International Journal of Advances in Data and Information Systems最新文献

Exploring Sentiment Trends: Deep Learning Analysis of Social Media Reviews on Google Play Store by Netizens 探索情感趋势：网民对 Google Play 商店社交媒体评论的深度学习分析

International Journal of Advances in Data and Information Systems Pub Date : 2024-03-28 DOI: 10.59395/ijadis.v5i1.1318

Rosa Eliviani, Dwi Diana Wazaumi

引用次数: 0

Classification of Students' Academic Performance Using Neural Network and C4.5 Model 利用神经网络和 C4.5 模型对学生的学习成绩进行分类

International Journal of Advances in Data and Information Systems Pub Date : 2024-03-25 DOI: 10.59395/ijadis.v5i1.1311

Sulika Sulika, Ririen Kusumawati, Yunifa Miftachul Arif

{"title":"Classification of Students' Academic Performance Using Neural Network and C4.5 Model","authors":"Sulika Sulika, Ririen Kusumawati, Yunifa Miftachul Arif","doi":"10.59395/ijadis.v5i1.1311","DOIUrl":"https://doi.org/10.59395/ijadis.v5i1.1311","url":null,"abstract":"ducation involves deliberately creating an environment and learning process to empower students to fully utilize their academic and non-academic potential. It encompasses fostering spiritual qualities, religious understanding, self-discipline, cognitive abilities, and skills necessary for personal, societal, national, and state development. Madrasah Aliyah, in particular, emphasizes preparing participants for higher studies in areas of their interest, thereby showcasing their academic prowess. The evaluation of educational models like Neural Networks is crucial for ensuring their effectiveness in problem-solving. This involves testing and assessing the performance of the Neural Network model to ensure its accuracy and reliability. Similarly, the C4.5 method, based on condition data mining, is utilized to measure classification performance by assessing accuracy, precision, and recall. Research findings indicate that the neural network algorithm is more adept at accurately classifying students' academic abilities compared to the C4.5 algorithm. With an accuracy of 92.6% for the neural network algorithm and 80.6% for the C4.5 algorithm, it is evident that the former is more precise in determining the classification of students' academic abilities. This highlights the suitability of the neural network approach for classifying academic abilities in Madrasah Aliyah. Furthermore, the insights gained from this classification process can be extrapolated to benefit other madrasas.","PeriodicalId":483284,"journal":{"name":"International Journal of Advances in Data and Information Systems","volume":" 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140381884","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}

引用次数: 0

Data-Driven Analytical Model Using Machine Learning Algorithms 使用机器学习算法的数据驱动分析模型

International Journal of Advances in Data and Information Systems Pub Date : 2024-03-25 DOI: 10.59395/ijadis.v5i1.1309

Harun Al Azies, Noval Ariyanto, Ishak Bintang Dikaputra

引用次数: 0

Integrated Multi-Income Stream Performance Dashboard: a Japanese Corporate Banking Case 综合多收入流绩效仪表板：日本企业银行案例

International Journal of Advances in Data and Information Systems Pub Date : 2024-03-15 DOI: 10.59395/ijadis.v5i1.1313

Krisnhu Hananta Rachansa, Wasesa Meditya

{"title":"Integrated Multi-Income Stream Performance Dashboard: a Japanese Corporate Banking Case","authors":"Krisnhu Hananta Rachansa, Wasesa Meditya","doi":"10.59395/ijadis.v5i1.1313","DOIUrl":"https://doi.org/10.59395/ijadis.v5i1.1313","url":null,"abstract":"In response to the complex operational challenges faced by Japanese Corporate Banking (JCB), arising from the coexistence of disparate core banking systems post-merger, this study aims to address inherent issues affecting marketing performance monitoring. The existing condition at JCB is characterized by data inconsistency, limited system interoperability, and fragmented income tracking through multiple Excel reports and management systems. Recognizing the gaps in the current setup, the research question revolves around how to enhance marketing performance monitoring effectively. The research objectives, therefore, encompass the development and implementation of a tailored integrated report utilizing the CRISP-DM methodology. This innovative performance dashboard harmoniously consolidates data from diverse sources, presenting a cohesive representation crucial for comprehensive marketing performance assessment. Leveraging advanced methodologies like data normalization and cross-platform integration, the research approach ensures streamlined income tracking, mitigating existing limitations. The data, drawn from various product applications, undergoes meticulous processing to facilitate a unified view on the integrated dashboard. The anticipated result is a significant improvement in monitoring efficiency, heightened data accuracy, and an empowered decision-making process within JCB's operations. The business implication of this initiative is the tangible enhancement of the bank's ability to comprehensively assess income performance, thereby elevating the quality of strategic decision-making and reinforcing JCB's competitive positioning in the banking sector.","PeriodicalId":483284,"journal":{"name":"International Journal of Advances in Data and Information Systems","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140391415","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}

