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The Impact on Review Credibility and Trust from Review Solicitation on E-commerce 6

The Impact on Review Credibility and Trust from Review Solic...

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6th IEEE International Conference on Cybernetics and Computational Intelligence, CyberneticsCom 2022

作者： Halim, Erwin Muzakir, Zahran Fawwaz Hebrard, Marylise School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Institut des Usages Enterprise Law Program Study Montpellier France

ISBN: (数字)9781665497428

ISBN: (纸本)9781665497428

It has widely known that Online Customer Reviews have become an integral part of customer decision-making before making online purchases. Sellers and platforms alike develop a strategy to shape reviews profitably under the pretext of increasing sales. Review Solicitation has been used to increase review volume and review valance in the online review platform. Interestingly, while much research is conducted to find the impact of review solicitation on the characteristics of reviews generated, there is not much research done on the perception of customers who have experienced the review solicitation strategy that might pose a problem for parties involved. This study aims to fill the gap of previous studies in finding the answer to what happens to the review credibility and Trust from the customer perspective after review solicitation. The research used Sequential Equation Modeling (SEM) process from 112 data obtained using Purposive sampling with online respondents around the Jabodetabek area in Indonesia in March 2022. There are five variables (Review Solicitation Awareness, Review Solicitation experience, Review Credibility, Trust, and Purchase Intention) with four hypotheses in this study. This study found that customers' Reviews Solicitation Experience significantly influences review credibility. At the same time, customers' Reviews of Solicitation Awareness significantly influence Trust. Then, Trust significantly influences Purchase Intention. © 2022 IEEE.

关键词： Electronic commerce

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The Impact of Customer Satisfaction and Customer Trust to Repurchase Intention in Purchasing Digital Product at the Marketplace 23

The Impact of Customer Satisfaction and Customer Trust to Re...

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23rd International Seminar on Intelligent Technology and Its Applications, ISITIA 2022

作者： Halim, Erwin Hebrard, Marylise T. Laurent, Clalita Kurniawan, Yohannes Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Enterprise Law Program Study Institut Des Usages Montpellier France

ISBN: (数字)9781665460811

ISBN: (纸本)9781665460811

Internet technology in Indonesia is increasing nowadays, especially in e-commerce. With internet users in the third rank in Asia (212.35 million) [1] and the highest e-commerce usage (88.1%) percentage in the world [2]. E-marketplace, as one of the e-commerce types, is a platform that acts as a mediator or creates a bridge between sellers and buyers while doing an online transaction. Not only are physical products sold in the marketplace, but there are also digital products. Digital products are not physical but in the form of electronic. There have been many transactions on purchasing digital products in the marketplace because the price is affordable compared to other platforms. Therefore, this study will analyze the impact of customer satisfaction and customer trust on repurchase intention in purchasing digital products in the marketplace. This study used 246 respondents who have purchased a digital product through a marketplace and live around the Jabodetabek area (Jakarta, Bogor, Depok, Tangerang, Bekasi) in Indonesia in November 2021 with a purposive sampling method. Structural Equation Modelling (SEM) PLS is the statistical method to check three hypotheses with Smart PLS as a tool. This study shows that Customer Satisfaction and Customer Trust variables significantly impact Customer Loyalty, and Customer Loyalty substantially affects Repurchase Intention. Intention. © 2022 IEEE.

关键词： Customer satisfaction

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Optimizing Menu Bundling Strategies Through Apriori Algorithm in Sales Analysis

Optimizing Menu Bundling Strategies Through Apriori Algorith...

引用

Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Ahmad Sambang Setya Tama Faqih Hamami Taufik Nur Adi Information Systems Study Program Faculty of Industrial Engineering Telkom University Bandung Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

Indonesia, as one of the largest coffee producers and exporters in the world, has experienced significant growth in the number of coffee shops, driven by increasing consumer demand for ready-to-drink coffee. This study aims to enhance sales performance at Authen Café and Space through the implementation of a menu bundling strategy. By utilizing data mining techniques and the Apriori algorithm, customer purchasing patterns were analyzed to identify optimal menu combinations. The data was collected directly at Authen Cafe during the period from April to August 2028. The analysis revealed that bundling strategies, such as combining Ayam Rica-Rica with Es Kopi Susu Karamel, are effective in increasing sales volume and product popularity among consumers. Furthermore, this study evaluated the impact of offering discounts on bundled packages on the café's profitability, demonstrating that this approach can boost net profit without sacrificing profit margins. This research provides significant insights into the application of data-driven marketing strategies within the café'industry and offers guidance for more effective managerial decision-making.

