International Journal on Information and Communication Technology (IJoICT)最新文献

Performance Analysis of TCP Fractional Window Increment and Adaptive Fractional Window on IEEE 802.11 Multihop Ad Hoc Networks IEEE 802.11 多跳 Ad Hoc 网络上的 TCP 分数窗口递增和自适应分数窗口的性能分析

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2023-07-25 DOI: 10.21108/ijoict.v9i1.716

Arnas Sofyan, Vera Suryani, Hilal H. Nuha

引用次数: 0

Sentiment Analysis of Tourist Attraction Review from TripAdvisor Using CNN and LSTM 使用 CNN 和 LSTM 对 TripAdvisor 提供的旅游景点评论进行情感分析

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2023-07-24 DOI: 10.21108/ijoict.v9i1.756

Kevin Adrian Manurung

引用次数: 0

Implementation of the Learner Centered Design method and the personality approach (Case Study: Redesigning The Interface mobile LMS Tel-U) 实施以学习者为中心的设计方法和个性方法（案例研究：重新设计移动 LMS Tel-U 的界面）

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2023-07-17 DOI: 10.21108/ijoict.v9i1.723

Kurniawan Malik, Ati Suci, Dian Martha, Dawam Dwi, Jatmiko Suwawi

{"title":"Implementation of the Learner Centered Design method and the personality approach (Case Study: Redesigning The Interface mobile LMS Tel-U)","authors":"Kurniawan Malik, Ati Suci, Dian Martha, Dawam Dwi, Jatmiko Suwawi","doi":"10.21108/ijoict.v9i1.723","DOIUrl":"https://doi.org/10.21108/ijoict.v9i1.723","url":null,"abstract":"The Mobile LMS Tel-U is an e-learning platform developed by Telkom University to support the learning process. However, it still requires more demand from Telkom University students. Usability evaluation was conducted on twelve students using the System Usability Scale (SUS), resulting in a score of 46.5. Interviews and observations revealed interface problems on the dashboard, material, grades, and quizzes. This study aims to redesign the mobile LMS Tel-U interface using the Learner-Centered Design method and incorporating a personality approach by categorizing students into introverts and extroverts. Designing based on personality groups acknowledges the differences in interface design preferences and the relationship between personality and e-learning interface design. This approach yields two different interface designs, one for introverted students and one for extroverted students. The LCD method determines student needs in supporting the learning process. The redesigned interface's usability was evaluated using SUS to assess its appropriateness for students' learning needs. The study shows an average increase in usability scores of 80.4. The introverted student group achieved a usability score of 81, while the extroverted student group obtained a score of 80. Thus, the LCD method and personality approach effectively enhance the usability of distance learning applications (e-learning).","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139358800","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

Multi Aspect Sentiment Analysis of Mutual Funds Investment App Bibit Using BERT Method 使用 BERT 方法对共同基金投资应用程序 Bibit 进行多方面情感分析

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2023-07-05 DOI: 10.21108/ijoict.v9i1.718

Serly Setyani, S. S. Prasetiyowati, Y. Sibaroni

{"title":"Multi Aspect Sentiment Analysis of Mutual Funds Investment App Bibit Using BERT Method","authors":"Serly Setyani, S. S. Prasetiyowati, Y. Sibaroni","doi":"10.21108/ijoict.v9i1.718","DOIUrl":"https://doi.org/10.21108/ijoict.v9i1.718","url":null,"abstract":"With the rapid development of technology, an investor no longer needs to visit investment companies to make investments. Investors can conduct all investment transactions through their smartphone screens. Bibit is one investment application that can help investors invest in mutual funds. There are many reviews given by users every day, therefore, aspect-based sentiment analysis is needed to identify the aspects and sentiments of users from each review. BERT is one popular text classification method that currently has good performance. Therefore, aspect-based sentiment analysis will be carried out in this study using the BERT method with pre-trained IndoBERT on Bibit application reviews. From the multi-aspect sentiment analysis classification results, the service aspect had the highest average accuracy score of 0.92, the user satisfaction aspect had an average accuracy score of 0.87, and the system aspect had the lowest average accuracy score of 0.75. From the sentiment analysis results, the company can improve the system and service aspects of the Bibit application to provide better service & functionality.","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"98 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139362531","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

Overcoming Data Imbalance Problems in Sexual Harassment Classification with SMOTE 用SMOTE克服性骚扰分类中的数据不平衡问题

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2022-08-02 DOI: 10.21108/ijoict.v8i1.622

