International Journal of Science, Technology & Management (IJSTM)
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The Influence Of Beauty Influencer Marketing And Viral Marketing On Purchase Intention: The Mediating Role Of Brand Trust In The Originote Skincare Products
Full text linkThis study aims to examine the impact of beauty influencer marketing and viral marketing on purchase intention, with brand trust as a mediating variable in the context of the skincare brand The Originote. The use of influencer and viral marketing strategies has become increasingly popular among brand owners as a means to foster consumer trust and drive purchasing behaviour. A quantitative approach with an explanatory research design was adopted. Primary data were collected through an online questionnaire distributed to 160 male and female respondents aged 20 and above, all of whom are active social media users familiar with the influencers Tasya Farasya and Dokter Detektif. The data were analyzed using the Partial Least Square Structural Equation Modeling (PLS-SEM) method via SmartPLS 4.0 software. The findings reveal that both beauty influencer marketing and viral marketing have a positive and significant influence on brand trust and purchase intention. in addition, brand trust was found to significantly mediate the relationship between both types of marketing and purchase intention
The Effect Of Employee Engagement On Turnover Intention: The Mediating Role Of Job Satisfaction At PT XYZ, A Healthcare Provider Company
No full textEmployee engagement is a critical factor in managing human resources in the healthcare sector. Low engagement may reduce job satisfaction and increase turnover intention, affecting service quality and organizational stability. At PT XYZ, internal data show declining engagement and rising turnover intention in the past two years. This study aims to examine the effect of employee engagement on turnover intention, with job satisfaction as a mediating variable. Using a quantitative survey method, data from 131 permanent employees were analyzed with PLS-SEM. The expected result is that employee engagement negatively affects turnover intention, with job satisfaction mediating this relationship. Findings are expected to support policies to improve employee retention and satisfaction in healthcare services
Performance Evaluation of Machine Learning Algorithms in Aspect-Based Sentiment Analysis on E-Commerce User Reviews
No full textThe rapid growth of the e-commerce industry in Indonesia has resulted in a significant surge in the number of user reviews available on various digital platforms. These reviews contain valuable information about customer experiences related to price, product quality, service, delivery, and applications. However, the massive volume of data and its unstructured nature pose challenges in extracting relevant information. Aspect-Based Sentiment Analysis (ABSA) presents an approach that can provide deeper insights by identifying sentiment towards specific aspects within a review, rather than just the overall general sentiment. This study aims to evaluate the performance of several machine learning algorithms, namely Naïve Bayes, Support Vector Machine (SVM), Random Forest, and K-Nearest Neighbors (KNN), in implementing ABSA on e-commerce user reviews in Indonesia. The dataset used consists of 20,000 user reviews of the Shopee and Tokopedia applications obtained through a crawling process on the Google Play Store. The data is processed through several stages: text preprocessing, aspect and sentiment annotation, model training, and performance evaluation using accuracy, precision, recall, and F1-Score metrics. The evaluation results showed differences in performance among the tested algorithms. Naïve Bayes achieved an accuracy of 82.5%, KNN achieved 84.6%, Random Forest 87.1%, while SVM provided the best performance with an accuracy of 89.3% and an F1-Score of 88.3%. This difference in performance indicates that algorithms that are better able to handle high-dimensional text representations, such as SVM, are superior in aspect-based sentiment classification compared to other methods. Thus, this study not only provides a comprehensive overview of the effectiveness of machine learning algorithms in sentiment analysis in the e-commerce sector but also provides a practical basis for developing recommendation systems, improving customer service, and enhancing user experience strategies on digital platforms. This research is expected to serve as a reference in the application of machine learning to support the growth of the e-commerce industry in Indonesia
Assessing Service Quality, Product Quality, And Brand Image On Repurchase Intention Through Customer Satisfaction At Arunika Restaurant Palembang: A Pilot Study
No full textIn Palembang’s increasingly competitive food and beverage (F&B) industry, customer retention has become a pressing challenge for businesses like Arunika Restaurant. Despite serving over 1,600 customers monthly, the restaurant faces fluctuating sales and limited product differentiation in a market where digital engagement plays a critical role. This study investigates the influence of service quality, product quality, and brand image on repurchase intention, with customer satisfaction as a mediating variable. A pilot test was conducted with 30 Arunika customers using a structured questionnaire distributed via face-to-face interactions and completed through Google Forms. The data were analyzed using SPSS to assess the instrument’s validity and reliability. All items demonstrated Corrected Item Total Correlation (CITC) values above 0.3 and Cronbach’s Alpha values exceeding 0.7 (Indrawati, 2015). Furthermore, loading factors surpassed 0.70, AVE values exceeded 0.50, and Composite Reliability (CR) values ranged from 0.871 to 0.909, confirming strong internal consistency and convergent validity (Hair et al., 2022). These results support the instrument’s suitability for use in further analysis of repurchase behavior in the F&B sector
Exploratory Analysis and Identification of Factors Challenging Digital Transformation in Bio Farma Group
No full textIn the era of Industry 4.0, companies must adapt to remain competitive, including through digital transformation. Bio Farma, a leading vaccine manufacturer in Indonesia and the parent of the state-owned pharmaceutical holding (Bio Farma Group), is undergoing such a transformation. This includes subsidiaries like Kimia Farma, Indofarma, and INUKI. To accelerate this process, Bio Farma established the Directorate of Transformation and Digital to coordinate initiatives across all levels of the organization. This study explores and identifies the main challenges in the company’s digital transformation using a mixed-methods approach with an exploratory sequential design. Data were collected from interviews with five key informants and surveys involving 327 employees across the Bio Farma Group. A combination of qualitative and quantitative analysis, including Confirmatory Factor Analysis (CFA), was used to uncover the core challenges. The findings revealed 13 key factors: digital capability, strategy, technology, organization and culture, digital efficiency, digital readiness, customer focus, digital research, investment perception, operations, collaboration, investment review, and digital priority. These challenges extend beyond technical issues to strategic planning, organizational readiness, cultural alignment, collaboration, and investment evaluation. This research provides a strategic reference for managing digital transformation, particularly for state-owned enterprises in the health sector. The results are expected to support Bio Farma Group in formulating effective policies to enhance digital capabilities, strengthen collaboration, improve efficiency, and ensure sustainable digital development.