关键词： Industries Consumer behavior Profitability Computational modeling Decision making Data models Association rule learning

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Minimum Message Length Mixture Modelling of Rainfall Data

Minimum Message Length Mixture Modelling of Rainfall Data

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Yudi Agusta Information Systems Study Program STIKOM Bali Denpasar Indonesia

Rainfall is an important part of people daily life, especially farmers. Agriculture, and also tourism, have been affected greatly by rainy season. As the climate changes, the chance of rainfall amount to change gets higher. Several studies have been performed regarding rainfall data including studies on rainfall model as well as clustering of regions based on rainfall data. However, assumption used in the studies is that the data comes from one class population. This paper reports a study conducted on rainfall data with assumptions that rainfall pattern changes and its data can come from several class populations. The rainfall data used in this study is taken from Badung Regency. The class population is also assumed to come from several distributions including Gamma, Gaussian, and Student t distributions. In developing the model, the Minimum Message Length (MML) principle is applied for both parameter estimation and model selection processes. The result shows that rainfall data comes from a one class Gamma distribution model. None of the classes has chosen Gaussian and Student t distributions as their class models. The model with a gamma value less than 1.0 is better fit with a less message length = 1076.329 bits compared to that with a gamma value greater than or equal to 1.0 with a message length = 1086.851 bits. The results also show that MML slightly performed better compared to Akaike information Criterion (AIC) and Schwarz’s Bayesian information Criterion (BIC), in terms of the probability bit-costings calculated from the modelling of sampled data. This shows that the uncertainty region involved in the MML modelling accommodates the unseen existing data better. The selected model implies that rainfall data is not normally distributed and tends to have higher probabilities for less rainfall amounts. This result can be further used in agricultural and tourism sectors in predicting the rainfall amount in the next period.

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Early Detection and Classification of Melanoma Based on Android MobileNet V2 Convolutional Neural Network

Early Detection and Classification of Melanoma Based on Andr...

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

作者： Prabandari, Jasmine Iswarini Dyah Sari, Christy Atika Rachmawanto, Eko Hari Irawan, Candra Altamer, Bilal R. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Mosul University Presidency University of Mosul Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer are usually done through manual screening and visual inspection. This process requires a long time, has high complexity, is subjective, and is prone to errors. CNN is one of the algorithms with advantages in accurate classification. In this research, early detection and classification of melanoma cancer were carried out based on two classes, namely benign and malignant using the Convolutional Neural Network method. Our proposed method yields an accuracy of 81.11% for the validation data. The accuracy results obtained can be improved by using more datasets and increasing the number of layers used. This study uses the CNN method using MobileNet V2 architecture to detect melanoma skin cancer. The class used is benign and malignant. © 2023 IEEE.

关键词： Convolutional neural networks

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Increasing Customer Loyalty in Food and Beverage MSMEs Through Social CRM

Increasing Customer Loyalty in Food and Beverage MSMEs Throu...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Gabriel Gui Andreas Raharto Condrobimo Enggal Sriwardiningsih Information System and Management School of Information System Bina Nusantara University Jakarta Indonesia Information Systems Study Program School of Information Systems Bina Nusantara University Jakarta Indonesia Management Study Program Business School Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350309508

ISBN: (纸本)9798350309515

Micro, Small, and Medium Enterprises (MSME) in the food and beverage (F&B) industry have mostly used social customer relationship management (SCRM) approaches to promote customer loyalty (CL). This method is extensively adopted in the digital era since it is thought to improve consumer satisfaction. The primary goal of this study is to examine how SCRM affects customer loyalty through the mediation of customer engagement (CE), trust (TR), and enhanced customer service (ICS). This research received data from 350 respondents using Google Form and analyzed it using SmartPLS (SEM-PLS). The obtained data reveal that all hypotheses have a favorable and substantial effect on SCRM, CE, TR, ICS, and CL.

关键词： Industries Analytical models Data analysis Customer services Companies Data models Internet

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The Role of Social Media on Purchase Decisions in Indonesia: Perspective of Z Generation

The Role of Social Media on Purchase Decisions in Indonesia:...