引用次数: 0

Recommendation System for Selecting Web Programming Learning Materials for Vocational High School Students using Multi-criteria Recommendation Systems 利用多标准推荐系统为职业高中学生选择网络编程学习材料的推荐系统

International Journal of Advances in Data and Information Systems Pub Date : 2024-03-15 DOI: 10.59395/ijadis.v5i1.1317

Lia Wahyuliningtyas, Yunifa Mittachul Arif, Ririen Kusumawati

{"title":"Recommendation System for Selecting Web Programming Learning Materials for Vocational High School Students using Multi-criteria Recommendation Systems","authors":"Lia Wahyuliningtyas, Yunifa Mittachul Arif, Ririen Kusumawati","doi":"10.59395/ijadis.v5i1.1317","DOIUrl":"https://doi.org/10.59395/ijadis.v5i1.1317","url":null,"abstract":"In the independent curriculum, the learning that is carried out focuses on developing character, student competence and honing interests, talents. So the amount of learning material given to students does not have to be complete or less. Apart from that, the independent curriculum no longer burdens students with achieving a minimum score because assessments no longer use Minimum Completeness Criteria (KKM) scores. This makes it difficult for teachers to determine whether the material that has been explained can be understood because grades are not a benchmark for a student's success. In fact, if the teacher does not know a student's understanding, the teacher will have difficulty continuing to the next material. Implementation of the Multi-Criteria Recommender System (MCRS) can make it easier for teachers to predict whether students can progress to the next material and recommend which modules are suitable for these students. The recommendation system that will be built is in the form of web-based learning media so that students can be more interested and can help teachers improve learning outcomes. The method used is collaborative filtering by comparing adjusted cosine similarity, cosine based similarity and spearman rank order correlation. Based on the implementation of MCRS using the collaborative filtering method, it shows that the results of the recommendation system have a good impact on the teaching and learning process. Based on the 3 algorithms implemented, the best prediction result is cosine based similarity because the MAE value obtained is the lowest, namely 1.19 and the accuracy value is 76%.","PeriodicalId":483284,"journal":{"name":"International Journal of Advances in Data and Information Systems","volume":" 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140391400","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}

引用次数: 0

Recommendation of Prospective Construction Service Providers in Government Procurement Using Decision Tree 利用决策树推荐政府采购中的潜在建筑服务供应商

International Journal of Advances in Data and Information Systems Pub Date : 2024-03-15 DOI: 10.59395/ijadis.v5i1.1316

Eva Yustina, M. A. Hariyadi, Cahyo Crysdian

{"title":"Recommendation of Prospective Construction Service Providers in Government Procurement Using Decision Tree","authors":"Eva Yustina, M. A. Hariyadi, Cahyo Crysdian","doi":"10.59395/ijadis.v5i1.1316","DOIUrl":"https://doi.org/10.59395/ijadis.v5i1.1316","url":null,"abstract":"The determination of prospective construction service providers using the direct procurement method is the authority of the Goods/ Services Procurement Officer. Administrative requirements are an important factor in selecting prospective construction service providers. The use of the decision tree method in this study is to find out, determine, and analyse the variables that influence the assessment of the feasibility of prospective construction service providers, and get an accuracy value in providing an assessment of the feasibility of prospective construction service providers. The data used in this study are 153 datasets consisting of 13 variables. The existing variables are divided into basic variables and additional variables. The basic variables consist of 5 variables, namely experts, work experience, quality of work, winning tenders and contract value. While the additional variables consist of 8 variables namely business entity status, business entity form, business entity NPWP, business entity domicile, business entity qualification, type of business licence, percentage of work and construction services business licence. By using the decision tree method, the accuracy on the basic variable is 84.84%. The addition of additional variables to the basic variables resulted in an accuracy of 90.91%. This shows that by adding additional variables the accuracy results are higher than using only the basic variables.","PeriodicalId":483284,"journal":{"name":"International Journal of Advances in Data and Information Systems","volume":" 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140392272","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}

引用次数: 0