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All Journal Jurnal Media Infotama Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Jurnal Informatika dan Teknik Elektro Terapan Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) Riau Journal of Computer Science International Journal of Artificial Intelligence Research JIKO (Jurnal Informatika dan Komputer) INOVTEK Polbeng - Seri Informatika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JOURNAL OF SCIENCE AND SOCIAL RESEARCH MIND (Multimedia Artificial Intelligent Networking Database) Journal JSAI (Journal Scientific and Applied Informatics) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Tekinkom (Teknik Informasi dan Komputer) Indonesian Journal of Electrical Engineering and Computer Science IJIIS: International Journal of Informatics and Information Systems Journal of Computer System and Informatics (JoSYC) JINAV: Journal of Information and Visualization Journal of Applied Data Sciences JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Journal of Applied Computer Science and Technology (JACOST) Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD International Journal for Applied Information Management Journal Corner of Education, Linguistics, and Literature JUSTIN (Jurnal Sistem dan Teknologi Informasi) ProBisnis : Jurnal Manajemen Edu Sociata : Jurnal Pendidikan Sosiologi JOURNAL OF ICT APLICATIONS AND SYSTEM Neraca Manajemen, Akuntansi, dan Ekonomi Cendikia Pendidikan Jurnal Media Akademik (JMA) Bhinneka Multidisiplin Journal Jurnal Manajemen Kewirausahaan dan Teknologi
B. Herawan Hayadi
Universitas Bina Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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Journal : Journal of Applied Data Sciences

 1 
Multiple Choice Question Difficulty Level Classification with Multi Class Confusion Matrix in the Online Question Bank of Education Gallery Siregar, Pariang Sonang; Hatika, Rindi Genesa; Hayadi, B. Herawan
Journal of Applied Data Sciences Vol 4, No 4: DECEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i4.132

Abstract

The importance of test question planning as a critical element in improving the quality of education is undeniable as it helps teachers evaluate student understanding. The creation of questions must consider the level of difficulty, which is often divided into three categories: easy, medium, and difficult. Predicting the difficulty level of questions has great importance as it helps teachers create test questions that match students' abilities. In this study, we view the identification of item difficulty as a classification problem. The data used includes questions from elementary and junior high school, with various machine learning methods applied to perform classification. We tested Random Forest, Logistic Regression, SVM, Gaussian, and Dense NN, considering embedding, lexical, and syntactic features. The evaluation results show that the best method in identifying the difficulty level of questions in subjects is using Random Forest, resulting in an accuracy of 84%. