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Analyzing Customers in E-Commerce Using Dempster-Shafer Method Nazaruddin, Erizal; Caroline; Andrijanni; Sulistyawati, Upik Sri
International Journal Software Engineering and Computer Science (IJSECS) Vol. 3 No. 2 (2023): AUGUST 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v3i2.1497

Abstract

This research explores the analysis of consumer sentiment in the context of e-commerce by applying the sophisticated Dempster-Shafer method. We started with the collection of more than 20,000 consumer reviews from various leading e-commerce platforms and continued with a detailed data pre-processing stage to obtain a clean and structured dataset. Next, we leverage the Dempster-Shafer method to represent and combine information from multiple sources, addressing uncertainty in diverse consumer opinions. The results of the sentiment analysis show that the Dempster-Shafer method achieves an accuracy of around 85%, with good evaluation metrics. Additionally, this research provides insight into the factors that influence consumers' views of products or services in the growing e-commerce context. The literature review also reveals the potential application of the Dempster-Shafer method in other aspects of e-commerce business, such as risk management and consumer trust. This research highlights the contribution of the Dempster-Shafer method in addressing uncertainty and complexity in consumer sentiment analysis, yielding a deep understanding of consumer perceptions, and enabling more accurate decision making in a dynamic e-commerce context. This research also provides a foundation for further development in consumer sentiment analysis and the application of the Dempster-Shafer method in e-commerce.
E-Commerce Supply Chain Optimization with the MOORA Method and Certainty Factor Caroline
International Journal Software Engineering and Computer Science (IJSECS) Vol. 3 No. 2 (2023): AUGUST 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v3i2.1506

Abstract

This study analyzes supply chain optimization on e-commerce platforms by applying the MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) and Certainty Factor methods. The aim of this research is to gain in-depth insights into the relative performance of e-commerce platforms in the context of predefined criteria and sub-criteria. The research methodology consists of six stages, including data collection, selection of criteria and sub-criteria, application of Certainty Factor, selection of case studies, relative analysis using MOORA, and certainty level analysis using Certainty Factor. The results of the analysis show that these two methods provide valuable insights regarding the performance of e-commerce platforms. The MOORA method provides a relatively strong rating, while the Certainty Factor provides an additional dimension by considering the level of certainty regarding the factors that affect performance. From a comparison of the results of the two methods, platforms such as Tokopedia.com and Shopee consistently rank well in both analyses. The implication of this research is that the e-commerce platform has greater development potential in supply chain optimization efforts. Overall, the integration of the MOORA and Certainty Factor methods has succeeded in providing more detailed and comprehensive insights into supply chain optimization on e-commerce platforms. This research provides guidance for stakeholders in making more informed and directed decisions regarding supply chain optimization strategies in e-commerce platforms
Analysis of E-Commerce Purchase Patterns Using Big Data: An Integrative Approach to Understanding Consumer Behavior Caroline; Yuswardi; Rofi'i, Yulianto Umar
International Journal Software Engineering and Computer Science (IJSECS) Vol. 3 No. 3 (2023): DECEMBER 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v3i3.1840

Abstract

This research undertakes a meticulous examination of the Indonesian e-commerce industry, aiming to unravel the intricate patterns governing consumer behavior within this rapidly evolving digital landscape. Employing an extensive dataset and cutting-edge data analysis methodologies, this study discerns pivotal trends that have engendered transformative shifts in Indonesia's e-commerce sector. A conspicuous trend uncovered is the escalating reliance on instant messaging platforms and social media conduits for e-commerce transactions. This pronounced transition underscores the remarkable adaptability of businesses to the digital milieu, thereby accentuating the significance of a digitally oriented business paradigm. Furthermore, this research brings to light the prevailing predilection among non-formal e-commerce enterprises, whose revenues predominantly dwell below the IDR 300 million threshold. Notably, the Cash on Delivery (COD) method remains the preeminent payment mechanism. These observations illuminate the structural underpinnings of the market and consumer payment proclivities, thereby exerting a discernible influence on pricing strategies and payment processing mechanisms adopted by enterprises. Moreover, the study delves into the transformative effects of the COVID-19 pandemic, which have expedited the digital metamorphosis of both consumers and e-commerce enterprises. This acceleration has ushered in a new epoch characterized by novel opportunities and concomitant challenges within the e-commerce domain. In summation, this research furnishes a multidimensional and academically rigorous perspective on the Indonesian e-commerce landscape, furnishing actionable insights indispensable for businesses and policymakers alike. The comprehension of these evolving trends is indispensable for strategic formulation and policy calibration, enabling adept navigation of the dynamic e-commerce milieu.
Enhancing Online Learning Experiences through Personalization Utilizing Recommendation Algorithms Caroline; Oroh, Oliviane; Pada, Damir
International Journal Software Engineering and Computer Science (IJSECS) Vol. 3 No. 3 (2023): DECEMBER 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v3i3.1852

Abstract

This research investigates the implementation and impact of personalized learning systems underpinned by advanced recommendation algorithms in the realm of online education. The study encompasses a diverse group of participants from various educational backgrounds and explores their interactions with the personalized learning platform. The key findings of this research are noteworthy. Participants who had access to the personalized learning environment exhibited a substantial increase in engagement, satisfaction, and learning outcomes compared to those in the control group. This signifies the transformative potential of personalized learning in online education. The research emphasizes the critical role of personalization in enhancing learner engagement and satisfaction. It highlights how learners actively engaged with the system, making use of personalized recommendations to tailor their learning experiences. Moreover, the study sheds light on the positive impact of personalization on learning outcomes, indicating that learners achieved higher academic performance when their learning experiences were customized to their needs and preferences. In addition to its benefits for learners, the research underscores the advantages of personalized learning for instructors. The system provided instructors with valuable insights into each learner's progress and challenges, enabling more targeted and effective support. While the study demonstrates the effectiveness of personalized learning, it acknowledges certain limitations, including a relatively limited sample size and short duration. Future research endeavors could involve larger and more diverse samples and extend the study duration to gain a more comprehensive understanding of the long-term effects of personalized learning. In conclusion, this research contributes to the growing body of literature on personalized learning in online education. It provides compelling evidence that personalized learning, facilitated by sophisticated recommendation algorithms, can significantly enhance the online learning experience. The findings offer insights for educators and institutions looking to integrate personalized learning features into their online platforms to improve learner engagement, satisfaction, and learning outcomes.
Analisis Perbandingan Merek Smartphone Apple dan Samsung pada Mahasiswa Fakultas Ekonomi Universitas Swasta di Jakarta Susbiyantoro; Caroline; Aninam, Johny; Nugraha, Aat Ruchiat
Jurnal EMT KITA Vol 7 No 4 (2023): OCTOBER 2023
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/emt.v7i4.1547

Abstract

The rapid development of the telecommunications sector, especially the smartphone sector, has created fierce competition among different brands to win the hearts of consumers. This study aimed to determine the differences in brand associations between the two market leaders, Apple iPhone, and Samsung, among students of the Faculty of Economics of a private university in Jakarta. Data was collected through a survey of 100 respondents who have used or are currently using products from one of these brands. Data analysis results show a significant difference in brand associations between Apple iPhone and Samsung. The high t value (9.296 > 1.984) confirms that this difference is statistically significant. These results provide valuable information about how these two brands are perceived by students in the School of Economics, which can be used to improve branding and marketing strategies within a market. growing and more competitive. This study makes an important contribution to understanding the dynamics of brand associations in the context of the rapidly evolving smartphone industry.
Analisis Dampak Kualitas Layanan Pada Fakultas Ekonomi Universitas di Provinsi Jawa Timur, Jawa Barat dan Jawa Tengah Hanafi, Imam; Trisolvena, Muhammad Nana; Caroline; Sumiati, Siti
Jurnal EMT KITA Vol 7 No 4 (2023): OCTOBER 2023
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/emt.v7i4.1604

Abstract

This study analyzes the impact of service quality at the Faculty of Economics of several universities in the provinces of East Java, West Java, and Central Java. This study aims to evaluate the correspondence between expectations and reality of 100 students from different Economics Faculties in 3 research provinces using the Convenience Sampling method. Research results show that there is a significant difference between expectations and reality in terms of reliability, showing that service quality at economics faculties in three provinces has still not met students' expectations. A similar phenomenon occurs in relation to the responsiveness factor, highlighting the need to increase the level of service responsiveness. The analysis also highlighted the need to improve trust and empathy elements in services, with significant discrepancies between expectations and reality. T-test results confirm that service quality, especially in the aspects of reliability, responsiveness, trustworthiness, empathy, and tangibility, still does not fully meet students' expectations. Faculty of Economics of three provinces. Therefore, relevant universities should increase efforts to improve the aspects of reliability, responsiveness, trustworthiness, empathy, and tangibility so that students can have more confidence in the services are provided. It is hoped that this step will have a positive impact in enhancing student satisfaction and their academic success.
Peran Kepemimpinan Komunikasi Internal dan Pengembangan Karir Terhadap Kepuasan Kerja Karyawan Pada Perusahaan Telekomunikasi Anshori, M Isa; Caroline; Putro, Suryati Eko; Ariyadi, Muhammad Yusuf
Jurnal EMT KITA Vol 7 No 4 (2023): OCTOBER 2023
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/emt.v7i4.1672