引用

2023 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2023

作者： Vellamy, Flourency Wijaya, Dini Agnes Gui, Anderes Shaharudin, Muhammad Shabir Pitchay, Anwar Allah Chanda, Razib Chandra School of Information Systems Bina Nusantara University Information System Study Program Jakarta Indonesia School of Management Universiti Sains Malaysia Penang Malaysia Graduate School of Business Universiti Sains Malaysia Penang Malaysia

ISBN: (纸本)9798350347494

The technological revolution had a significant impact on people's lifestyles. With the development of technology, more and more social media are being created. Social media that is now widely used, namely Instagram, Facebook, TikTok, Twitter, etc. is one indication of the increasing use of the internet and people's need for online shopping. Currently, almost all social media have implemented live streaming and even shop features, which can increase usage and consumption rates, especially for Generation Z. Generation Z has an open way of thinking and likes instant things, including shopping. Apart from the convenience provided by social media, various impacts help Generation Z in making purchasing decisions. Therefore, this research was conducted to find out whether the role of social media can help Generation Z in making purchasing decisions, with the risks that exist in social media. With a sample of 300 respondents including Generation Z, who make purchasing decisions online, this research was collected through a quantitative survey method. The results of the questionnaire data will be analyzed using IBM SPSS version 28, while the model and structural measurements are analyzed using SmartPLS 4. The results of data collection show that Generation Z, in making purchasing decisions, does not care about the risks involved. Perceived risks are considered insignificant, but the theory holds that it is significant to consumers. Therefore, future research should consider whether the role of social media use in Generation Z has a different risk perception. © 2023 IEEE.

关键词： Risk perception

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Stunting Classification in Toddlers: Implementation and Evaluation of the Decision Tree Algorithm

Stunting Classification in Toddlers: Implementation and Eval...

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2024 International Conference on information Technology and Computing, ICITCOM 2024

作者： Alita, Debby Ahmad, Imam Jafar Rumandan, Rhaishudin Erkamim, Moh Widyasmoro Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Institut Agama Islam Negeri Ambon Islamic Education Management Study Program Ambon Indonesia Universitas Tunas Pembangunan Smart City Information Systems Study Program Surakarta Indonesia Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350379839

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data. © 2024 IEEE.

关键词： Classification Data Mining Decision Tree Stunting

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Level of awareness of Digital Banking Users on Risk and Security in Greater Jakarta 8

Level of awareness of Digital Banking Users on Risk and Secu...

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8th International Conference on Business and Industrial Research, ICBIR 2023

作者： Vellamy, Flourency Wijaya, Dini Agnes Gui, Anderes Ganesan, Yuvaraj Shaharudin, Muhammad Shabir Pitchay, Anwar Allah School of Information Systems Bina Nusantara University Information System Study Program Jakarta Indonesia Graduate School of Business Universiti Sains Malaysia Penang Malaysia School of Management Universiti Sains Malaysia Penang Malaysia

ISBN: (纸本)9798350399646

The development of technology in financial sector has change the monetary transaction system in the world. Currently, there are many banks provide services in digital banking because it is convenience to the users and, it has simplifies the movement and less time required compared to non-digital banking transaction. However, the side back of the digital banking to users are such as many frauds committed through digital banking, leaks or theft of users' data, when top-up balances are held up, interruptions when making transfers, and others. According to the OJK, with this digital transformation, cyber security attacks have increased by up to 86.70%. Therefore, it is important to seek and examine the awareness of digital banking users related to the risk and security of digital banking. 104 respondents participated in the self-administered questionnaire and we used a descriptive analysis to measure the level of awareness of risk and security of using digital banking. The descriptive results shows that more than 75% of respondents agree and are aware that digital banks have a fairly high-security risk, when doing top-ups there are frequent interruptions or pending, and the account is easy to access by anyone who knows our account. In addition, more than 15% of respondents feel that traditional banks have a higher risk, and fraud that occurs in digital banks does not occur often. The results of the study provides a preliminary information to the reader about the awareness of the digital banking in the context of Greater Jakarta. © 2023 IEEE.

关键词： Cybersecurity

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Mobile Payment Continuance Usage Intention in Indonesia 25

Mobile Payment Continuance Usage Intention in Indonesia

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25th International Conference on information Technology, IT 2021

作者： Seannery, G. Gui, A. Bina Nusantara University Accounting Information Systems Program Indonesia Bina Nusantara University Information Systems Study Program School of Information Systems Indonesia

ISBN: (纸本)9781728191034

Due to the increase in mobile payment user, this study explores the factors influencing continuance usage intention mobile payment in Indonesia. A total of 506 respondents are collected and analyzed using SmartPLS 3. The result revealed that additional values, perceived transaction convenience, and perceived risk are significant factor that positively affect continuance usage intention. However perceived security and trust surprisingly do not affect continuance usage intention of mobile payment in Indonesia. © 2021 IEEE.

关键词： Electronic money

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