IJIIS: International Journal of Informatics and Information Systems
The IJIIS is an international journal that aims to encourage comprehensive, multi-specialty informatics and information systems. The Journal publishes original research articles and review articles. It is an open access journal, with free access for each visitor (ijiis.org/index.php/IJIIS/); meanwhile we have set up a robust online platform and use an online submission system to ensure the international visibility and the rigid peer review process. The journal staff is committed to a quick turnaround time both in regards to peer-review and time to publication.
Articles
162 Documents
<![CDATA[A Study of Influence Factors for Advertising on Messaging Applications Towards Mobile Buyer's Decision Making ]]>
<![CDATA[Paireekreng, Worapat]]>;
<![CDATA[Osathanukroh, Jaruvarintra]]>;
<![CDATA[Supasak, Chavanit]]>
<![CDATA[ International Journal of Informatics and Information Systems Vol 2, No 2: September 2019 ]]>
Publisher : <![CDATA[International Journal of Informatics and Information Systems ]]>
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DOI: 10.47738/ijiis.v2i2.90
<![CDATA[The advancement of information technology leads to development of a new business paradigm which is focused on innovative technology. M-commerce seems to be a crucial tool to develop a country rapidly. The combination of messaging application features and business model can build start-up business driven by these technologies. However, the appropriate accessing target group of each business issues to be a main issue in the messaging application usage. This research aims to investigate the influence factors related to advertising on messaging applications. The Mixed method; quantitative and qualitative methods were implemented to investigate such factors. The findings are that three main factors, demographic factors, m-commerce factors, and behavioral factors, affected the buying decision making. Whereas, the demographic factor such as marital status showed no differences in this study. The products such as information technology accessories, beauty products and fashion goods are an important business area for customers focused on m-commerce. In addition, it was found that education had a significant effect towards advertising on messaging applications. Furthermore, the derived influence factors and criteria for advertising on messaging applications were confirmed with online merchants in the focused group method. The main advantage of messaging applications is the ability to interact with merchants and get quick responses. The results can be a guidance for start-up businesses for sustainable development.]]>
<![CDATA[Modelling Customers Lifetime Value For Non-Contractual Business ]]>
<![CDATA[Riyanto Riyanto]]>;
<![CDATA[Abdul Azis]]>
<![CDATA[ International Journal of Informatics and Information Systems Vol 4, No 1: March 2021 ]]>
Publisher : <![CDATA[International Journal of Informatics and Information Systems ]]>
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DOI: 10.47738/ijiis.v4i1.77
<![CDATA[Due to the increasing importance placed on customer equity in today's business environment, many companies are focusing on the notion of customer loyalty and profitability to increase market share. Building a successful Customer Relationship Management (CRM), a company starts from identifying true value and customer loyalty because customer value can provide basic information to spread more targeted and personalized marketing. In this paper, customer lifetime value (CLV) is used for customer segmentation in non-contracted businesses. The results obtained from this study are very acceptable. CLV has successfully analyzed and produced a fairly strong assumption about the value possessed by each customer whether they will make a return transaction or not.]]>
<![CDATA[Social Network Analysis for User Interaction Analysis on Social Media Regarding E-Commerce Business ]]>
<![CDATA[Nugroho Agung Prabowo]]>;
<![CDATA[Bambang Pujiarto]]>;
<![CDATA[Firmantya Safri Wijaya]]>;
<![CDATA[Lutfiana Gita]]>;
<![CDATA[Denny Alfandy]]>
<![CDATA[ International Journal of Informatics and Information Systems Vol 4, No 2: September 2021 ]]>
Publisher : <![CDATA[International Journal of Informatics and Information Systems ]]>
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DOI: 10.47738/ijiis.v4i2.106
<![CDATA[Abstract: E-commerce business requires promotion in introducing its products. One of the media that can be used is social media. There is a lot of information provided on social media, one of which is User Generated Content (UGC). UGC is a user's track record on social media that can be seen by other users. Social media analysis is needed to see the pattern of interaction between the company and its customers from UGC which is widely spread on social media. This can be used as an insight for companies in helping product marketing on social media. The method used in analyzing the interaction pattern of UGC in social media is Social Network Analysis (SNA). Social network modeling can help e-commerce businesses to understand the interaction patterns that occur on social media. The findings in this study show that the social network that is superior is the interaction social network regarding Lazada. Research also shows the key players for each e-commerce.]]>