Abstract

This research is an empirical study which aims to analyze the impact of leadership, internal communication, and career development on employee job satisfaction at Plasa Telkom East Java and Central Java Province. The research was conducted at the Plaza offices of East Java and Central Java Province involving the employee population (93 respondents) and using questionnaires and documentation as data collection tools. The research results show that partially, leadership and internal communication have a significant impact on employee job satisfaction, while career development does not show a significant impact. Overall, these three variables have a significant impact on the job satisfaction of Plasa Telkom employees in East Java and Central Java Province, with leadership as the most dominant factor, indicated by a regression coefficient value that is greater than the smallest probability value. The relationship between leadership, internal communication, career development and employee job satisfaction show a positive and significant correlation. However, the role of these three variables in supporting employee job satisfaction is still relatively less dominant, which may indicate that there are other factors outside the research framework that have a greater contribution to employee job satisfaction.
The Effect of Tax Knowledge and Tax Socialization on Motivation to Pay Taxes in STIE Eka Prasetya Students Tanelwy, Aurellia; Kosasih, Jocelin; Calosa, Charen; Caroline; Jesslyn; Stefanie; Tina Muhardika Handayani; Bambang Sutejo; Sudirman
Outline Journal of Management and Accounting Vol. 3 No. 1 (2024): June
Publisher : Outline Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61730/ojma.v3i1.141

Abstract

This study aims to determine the effect of partially or simultaneously Tax Knowledge and tax Socialixation on Motivation to Pay Taxes. The population in this study are STIE Eka Prasetya Students. The sampling technique in this study used saturated samples, which amounted to 35 students of 20.1 class. The research method used is the technique of collecting data through questionnaires. The analytical method used to solve problems and prove hypotheses is descriptive analysis, regression analysis. Partially Tax Knowledge has a positive and significant effect on Motivation to Pay Taxes and Tax Socialization has a positive and significant effect on Motivation to Pay Taxes. Simultaneously Tax Knowledge and Tax Socialization have a positive and significant effect on Motivation to Pay Taxes. The coefficient of determination test results (R2) shows that 56,1% of the Motivation to Pay Taxes variable is influenced by the Tax Knowledge and Tax Socializationvariable, while the remaining 43,9% is influenced by other variables outside of this study.
Comparison of Deep Neural Networks and Random Forest Algorithms for Multiclass Stunting Prediction in Toddlers Lestari, Wulan Sri; Saragih, Yuni Marlina; Caroline
Teknika Vol. 13 No. 3 (2024): November 2024
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v13i3.1063

Abstract

Stunting in toddlers is a serious global health issue, with long-term impacts on physical growth and cognitive development. To address this problem more effectively, it is crucial not only to identify whether a child is stunted but also to predict the severity of the condition. Multiclass stunting prediction offers deeper insights into a child’s condition, enabling more precise and targeted interventions. This study aims to compare the performance of multiclass stunting prediction models using two machine learning algorithms: Deep Neural Networks and Random Forest. The research process involved data collection, preprocessing, as well as model development and testing. The results show that the Random Forest model achieved 100% accuracy in training and 99.92% accuracy in testing, while the Deep Neural Networks model achieved 93.49% accuracy in training and 93.21% in testing. Both models demonstrated strong performance in multiclass stunting prediction, with Random Forest proving superior in terms of accuracy compared to Deep Neural Networks.
Juridical Analysis of Doctors Engaging in Collusion with Pharmaceutical Companies in Prescription of Medications Heriman, Amanda Regina Pallas; Caroline; Hasian, Clarisa Permata; Tobing, Ega Yolanda Lumban; Alexander, Johan; Naibaho , Novia
Lex Prospicit Vol. 2 No. 2: July 2024
Publisher : Universitas Pelita Harapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19166/lp.v2i2.7359

Abstract

In Indonesia, the legal rules that regulate the prohibition of doctors receiving gifts from pharmaceutical companies have not had a significant impact because the existing regulations only exist in the realm of ethics and administration. As a result, the collaboration between doctors and pharmaceutical companies in prescribing drugs continues and has a negative impact on patients. This research analyses the actions of doctors and pharmaceutical companies colluding in prescribing drugs to patients. The purpose of this research is to understand the legal responsibility of doctors and pharmaceutical companies colluding in prescribing drugs to patients, and also to understand the comparison of prevention of collusion between doctors and pharmaceutical companies in drug marketing in Indonesia and the United States. This study uses normative legal research because this research is only intended for written regulations, so this research is closely related to literature because it requires secondary data. The findings of this study indicate that collusion between doctors and pharmaceutical companies, which involves unethical or illegal agreements, can result in civil legal liability. However, if we review the law in the United States, the United States has stronger regulations, better transparency, and stricter legal sanctions in preventing collusion between doctors and pharmaceutical companies in drug marketing compared to Indonesia.