Aji Gautama Putrada, Irfan Dwi Wijaya, Dita Oktaria

{"title":"Overcoming Data Imbalance Problems in Sexual Harassment Classification with SMOTE","authors":"Aji Gautama Putrada, Irfan Dwi Wijaya, Dita Oktaria","doi":"10.21108/ijoict.v8i1.622","DOIUrl":"https://doi.org/10.21108/ijoict.v8i1.622","url":null,"abstract":"Delivery of justice with the help of artificial intelligence is a current research interest. Machine learning with natural language processing (NLP) can classify the types of sexual harassment experiences into quid pro quo (QPQ) and hostile work environments (HWE). However, imbalanced data are often present in classes of sexual harassment classification on specific datasets. Data imbalance can cause a decrease in the classifier's performance because it usually tends to choose the majority class. This study proposes the implementation and performance evaluation of the synthetic minority over-sampling technique (SMOTE) to improve the QPQ and HWE harassment classifications in the sexual harassment experience dataset. The term frequency-inverse document frequency (TF-IDF) method applies document weighting in the classification process. Then, we compare naïve Bayes with K-Nearest Neighbor (KNN) in classifying sexual harassment experiences. The comparison shows that the performance of the naïve Bayes classifier is superior to the KNN classifier in classifying QPQ and HWE, with AUC values of 0.95 versus 0.92, respectively. The evaluation results show that by applying the SMOTE method to the naïve Bayes classifier, the precision of the minority class can increase from 74% to 90%.","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"64 20","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120821574","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: 10

General Depression Detection Analysis Using IndoBERT Method 用IndoBERT方法进行一般抑郁检测分析

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2022-08-02 DOI: 10.21108/ijoict.v8i1.634

Ilham Rizki Hidayat, W. Maharani

引用次数: 3

Stock Portfolio Optimization on JII Index using Multi-Objective Mean-Absolute Deviation-Entropy 基于多目标均值-绝对偏差-熵的JII指数股票组合优化

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2022-08-02 DOI: 10.21108/ijoict.v8i1.623

D. Saepudin, Dimas Rizqi Guintana

引用次数: 0

Java Island Health Profile Clustering using K-Means Data Mining 使用K-Means数据挖掘的Java岛健康概况聚类

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2022-07-27 DOI: 10.21108/ijoict.v8i1.606

Muhammad Andryan Wahyu Saputra, S. Harini

引用次数: 0

Performance Analysis of the Hybrid Voting Method on the Classification of the Number of Cases of Dengue Fever 混合投票法在登革热病例数分类中的性能分析

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2022-07-27 DOI: 10.21108/ijoict.v8i1.614

Arief Rahman, S. S. Prasetiyowati

{"title":"Performance Analysis of the Hybrid Voting Method on the Classification of the Number of Cases of Dengue Fever","authors":"Arief Rahman, S. S. Prasetiyowati","doi":"10.21108/ijoict.v8i1.614","DOIUrl":"https://doi.org/10.21108/ijoict.v8i1.614","url":null,"abstract":"Dengue hemorrhagic fever (DHF) is a health problem in Indonesia. The region in Indonesia that has the highest number of cases in West Java with the highest ranking with 10,772 cases. The city of Bandung is recorded to have the highest number of cases at this time, namely 4,424 cases. Dengue fever can be caused by high rainfall. Judging from the high number of cases and fluctuations that occur, it is necessary to predict the spread of the disease so that in the future it can be anticipated by the government. Prediction of the spread of dengue fever in the city of Bandung using various classification algorithms has been done. Therefore, the author wants to make a new breakthrough by using hybrid ensemble learning using a hard voting method from three classification methods, namely Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Decision Tree (DT). Using the Bandung City DHF disease dataset from 2012 to 2018. The results obtained using the Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Decision Tree (DT) were 84%, 87%, 79%. to improve the classification accuracy of the three methods using a hybrid classification with the hard voting method to get 91% results.","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133822416","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

Multivariate Markov Chain Model for Sales Demand Estimation in a Company 某公司销售需求估计的多元马尔可夫链模型

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2022-01-01 DOI: 10.21108/ijoict.v7i2.604

Annisa Martina

{"title":"Multivariate Markov Chain Model for Sales Demand Estimation in a Company","authors":"Annisa Martina","doi":"10.21108/ijoict.v7i2.604","DOIUrl":"https://doi.org/10.21108/ijoict.v7i2.604","url":null,"abstract":"Estimation of the number of demands for a product must be done correctly, so that the company can get maximum profit. Therefore, this study discusses how to estimate the amount of sales demand in a company correctly. The model that will be used to estimate sales demand is the Multivariate Markov Chain Model. This model can estimate the future state by observing the present state. The model requires parameter estimation values first, namely the transition probability matrix and the weighted Markov chain, where in previous studies an estimation of the transition probability matrix has been carried out, so that in this study we will continue to estimate the weighted Markov chain parameters. This model is compatible with 5 data sequences (product types) defined as product 1, product 2, product 3, product 4, and product 5, with 6 conditions (no sales volume, very slow-moving, slow-moving, standard, fast moving, and very fast moving). As the result, the state probability for product 1, product 2 and product 3 in company 1 are stationary at state 6 (very fast moving), product 4 and product 5 are stationary at state 2 (very slow moving).","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133894610","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: 1