International Journal of Artificial Intelligence Research最新文献

{"title":"Javanese Culture-Based Digital Book for Foreign Speakers","authors":"Budhi Setiawan, K. Saddhono, Muhammad Rohmadi","doi":"10.29099/ijair.v8i1.1.1197","DOIUrl":"https://doi.org/10.29099/ijair.v8i1.1.1197","url":null,"abstract":"Digital textbooks are learning tools that support distance learning needs, especially Indonesian for foreign speakers. It is important to develop digital textbooks based on Javanese culture as a vehicle for introducing Javanese culture as well as improving Indonesian language skills. In order to answer the formulation of the problem, research, design, and development of compatible, valid, and reliable digital textbooks were carried out. The effectiveness of digital textbooks is analyzed through the analysis of accessibility, media quality, legability, easy to understand, cultural representation, clarity, ease of use, and navigation. The results of the assessment are used as the basis for product improvement so that it can be applied more widely in improving Indonesian language proficiency for foreign speakers. In general, product development is divided into (1) development of Indonesian language teaching materials based on Javanese culture, and (2) development of android-based textbooks, starting from making flowcharts, story boards, and developing multimedia based on Javanese culture. The topic of Javanese culture was well presented and was able to increase enthusiasm for learning Indonesian for foreign speakers. Final product evaluation to see the usability of digital textbooks, including functionality, reliability, usability, efficiency, maintainability, and protability which showed very significant results. ","PeriodicalId":334856,"journal":{"name":"International Journal of Artificial Intelligence Research","volume":"80 26","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141818844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Proposed Framework for ERP System Implementation in SMEs","authors":"Danang Setiawan, Muhammad Fahrezha, Nur Abdillah Bagus Prakoso, Qurtubi Qurtubi","doi":"10.29099/ijair.v7i2.1102","DOIUrl":"https://doi.org/10.29099/ijair.v7i2.1102","url":null,"abstract":"SMEs face numerous challenges and opportunities due to their pivotal roles in the economic development of a country. Adopting an ERP system is believed to be the catalyst to cope with the challenges and grab the opportunities faced by SMEs. However, implementing ERP led to potential risks caused by implementation failure, even for big companies. SMEs have a unique characteristic due to being receptive to adopting new technologies but having limited resources. Most previous research related to designing frameworks for ERP implementation was focused on big companies, although the fact that SMEs have distinct characteristics compared to big companies. Therefore, this study aims to design a framework for SMEs' ERP implementation. The framework phase consists of (1) measuring the business maturity, information communication and technology (ICT) maturity, proposed business process improvement, and (2) implementing an ERP system. The author has also provided a case study of ERP adoption in an SME in this paper by compiling both steps. This research will contribute to research on ERP in SMEs and practice as guidance for ERP implementors and SMEs in adopting the ERP system","PeriodicalId":334856,"journal":{"name":"International Journal of Artificial Intelligence Research","volume":"29 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating Sentiment Analysis and Quality Function Deployment for Product Development","authors":"Abdullah 'Azzam, Syafira Mahardiningtyas, Qurtubi Qurtubi","doi":"10.29099/ijair.v7i2.1100","DOIUrl":"https://doi.org/10.29099/ijair.v7i2.1100","url":null,"abstract":"The development of technology and media has made online data reviews a promising data source. Through machine learning utilizing text processing, data analysis of Ventela Public Low product reviews can be carried out—sentiment analysis is used to find class groups from each data. The classification algorithm is Naïve Bayes and Support Vector Machine (SVM). A classification model with the best performance and accuracy values will be selected. Word association is then applied to obtain information from the required class. Quality Function Deployment (QFD) is a tool used to assist designers in developing products. The results of the integration of sentiment analysis into QFD show that sentiment analysis produces information by the provisions of the QFD method and can support the product development process in terms of the amount of data various data topics and reduces the subjectivity of designers at the stage of determining Voice of Customer (VOC) and performance values of products and competitors","PeriodicalId":334856,"journal":{"name":"International Journal of Artificial Intelligence Research","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140514798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of SQL Injection Attack Using Machine Learning Based On Natural Language Processing","authors":"Joko Triloka, H. Hartono, Sutedi Sutedi","doi":"10.29099/ijair.v6i2.355","DOIUrl":"https://doi.org/10.29099/ijair.v6i2.355","url":null,"abstract":"There has been a significant increase in the number of cyberattacks. This is not only happening in Indonesia, but also in many countries.  Thus, the issue of cyber attacks should receive attention and be interesting to study.  