 
Application Of The Profile Matching Method For A Decision Support System In Selecting The Quality Of Fresh Fruit Marks (FFB) Of Oil Palm Worth Harvesting
No full textOil palm has an important role for the country's economy and is one of the commodity crops for Indonesian plantations. The oil content in palm oil has benefits for everyday life such as cooking oil, processed food, cosmetics and so on. Selection of quality fresh fruit bunches (FFB) for oil palm suitable for harvest requires a method to determine which fresh fruit bunches (FFB) are very suitable. One way to do this is by using the profile matching method. The profile matching method is a method of making decisions by assuming that there is an ideal variable level. The results of the study concluded, among others: the decision support system used to assist in selecting the quality of fresh fruit bunches (FFB) of oil palm worth harvesting. The application of the profile matching method can make decisions in selecting the quality of fresh fruit bunches worth harvesting based on ranking for the 30 samples used. TBS20 with a value of 4.9 is ranked first and TBS16 with a value of 3 is ranked last
Web-based Palm Oil Seedling Sales Information System (Case Study: CV. XYZ)
No full textOil palm seedling sales are one of the important aspects of the agricultural industry in Indonesia. However, conventional sales processes often encounter various obstacles, such as limited access to information for consumers, difficulties in inventory management, and low operational efficiency. To overcome these problems, this study aims to develop a Web-based Oil Palm Seedling Sales Information System at CV. XYZ. We designed this system to offer a comprehensive solution for sales management, encompassing stock recording and real-time transaction processing. This study uses a system development method with the waterfall method, in which the development stages include requirements, system design, implementation, verification, and maintenance. We collected data through direct observation at CV XYZ, interviews with management and customers, and related literature studies. Users then tested the prototype to identify potential problems and gather feedback for system improvement. According to the study's findings, the implementation of this web-based information system has resulted in increased efficiency in sales and inventory management. Users can easily access product information, place orders, and track the status of their orders. In addition, this system also allows integration with payment gateways, so that the transaction process becomes faster and safer. This system simplifies customer data management, sales recording, and financial report analysis from a management standpoint. At CV. XYZ, the development of the Web-based Palm Oil Seedling Sales Information System positively impacted operational efficiency and effectiveness. This system not only increases customer satisfaction by providing faster and more transparent services, but it also helps management make more accurate decisions based on available data. We need to add more advanced data analysis features to forecast sales trends and market demands, and integrate the system with e-commerce platforms to broaden our market reach
Customer Satisfaction Mediates Service Quality And Price Perception On Customer Loyalty
No full textThe present study aims to analyse the effect of service quality and price perception on loyalty, as mediated by customer satisfaction, in the context of the selection of educational institutions by parents of students. The study adopts a quantitative approach, utilising a survey method, and involves 181 respondents who are parents of students. These respondents were selected through a purposive sampling technique. The data collection was conducted through a Google Form-based questionnaire, while data analysis employed the Structural Equation Modeling (SEM) method, utilising WarpPLS V.8 software. The results of the analysis demonstrate that service quality and price perception exert a substantial influence on parental satisfaction and loyalty. The study concluded that good service quality fosters trust and satisfaction, while reasonable price perception fosters long-term loyalty. The findings of this study corroborate the significance of service and pricing strategies in enhancing learner retention
The Role of Training and Assistance in Improving the Utilization of Accounting Information Systems to Improve The Quality of Financial Reports In the SMEs Sector
No full textThis study aims to analyze the role of training and mentoring to improve the quality of financial reports in the SMEs sector in Sragen Regency by utilizing an accounting information system. This study uses a survey method with the type of data used quantitative data and primary data sources. Sampling used a purposive sampling technique and 58 SMEs became respondents in this study. The results of the study concluded that the use of Accounting Information System has a positive and significant effect on the quality of financial reports, while the understanding of accounting no effect on the quality of financial reports. Training and mentoring variables moderate the relationship between use of Accounting Information System and quality of financial reports. Meanwhile, the variable use of Accounting Information System on the quality of financial reports cannot be moderated by training and mentoring
Analysis of Enterprise Resource Planning Integration in Supply Chain Management at PT. Dayamitra Telekomunikasi (Mitratel)
No full textThis study aims to understand and analyze the integration of Enterprise Resource Planning (ERP) systems in Supply Chain Management (SCM) at PT Dayamitra Telekomunikasi. The method used in this research is qualitative research. Data collection techniques were conducted through interviews with managers and officers from Mitratel. The results of the study indicate that the integration of ERP in SCM at Mitratel has a positive impact on the efficiency and effectiveness of SCM operations, allowing the company to gain a competitive advantage. Research on ERP integration in SCM at PT Dayamitra Telekomunikasi is still limited. Therefore, it is recommended to conduct further in-depth research on ERP integration in SCM at Mitratel