<![CDATA[A Classification of Internet Pornographic Images ]]>
<![CDATA[Srisa-an, Chetneti]]>
<![CDATA[ International Journal of Informatics and Information Systems Vol 2, No 3: December 2019 ]]>
Publisher : <![CDATA[International Journal of Informatics and Information Systems ]]>
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DOI: 10.47738/ijiis.v2i3.96
<![CDATA[According to Pornography Statistics,more than 34 percent of Internet users exposeto pornography. There are 12 percent of the total number of websites and 72 million monthly visitors.Internet pornography (Internet Porn) is addictive to teenagers and kids around the world. The normal practice is to block those websites or filter out pornographyfrom kids.In order to do so, researchers has to find a way to detect and classify first. The pixel features including YCbCr range, area of human skin are chosen as pornographyfeatures because of their easy acquisition. C4.5 (Data mining technique)is applied to construct a decision tree. The purpose of this paper is to classify pornography images in a simple if-then rule. The accuracy of experimental result is 85.2%.]]>
<![CDATA[The Charisma of Online Group-Buying: The Moderating Role of Social Motivation ]]>
<![CDATA[Yi-Mu Chen]]>;
<![CDATA[Tseng-Lung Huang]]>;
<![CDATA[Sean Hung]]>
<![CDATA[ International Journal of Informatics and Information Systems Vol 2, No 3: December 2019 ]]>
Publisher : <![CDATA[International Journal of Informatics and Information Systems ]]>
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DOI: 10.47738/ijiis.v2i1.86
<![CDATA[Group buying can spread worldwide because the growth of the online shopping market has been considerable. In addition to deal popularity and discount rate, social motivation was included in this study. If a consumer cannot achieve an economic exchange benefit, a social exchange benefit might provide another function for the group member to stay in the community. This study adopted convenience sampling and an online questionnaire to conduct a survey. Among 240 questionnaires collected, 204 were valid. According to ANOVA analysis, the results demonstrated that social motivation has a positive influence on the relationship between the discount of a product and customers 'purchasing intention but not on the relationship between the popularity of a product and customers' purchasing intention. Therefore, we concluded that strengthening social networking can have a positive effect on customers' purchasing intention and thus encouraging the development of group purchasing retailers and related industries.]]>
<![CDATA[Analysis Of Internal Factors Affecting Bank Probability: Evidence From Listed Banks On Vietnam Stock Market ]]>
<![CDATA[Dieu Nguyen, Chi Thi]]>;
<![CDATA[Thuy Nguyen, Trang Thi]]>
<![CDATA[ International Journal of Informatics and Information Systems Vol 4, No 2: September 2021 ]]>
Publisher : <![CDATA[International Journal of Informatics and Information Systems ]]>
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DOI: 10.47738/ijiis.v4i2.111
<![CDATA[This study using the multivariate linear regression model based on the ordinary least squares method (OLS) to estimate the internal factors affecting profitability of 9 listed banks on Vietnam Stock Market for the period from 2008 to 2016. A sample with 81 observations was used in study model, and Return on assets (ROA) is used to measure banks’ profitability in the study model. The results indicated that capital size and loan have a positive and significant effect on bank profitability, and asset size, deposits, liquidity risk and bad debts have a negative and significant impact on bank profitability. These findings suggest that banks can improve their profitability through increasing capital size and loan, remaining asset size, deposits, liquidity risk and bad debts reasonably. These findings allow authors to give some solutions to support Vietnam commercial banks increasing their profitability in integration era]]>
<![CDATA[Comparison of K-Means Clustering & Logistic Regression on University data to differentiate between Public and Private University ]]>
<![CDATA[Adhien Kenya Anima Estetikha]]>;
<![CDATA[Deden Hardan Gutama]]>;
<![CDATA[Musthofa Galih Pradana]]>;
<![CDATA[Dhina Puspasari Wijaya]]>
<![CDATA[ International Journal of Informatics and Information Systems Vol 4, No 1: March 2021 ]]>
Publisher : <![CDATA[International Journal of Informatics and Information Systems ]]>
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DOI: 10.47738/ijiis.v4i1.74