Regarding the explored security vulnerabilities, the Open Web Application Security Project has published the Top-10 website vulnerabilities. SQL Injection is still become one of the website vulnerabiliteis which is often exploited by attacker. This research has implemented and tested five algorithms. They are Naïve Bayes, Logistic Regression, Gradient Boosting, K-Nearest Neighbor, and Support Vector Machine. In addition, this study also uses natural language processing to increase the level of detection accuracy, as a part of text processing. Therefore, the main dataset was converted to corpus to make it easier to be analyzed. This process was carried out on feature enginering stage. This study used two datasets of SQL Injection. The first dataset was used to train the classifier, and the second dataset was used to test the performance of classifier. Based on the tests that have been carried out, the Support Vector Machine get the highest level of accuracy detection. The accuracy of detection is 0.9977 with 0,00100 micro seconds per query time of process. In performance testing, Support Vector Machine classifier can detect 99,37% of second dataset. Not only Support Vector Machine, the study have also revealed the detection accuracy level of further tested algorithms: K-Nearest Neighbor (0,9970), Logistic Refression (0,9960), Gradient Boosting (0,99477), and Naïve Bayes (0,9754).","PeriodicalId":334856,"journal":{"name":"International Journal of Artificial Intelligence Research","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130679895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Student Opinions on the Use of High-Tech Mobile Devices in the Design of Digital Games for Learning","authors":"Eva Jeanette, Brooks Ovchinnikova, H. Nurdiyanto","doi":"10.29099/ijair.v6i2.358","DOIUrl":"https://doi.org/10.29099/ijair.v6i2.358","url":null,"abstract":"Schools have adopted digital technologies as a strategy for learning and teaching activities because it offers opportunities for scaffolding. This strategy has been implemented in conjunction with creative activities. In addition, activities based on digital games, known as digital game-based learning (DGBL), and various mobile technologies, have been piloted in schools over the past few years to develop innovative learning. The purpose of this research is to investigate how children's collaborative interactions develop while participating in activities requiring them to solve problems utilizing intelligent and mobile technology. Our research combines theoretical viewpoints on joint participation, affordances, and a sense of community in the context of collaborative interactions. This is done with a contextual perspective on learning as its starting point. The following are some of the questions posed in this research: (1) How do children's digital game design activities drive and support collaborative interactions while they are engaged in problem-solving activities? Furthermore, (2) How do children's ideas for designing digital games manifest themselves during activities involving the design of games that involve innovative mobile technology? The study is based on a case where a creative workshop was held with 22 Swedish third-grade children aged 9 to 10 years old who participated in game design activities in a pedagogical lab. When the children worked together to solve the problem of designing and producing a joint digital game idea using mobile technology, a sense of community emerged due to their efforts. The study's results were analyzed using a thematic approach, which revealed that the children used different orientations in their collaborative interactions. Based on this, we argue that it is crucial to be aware of the pedagogical context when preparing for educational activities that involve innovative mobile technology. This is because the pedagogical context is the aspect of the design that creates meaningful collaborative interactions, and it is only then that innovative mobile technology becomes smart. These findings have significant ramifications for the methodological field of incorporating cutting-edge mobile technology into various types of educational settings","PeriodicalId":334856,"journal":{"name":"International Journal of Artificial Intelligence Research","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127607775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Approach for Recognition and Identification of Low-Level Flight Military Aircraft using Naive Bayes Classifier and Information Fusion","authors":"A. D. W. Sumari, Afifah Millatina Nugraheni, Y. Yunhasnawa","doi":"10.29099/ijair.v6i1.248","DOIUrl":"https://doi.org/10.29099/ijair.v6i1.248","url":null,"abstract":"A problem that has been faced by the Radar is if the aircraft flies at low level or near to the surface so its coming in the aerial-surveillance airspace cannot be detected and endangers the air sovereignty. The aircraft can be recognized and identified by carrying out a technique called Visual Aircraft Recognition (VACR) using a binocular. This technique requires military personnel that has capability carrying out the air surveillance from the ground. Surveillance is a time-consuming and tiring task so it can cause fatigue and impact to the results of the recognition and identification. To cope with this problem, we have designed and implemented a novel recognition and identification method using the combination of Naive Bayes Classifier (NBC) and information fusion. By using a dataset that consists of 45 military aircrafts, 35 civilian aircrafts, 40 military helicopters, and 35 civilian helicopters with 80:20 dataset distribution for the training scheme and the validation one, we obtained the recognition accuracy of 87.1%. We also found that the recognition and identification process can be speeded up 1.2 seconds when using information fusion.","PeriodicalId":334856,"journal":{"name":"International Journal of Artificial Intelligence Research","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124437983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Framework Authentication e-document using Blockchain Technology on the Government system","authors":"Isyak Meirobie, Agus Irawan, H. Sukmana, Diana Putri Lazirkha, N. Santoso","doi":"10.29099/ijair.v6i2.294","DOIUrl":"https://doi.org/10.29099/ijair.v6i2.294","url":null,"abstract":"As a sophisticated platform, namely Blockchain, which has 3 (three) potentials to change the governance system which is