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Taqwa Hariguna
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IJIIS: International Journal of Informatics and Information Systems
Published by Bright Publisher
ISSN : -     EISSN : 25797069     DOI : https://doi.org/10.47738/ijiis
Core Subject : Science,
Computer Science & IT
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.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 9 Documents
 1 
Search results for , issue "Vol 4, No 1: March 2021" : 9 Documents clear
implementing the Expected Goal (xG) model to predict scores in soccer matches Izzatul Umami; Deden Hardan Gautama; Heliza Rahmania Hatta
International Journal of Informatics and Information Systems Vol 4, No 1: March 2021
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i1.76

Abstract

Football is a sport that has the most fans in the world. What makes sebak patterns so popular are their uncertain and unpredictable results. There are many factors that affect the outcome of a football match, including strategy, skill, and even luck. Therefore, guessing the results of a soccer match is an interesting problem. All shots are grouped into sections on the playing field and theoretical goal scores are applied to each area. The factors analyzed are: distance of shot from goal and angle of shot in relation to goal. When calculating xG, it is recommended that the distance and angle of the shot are important. The combination of the two xG factors is better calculated than each variable only. In addition, this xG check has been able to relatively accurately identify the mid-table teams that score and concede goals.
Comparison of Min-Max normalization and Z-Score Normalization in the K-nearest neighbor (kNN) Algorithm to Test the Accuracy of Types of Breast Cancer Henderi Henderi; Tri Wahyuningsih; Efana Rahwanto
International Journal of Informatics and Information Systems Vol 4, No 1: March 2021
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i1.73

Abstract

The purpose of this study was to examine the results of the prediction of breast cancer, which have been classified based on two types of breast cancer, malignant and benign. The method used in this research is the k-NN algorithm with normalization of min-max and Z-score, the programming language used is the R language. The conclusion is that the highest k accuracy value is k = 5 and k = 21 with an accuracy rate of 98% in the normalization method using the min-max method. Whereas for the Z-score method the highest accuracy is at k = 5 and k = 15 with an accuracy rate of 97%. Thus the min-max normalization method in this study is considered better than the normalization method using the Z-score. The novelty of this research lies in the comparison between the two min-max normalizations and the Z-score normalization in the k-NN algorithm.
Analysis of the Effect of Website Sales Quality on Purchasing Decisions on e-commerce Websites Deden Hardan Gutama; Izzatul Umami; Pujo Hari Saputro
International Journal of Informatics and Information Systems Vol 4, No 1: March 2021
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i1.79

Abstract

Both Web-based information infrastructure and marketing activities are dealt with by business-to-consumer electronic commerce. Centered on information systems and marketing literature, this review suggests a research model to explain the effect on consumer loyalty of the dimensions of website quality (system quality, information quality, and service quality). In order to verify the validity of the calculation model, confirmatory factor analysis was performed, and the structural model was also examined to investigate the correlations hypothesized in the study model. In this study, by comparing the Hyperparameter class & Catboost class we can find a number of distributions of individual absolute errors which can be considered as a fairly important factor in the analysis of sales quality on e-commerce websites.
Comparison of Security Signing Data Authentication Integrity in Combination of Digest And AES Message Algorithm Rasna Rasna; Irjii Matdoan; Sitti Alam
International Journal of Informatics and Information Systems Vol 4, No 1: March 2021
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i1.72

Abstract

Online information systems with the Single Sign-On (SSO) model are currently widely used by many companies. Single Sign-On (SSO) is an independent authentication model. This system runs on the Hypertext Transfer Protocol (HTTP) protocol. Sending data or information without security is at risk of eavesdropping on information by the authorities. This study aims to compare the combination of Message-Digest and Advanced Encryption Standard (AES) algorithms to improve data security by modifying dynamic keys. The test results show that in each execution the user name and password with the MD5 algorithm are always the same while in the AES algorithm the results are always different so it is safe from replay attacks. So that the Advanced Encryption Standard (AES) algorithm can secure data through the Single-Sign-On authentication process with high-security accuracy.
With topological data analysis, predicting stock market crashes Nugroho Agung Prabowo; R Arri Widyanto; Mukhtar Hanafi; Bambang Pujiarto; Meidar Hadi Avizenna
International Journal of Informatics and Information Systems Vol 4, No 1: March 2021
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i1.78

Abstract

We are investigating the evolution of four big US stock market indexes' regular returns after the 2000 technology crash and the 2007-2009 financial crisis. Our approach is based on topological data processing (TDA). To identify and measure topological phenomena occurring in multidimensional time series, we use persistence homology. We obtain time-dependent point cloud data sets using a sliding window, which we connect a topological space for. Our research indicates that a new method of econometric analysis is offered by TDA, which complements the traditional statistical tests. The tool may be used to predict early warning signs of market declines that are inevitable.
Implementation of the Convolutional Neural Network Method to Detect the Use of Masks Arbiati Faizah; Pujo Hari Saputro; Augusta Jannatul Firdaus; Raden Nur Rachman Dzakiyullah
International Journal of Informatics and Information Systems Vol 4, No 1: March 2021
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i1.75

Abstract

The planet has been taken seriously by Coronavirus disease since the end of 2019. Wearing a mask in public is one of the key means of security for people. Furthermore, certain public service vendors only require clients to use the service if they wear masks correctly. However, based on image processing, there is relatively little study into the discovery of face masks. Almost everybody appears to wear a mask in order to shield themselves from the COVID-19 Pandemic. Monitoring whether people in the crowd wear face masks at the most public place, such as malls, museums, parks, has become increasingly important. The development of an AI approach to deal with if the person wears a face mask and their entrance would significantly assist society. In this article, we will use a deep learning model that is then combined with Keras / TensorFlow & OpenCV, respectively CNN or Confusional Neural Network. The accuracy of the research results obtained from this model is more than 96%.
Modelling Customers Lifetime Value For Non-Contractual Business Riyanto Riyanto; Abdul Azis
International Journal of Informatics and Information Systems Vol 4, No 1: March 2021
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i1.77

Abstract

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.
Comparison of K-Means Clustering & Logistic Regression on University data to differentiate between Public and Private University Adhien Kenya Anima Estetikha; Deden Hardan Gutama; Musthofa Galih Pradana; Dhina Puspasari Wijaya
International Journal of Informatics and Information Systems Vol 4, No 1: March 2021
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i1.74

Abstract

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%).
Predicting Airline Passenger Satisfaction with Classification Algorithms Hayadi, B.Herawan; Kim, Jin-Mook; Hulliyah, Khodijah; Sukmana, Husni Teja
International Journal of Informatics and Information Systems Vol 4, No 1: March 2021
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i1.80

Abstract

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.

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