The Effect of Fidgeting On Student Concentration Levels

Concentration is the ability needed to solve a problem.  Students in learning also need concentration (DePorter et al., 2010). Unfortunately students have difficulty concentrating on doing a job. To help concentrate, students play pen, spin coins, play cellphones and other fun activities. To meet this goal, an agitated repellent device such as fidget spinner and fidget cube was made (Plafke, 2016). The benefits of spinner fidget for increasing concentration are still questionable (Schecter et al., 2017). Therefore, quantitative research is needed to prove the claim that fidget spinner can increase concentration. Unfortunately, there is currently no quantitative research that tests the effectiveness of these tools to increase short-term memory. The concentration level of a person can be measured using the Stroop test. Stroop tests utilize primitive cognitive operations, offering clues to the basic process of attention. The variable studied is Reaction Time for Correct Answer (RTCA), which is the amount of reaction time in answering correctly divided by the number of correct answers. The results of this study are the use of fidget spinner not having a significant effect on differences in the results of measurement of RTCA. The use of fidget spinner does not provide a significant difference in average error between not using fidget spinner and using fidget spinner

Different Impact of Critic’s and Fellow Customer’s Score at Online Review Aggregator on Customer Purchase Intention in Motion Picture Industry

The Motion picture industry is somehow a unique industry when compared to other industries. Ticket prices for all films are the same, because of that price is not the main variable in decision making for watching a film. A review can become one of the most powerful variable when choosing which film to watch by the customer. Other than that, different from other industries and products, reviews that come in the form of narrative and detailed expositions tend to be avoided by customers because it will ruin the satisfaction of watching films activity due to leakage of information from the film plot and storyline. One that can be an aid for film customer is online review aggregator’s score that accumulated from a bunch of scores that are given from either critics or fellow customer and it made online review aggregator viewed as a more objective reviewer. This study aims to find whose review at the online review aggregator website will be more influential on customer purchase intention of Indonesia’s moviegoers. Data of 220 Indonesia’s millennial generation were retrieved and analyzed during the research. This research finds out that customers in Indonesia can be influenced by score or rating that comes from online review aggregator, an equally good review from critics and customer can increase customer purchase intention and vice versa. Furthermore, customer’s score or rating is the one more influential by a small margin compared to the score from critics

Moderating Effects of Time-Related Factors in Predicting the Helpfulness of Online Reviews: a Deep Learning Approach

Given the importance of online reviews, as shown by extensive research, we address the problem of predicting the helpfulness of online product reviews by developing a comprehensive research model guided by the theoretical foundations of signaling and social influence theories. We use review order and time interval to incorporate the moderating effects of the time-related variable on the reviewer’s valuation of products and the related details they provide. Applying deep learning techniques in text processing and model building on a dataset of 239297 reviews, the empirical findings represent strong support of the proposed approach and show its superior performance in predicting review helpfulness compared to current approaches. This research contributes to theory by analyzing online reviews from the points of two well-known information processing theories and contributes to practice by developing a model to sort the newly posted reviews

Detect Fake Reviews Using Random Forest and Support Vector Machine

With the rapid development of e-commerce, which makes it possible to buy and sell products and services online, customers are increasingly using these online shop sites to fulfill their needs. After purchase, customers write reviews about their personal experiences, feelings and emotions. Reviews of a product are the main source of information for customers to make decisions to buy or not a product. However, reviews that should be one piece of information that can be trusted by customers can actually be manipulated by the owner of the seller. Where sellers can spam reviews to increase their product ratings or bring down their competitors. Therefore this study discusses detecting fake reviews on product reviews on Tokopedia. Where the method used is the distribution post tagging feature to perform detection. By using the post tagging feature method the distribution got 856 fake reviews and 4478 genuine reviews. In the fake reviews, there were 628 reviews written with the aim of increasing product sales or brand names from store owners, while there were 228 reviews aimed at dropping their competitors or competitors. Furthermore, the classification is carried out using the random forest algorithm model and the support vector machine. By dividing the dataset for training data by 80% while 20% for data testing. Here it is known that the support vector machine gets much higher accuracy than the random forest. The support vector machine gets an accuracy of 98% while the random forest gets an accuracy of 60

THE CREDIBILITY OF CONSUMER REVIEWS ON THREE E-COMMERCE IN INDONESIA: MIXED METHOD APPROACH

Online stores with more than 3000 reviews have made it difficult for consumers to find reviews that can be used as the main source of information to decide on a purchase. This research aims to investigate the credibility of reviews that consumers can be trusted. This research used mixed methods (quantitative and qualitative) through sequential explanation. In this quantitative study, 300 respondents were collected using a voluntary sampling technique, and 900 reviews from three e-commerce sites in Indonesia were selected purposely. The qualitative approach used in-depth interviews with three consumers and a selected seller using a purposive sampling technique. The data was processed by multiple linear regression and descriptive using SPSS 25.0 and Nvivo 12. Research results confirmed that the motivation to read reviews and consumer attitudes toward reviews significantly affect online purchasing decisions, but a third of consumers still rarely provide reviews. Furthermore, based on source credibility, E-WOM quality, and recommendation rating, in the three e-commerce sites, almost half of the reviews studied were hard to be trusted. Based on these findings, this research summarizes the policy implications for consumers and governments and suggests future research