still considered traditional, solve the problem of principal agents, and minimize the crime of document falsification. However, in the government sector, the documents used can be insecure and lead to document falsification. Blockchain is becoming increasingly significant in document services and beyond until questions arise about the authenticity and security of manuscripts and documents in the government sector. So, Go-Chain (Government Blockchain) it is necessary to authenticate documents using Blockchain to minimize document forgery. By utilizing the potential of Blockchain technology, this research aims to maximize government e-documents in a modern and secure manner. Propose a Blockchain-based document framework method that is applied with a literature review study—in addition to ensuring the speed of system execution by utilizing DAO (Decentralized Autonomous Organization) and Smart Contracts. The result is that modern and safe government e-documents in document verification can significantly maintain transparency and increase trust in public services.","PeriodicalId":334856,"journal":{"name":"International Journal of Artificial Intelligence Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130229100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Journal Unique Visitors Forecasting Based on Multivariate Attributes Using CNN","authors":"Aderyan Reynaldi Fahrezza Dewandra, A. Wibawa, U. Pujianto, Agung Bella Putra Utama, A. Nafalski","doi":"10.29099/ijair.v6i1.274","DOIUrl":"https://doi.org/10.29099/ijair.v6i1.274","url":null,"abstract":"Forecasting is needed in various problems, one of which is forecasting electronic journals unique visitors. Although forecasting cannot produce very accurate predictions, using the proper method can reduce forecasting errors. In this research, forecasting is done using the Deep Learning method, which is often used to process two-dimensional data, namely convolutional neural network (CNN). One-dimensional CNN comes with 1D feature extraction suitable for forecasting 1D time-series problems. This study aims to determine the best architecture and increase the number of hidden layers and neurons on CNN forecasting results. In various architectural scenarios, CNN performance was measured using the root mean squared error (RMSE). Based on the study results, the best results were obtained with an RMSE value of 2.314 using an architecture of 2 hidden layers and 64 neurons in Model 1. Meanwhile, the significant effect of increasing the number of hidden layers on the RMSE value was only found in Model 1 using 64 or 256 neurons.","PeriodicalId":334856,"journal":{"name":"International Journal of Artificial Intelligence Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129182202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Mobile Deep Learning Model on Covid-19 CT-Scan Classification","authors":"Prastyo Eko Susanto, Arrie Kurniawardhan, Dhomas Hatta Fudholi, R. Rahmadi","doi":"10.29099/ijair.v6i1.257","DOIUrl":"https://doi.org/10.29099/ijair.v6i1.257","url":null,"abstract":"COVID-19 pandemic is currently happening in the world. Previous studies have been done to diagnose COVID-19 by identifying CT-scan images through the development of the novel Joint Classification and Segmentation System models that work in real-time. In this study, the author focuses on a different motivation and innovation focused on the development of mobile deep learning. Mobile Net, a deep learning model as a method for classifying the disease COVID-19, is used as the base model. It has a good level of efficiency and reliability to be implemented on devices that have small memory and CPU specifications, such as mobile phones. The used data in this study is a CT-scan image of the lungs with a horizontal slice that has been classified as positive or negative for COVID-19. To give a broader analysis, the author compares and evaluates the model against other architectures, such as MobileNetV3 Large, MobileNetV3 Small, MobilenetV2, ResNet101, and EfficientNetB0. In terms of the developed mobile architecture model, the classification of COVID-19 using MobileNetV2 obtained the best result with 0.81 accuracy.","PeriodicalId":334856,"journal":{"name":"International Journal of Artificial Intelligence Research","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121855432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Analytic Network Process Method Approach to Design Models of Lecturers Performance Evaluation","authors":"F. Purwani","doi":"10.29099/ijair.v6i2.283","DOIUrl":"https://doi.org/10.29099/ijair.v6i2.283","url":null,"abstract":"One approach to greatly enhance the quality of university education level is improving the quality and career of lecturers, including services to students. Therefore, performance and work ethic are critically evaluated to obtain re-liable information. Most performance evaluations are limited to assess students in the classroom exclusively. This research employed a Multi-Criteria Decision Making (MCDM), a model designed to evaluate the lecturer’s performance and factors influencing their performance. These factors were examined from various variables, such as training and development experience, motivation, self-esteem, competency, and job satisfaction. To demonstrate the correlation and dependency among factors of lecture performance evaluation, this study employed the Analytic Network Process (ANP) method, which is part of MCDM technique. The ANP method could serve different levels of stakeholders by considering available criteria and sub-criteria. Moreover, the method could predict performance measurement of human resources by considering factors affecting lecturer’s performance. This research produced a model to evaluate lecturers’ performance effectively","PeriodicalId":334856,"journal":{"name":"International Journal of Artificial Intelligence Research","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129351013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}