<![CDATA[The development of advances in educational methods has developed in the last few decades. especially at the higher education level such as college. The rising interest of students in pursuing their higher education education has caused the sector to be split into two sectors, both private and public university. This difference raises several questions recently about how the two types differ in carrying out the educational process. whether there is a difference in terms of cost, service or quality, we really can't tell exactly. For this study, we will try to use the K-Means Clustering & Logistic Regression to group the University into two groups, Private and Public and then compare the two model accuracy. The results of this study show that the results obtained from the K-Means clustering model (22%) are much lower than the Logistic Regression model (91%).]]>
<![CDATA[Exploring The Relationships Among Social Benefits, Online Social Networks Dependency, Satisfaction and Youth's Habit Formation ]]>
<![CDATA[Tran, Van-Dat]]>;
<![CDATA[Trang, Huynh Ngoc Doan]]>
<![CDATA[ International Journal of Informatics and Information Systems Vol 1, No 2: December 2018 ]]>
Publisher : <![CDATA[International Journal of Informatics and Information Systems ]]>
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DOI: 10.47738/ijiis.v1i2.101
<![CDATA[Online social network is one of the biggest phenomenon of the Internet, which has attracted many marketers and psychologists to understand social network users' behavior. Recognizing lack of theoretical and empirical attention has been given to this field especially in Vietnam market, this study is conducted to examine the relationships among social benefits, online social network dependency, satisfaction and youth's habit formation in the context of Facebook. The findings of the study of 200 Facebook users indicate that the interrelationship among four factors of social benefits, online social network dependency, satisfaction and habit formation are affected each other. Indeed, online social network dependency among the youth whose age range from 16 to 24 years old is significantly affected by social benefits factor and also lead to the formation of habit. In addition, satisfaction plays a role in determining the habitual use of Facebook. This paper contains a discussion of theoretical and practical implication in marketing and psychology field.]]>
<![CDATA[Improving Music Recommendation System by Applying Latent Topics of Lyrics ]]>
<![CDATA[Thwe, Khine Zar]]>;
<![CDATA[Yukawa, Takashi]]>
<![CDATA[ International Journal of Informatics and Information Systems Vol 2, No 2: September 2019 ]]>
Publisher : <![CDATA[International Journal of Informatics and Information Systems ]]>
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DOI: 10.47738/ijiis.v2i2.91
<![CDATA[The proposed music recommendation system was developed by using various information filtering approaches based on user context and song context. This study proposes a music recommendation system with Latent Dirichlet Allocation (LDA) by using user listening behavior and analyzing a latent relationship of each song. As a consequence, small musical niche genres without listing history will become a member of their respective topic groups. Modeling topic analysis of LDA is utilized for songs lyric as well as the user action and, then song group preferences support the collaborative filtering recommendation engine. The system addresses the optimization of the cold start problem of adding new items in Collaborative Filtering by lyric analysis with LDA. Predicted ratings for user recalculated by combination matrix of song listening action with binary rating values and latent topic group result of lyrics. In this analysis, a system proposition compared with two models, normal collaborative filtering and user defined genre group preference.]]>
<![CDATA[Predicting Airline Passenger Satisfaction with Classification Algorithms ]]>
<![CDATA[Hayadi, B.Herawan]]>;
<![CDATA[Kim, Jin-Mook]]>;
<![CDATA[Hulliyah, Khodijah]]>;
<![CDATA[Sukmana, Husni Teja]]>
<![CDATA[ International Journal of Informatics and Information Systems Vol 4, No 1: March 2021 ]]>
Publisher : <![CDATA[International Journal of Informatics and Information Systems ]]>
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DOI: 10.47738/ijiis.v4i1.80
<![CDATA[Airline businesses around the world have been destroyed by Covid-19 as most international air travel has been banned. Almost all airlines around the world suffer losses, due to being prohibited from carrying out aviation transportation activities which are their biggest source of income. In fact, several airlines such as Thai Airways have filed for bankruptcy. Nonetheless, after the storm ends, demand for air travel is expected to spike as people return for holidays abroad. The research is aimed at analyzing the competition in the aviation industry and what factors are the keys to its success. This study uses several classification models such as KNN, Logistic Regression, Gaussian NB, Decision Trees and Random Forest which will later be compared. The results of this study get the Random Forest Algorithm using a threshold of 0.7 to get an accuracy of 99% and an important factor in getting customer satisfaction is the Inflight Wi-Fi Service.]]>