Strengths, Opportunities and areas of Improvements for Maroof Platform in Saudi Arabia

Maroof is a new third-party platform that is managed by the Saudi Ministry of Commerce. Maroof is designed to evaluate, regulate, and organize stores and E-commerce practices in Saudi Arabia. This paper will examine the platforms\u27 strengths, opportunities, and recommendations for improvements. Maroof was designed to help buyers make purchase decisions and issue certificates to registered stores. A major strength of the platform is that sellers are encouraged to sign up with their social security number, which makes them known\u27\u27 to the Saudi Ministry of Commerce. Additionally, it legitimizes the store owners\u27 credentials. Therefore, Saudi citizens can feel more confident when purchasing goods from social media accounts that are registered with Maroof. Utilizing Maroof is one of the factors that increase trust in buying in Saudi Arabia, especially in E-commerce. The purpose of Maroof is to prevent any fraudulent activities as the platform allows buyers to report a claim easily. On the other hand, the Maroof is a new platform with a major shortcoming, and thus there are several opportunities to improve Maroof\u27s usability. The major area that could use improvement is the comments section. For instance, a registered sign in username and password is not required to post a review. The platform simply allows users to anonymously write product reviews and comments along with ratings of sellers or stores using their social media accounts. This paper\u27s aim is to review these comments on the Maroof platform, which is a supposed, reliable, and trusted governmental website. Although the Maroof team claims they are continuously working on detecting fake reviews, and the Ministry of Commerce states that Maroof provides authenticated reviews, findings of this paper show that there are many fake positive reviews on Maroof. As a result, the Saudi Ministry of Commerce should make it clear that ratings do not always represent the quality of a product, even on a governmental website

Are Online Consumer Reviews Credible? A Predictive Model based on Deep Learning

As the importance of online consumer reviews has grown, the concerns about their credibility being damaged by the presence of fake reviews have also grown. Extant literature reveals the importance of online reviews for consumers. Yet, there is a lack of research in the literature that considers consumer perception while developing a predictive model for the credibility of online reviews. This research aims to fill this gap by combining two different streams in the literature namely human-driven and data-driven approaches. To do so, we use two datasets with different labelling approaches to develop a predictive model, the first one is labelled based on the Yelp filtering algorithm and the second one is labelled based on the crowd’s perception towards credibility. Results from our predictive model reveal that it can predict credibility with a performance of 82% AUC, using reviews’ attributes namely, length, subjectivity, readability, extremity, external and internal consistency

THE CREDIBILITY OF CONSUMER REVIEWS ON THREE E-COMMERCE IN INDONESIA: MIXED METHOD APPROACH

Online stores with more than 3000 reviews have made it difficult for consumers to find reviews that can be used as the main source of information to decide on a purchase. This research aims to investigate the credibility of reviews that consumers can be trusted. This research used mixed methods (quantitative and qualitative) through sequential explanation. In this quantitative study, 300 respondents were collected using a voluntary sampling technique, and 900 reviews from three e-commerce sites in Indonesia were selected purposely. The qualitative approach used in-depth interviews with three consumers and a selected seller using a purposive sampling technique. The data was processed by multiple linear regression and descriptive using SPSS 25.0 and Nvivo 12. Research results confirmed that the motivation to read reviews and consumer attitudes toward reviews significantly affect online purchasing decisions, but a third of consumers still rarely provide reviews. Furthermore, based on source credibility, E-WOM quality, and recommendation rating, in the three e-commerce sites, almost half of the reviews studied were hard to be trusted. Based on these findings, this research summarizes the policy implications for consumers and governments and suggests future research

The social TV phenomenon and fake online restaurant reviews

Purpose – The social TV phenomenon has raised the interest of some researchers in studying the production of online reviews. However, little is known about the characteristics of reviewers that, without having had indeed a real experience of consumption, still dare to assess the service. The purpose of this research is to understand these reviewers better, using an experiment conducted in Brazil. Design/methodology/approach – Through a cluster analysis with 2547 reviewers of 7 restaurants that participated in a reality show in Brazil, we were able to create 4 fours. Using Spearman Correlation and Kruskal-Wallis Test, differences among groups were analysed in the search of behavioural changes among different types of reviewers. Findings – We conclude that social TV influence fake online reviews of restaurants that were involved in a tv show. Furthermore, we were able to verify that some reviewers indeed assess the service without indeed having tried the service, which strongly bias the influence they are going to cause in potential consumers. Four types of reviewers were identified: the real expert, the amateur reviewer, the speculator and the pseudo expert. The 2 latter types are analyzed through the anthropologic lens of the popular Brazilian culture and the TV influence in that country. Research limitations/implications – we were able to understand how TV can influence the construction of fake online reviews for restaurants. Practical implications – It is important for the restaurant and hospitality industry in general, to be able to be attentive to the phenomenon of fake reviews that can totally biased the advantages of this assessment system that was created to produce trust among consumers, but that can act exactly the other way around. Originality/value – This study highlights the relevance of taking into account cultural background of the country where the restaurant is located, as well as emphasizing the relevance of conducting a previous analysis of the decision of embarking on a reality show that it has high chances to biasedly influence consumers’ decisions.info:eu-repo/semantics/publishedVersio