracy. The results of the research showed that the Naïve Bayes algorithm was able to classify sentiments with fairly high precision, namely 75.54% for Anies, 82.74% for Ganjar, and 75.24% for Prabowo. The conclusion of this study is that sentimental analysis using the Naïve Bayes algorithm can provide significant insights into voter preferences and support. The sentimental data generated can serve as a strong foundation for decision-makers to design campaign strategies that are more effective and responsive to public perception. This research also opens up opportunities for further development in the use of sentimental analysis techniques in politics and campaigns
Comparison of Machine Learning Algorithms in Public Sentiment Analysis of TAPERA Policy
Get PDFThe rapid development of information technology has changed the way people interact and express their opinions on public policies, including the People's Housing Savings (Tapera) policy in Indonesia. People now primarily express their views openly on social media platforms like Twitter, generating a substantial amount of text data for analysis to understand public sentiment. However, the main challenge in this sentiment analysis is determining the most effective machine learning algorithm for classifying public opinion with high accuracy. This study aims to compare the performance of three machine learning algorithms, namely Naïve Bayes, Support Vector Machine, and Random Forest, in analyzing public sentiment towards the Tapera policy. This study analyzes public comment data obtained from Twitter. We measure the accuracy of each algorithm to determine its optimal performance in sentiment classification. The research method consists of several stages, starting with data collection, text preprocessing to clean and prepare data, and then applying the three algorithms to analyze sentiment. The results showed that Naïve Bayes had the highest accuracy of 69.17%, followed by Support Vector Machine with an accuracy of 68.42%, and Random Forest with an accuracy of 66.17%. This shows that Naïve Bayes is the most effective algorithm to use in sentiment analysis of public comments related to the Tapera policy, especially in the context of complex text data from social media. The conclusion of this study is that Naïve Bayes is superior in classifying public sentiment towards the Tapera policy compared to Support Vector Machine and Random Forest. As a result, this study makes a significant contribution to selecting the most appropriate machine learning algorithm for public sentiment analysis towards public policy, which in turn can help the government understand and respond to public perceptions more effectively
Factors Analysis Of Digital Transformation Challenges In Alfamart Company
No full textTechnological advancements occur continuously without our notice, requiring us to adapt to them in all aspects of life. Most firms now recognize the importance of digital transformation as a strategy for improving services and business efficiency. Alfamart, a minimarket company in Indonesia's retail industry, is facing a technological transformation. Alfamart offers a range of product categories to accommodate diverse family requirements. The acceleration of digital transformation in Indonesia necessitates the application of digital technology as a digital platform that serves as the foundation for the Industry 4.0 ecosystem by including technologies such as IoT, big data, artificial intelligence, and augmented reality. This study uses quantitative and descriptive approaches to identify the characteristics that challenge digital transformation at PT Sumber Alfaria Trijaya, Tbk (Alfamart), particularly in the International Business & Technology division. The research employs two-factor analyses: CFA (Confirmatory Factor Analysis) and EFA (Exploratory Factor Analysis). According to the research results, 4 (four) factors influencing Alfamart's digital transformation, particularly in the International Business & Technology section, shape the company's digital transformation issues. These challenges include IT, digitalization, digital business, and digital skills
The Impact of Leadership, Work Motivation and Work Environment on Employee Performance at XYZ Resto
No full textThis study aims to analyze leadership, work motivation, work environment and employee performance at XYZ Resto; to analyze the influence of leadership, work motivation and employee work environment on employee performance. This study uses quantitative methods with a descriptive and verification approach. Data collection techniques are carried out by distributing questionnaires, which must be tested for validity and reliability. The population in this study were employees at all XYZ Resto branches, totaling 250 people, where the sample was taken as much as 40% to 100 people. This study uses path analysis as a data analysis tool. The hypothesis is that leadership, work motivation and work environment have a significant effect on employee performance at XYZ Resto. Based on the research findings, it was found that the influence of the three variables of Leadership, Motivation and Work Environment simultaneously on the Employee Performance variable is 62.5%. While 37.5% is influenced by other variables outside those studied
Analysis Of Public Interest In Smartfren SIM Cards Using The K-Nearest Neighbors Method
No full textThe use of Smartfren SIM cards is increasing along with the public's need for fast and stable internet services. However, a deep understanding of public interest in the SIM card is necessary to optimize marketing strategies and increase sales. Proper analysis can help companies identify potential target markets and develop effective marketing strategies. We chose the K-Nearest Neighbors method to analyze public interest in using Smartfren SIM cards. This study aims to develop and evaluate the K-Nearest Neighbors model in predicting public interest in using Smartfren SIM cards. This study uses a dataset containing information about Smartfren SIM card users. We divide the data into two sets: a training set for model building and a test set for evaluating model performance. We apply the K-Nearest Neighbors method to classify the data into two categories: interested and not interested. We evaluate the model performance using accuracy, precision, recall, and F1-score metrics. We present the evaluation results as a confusion matrix. The developed K-Nearest Neighbors model showed excellent performance with an accuracy of 94.29%, a precision of 94.20%, a recall of 100%, and an F1-score of 97.01%. These results indicate that the K-Nearest Neighbors model is effective in predicting people's interest in Smartfren SIM cards. The high recall value indicates that the model is able to identify all interested individuals without missing any, while the high precision value indicates that the model rarely makes false positive prediction errors. This study concludes that the K-Nearest Neighbors method is very effective for use in analyzing people's interest in using Smartfren SIM cards. We can rely on the developed model's strong performance for real-world applications in marketing strategies
Antecendents Of Hotel Performance With Organizational Ambidexterity As Mediation On Employee of Three Star Hotels In Special Region Of Jakarta
No full textThe research aims to test and analyze the factors that influence Hotel Employee performance among 3 star hotel employees in Jakarta The unit of analysis is 322 individual employees who work for employees from 10 3-star hotels in Jakarta. Cross-sectional and one-shot data collection was carried out through structured questionnaires distributed via Google Form and also directly. Asymmetric causal research design using quantitative methods. The proposed model includes 123 hypotheses and is tested using Structural Equation Modeling (SEM). The majority of respondents were women aged 20-24 years, with contract employee status, staff positions, working period of less than 5 years with a high school/vocational school/equivalent education level. The results of the test found that Ambidextrous Leadership, Ambidextrous Organizational Culture and Organizational Ambidexterity had a positive influence on Hotel performance while Organizational Ambidexterity had a positive influence from Ambidextrous Leadership and Ambidextrous Organizational Culture The research results can help deepen understanding of the complexity of the relationship between HR Flexibility, ambidextrous, amdixterous leadership and High Performance Work Leadership System on Hotel Employee Performance through organizational Ambidexterity
The Influence of the 7P Strategy on Passenger Satisfaction and Loyalty at Terminal 3 Soekarno-Hatta Airport: An Operations Management Approach
No full textThe COVID-19 pandemic highlighted the dependence of aeronautical revenue on external factors, making it crucial to increase non-aeronautical revenue. Major global airports like Changi and Incheon have achieved this revenue balance, but Indonesia's five largest airports, including Soekarno-Hatta and I Gusti Ngurah Rai, have not. Balanced non-aeronautical revenue can cover investment and promotional costs without relying on aeronautical income. Soekarno-Hatta, as a major hub, still has limited tenants, and retail and F&B revenues in Terminal 3 have significantly declined. To address this issue, reducing passenger queue times through digitalization and improving airport facilities has become a primary focus.
This research uses 400 questionnaires analyzed with structural equation modeling (SEM) using SmartPLS 4.0 software. The focus is on identifying the influence of the 7P—covering product (tenant variety), price, promotion, place, people (service quality), process (self check-in and immigration autogates), and physical evidence (cleanliness and terminal design)—on customer satisfaction and loyalty in Soekarno-Hatta's Terminal 3. Digitalization, such as self check-in and immigration autogates, is expected to reduce queue times, providing passengers with more time to shop and thus increasing non-aeronautical revenue. This study aims to find the most significant factors affecting customer satisfaction and customer loyalty at the airport. The results indicate that product, process and physical evidence have a positive and significant impact on both customer satisfaction and customer loyalty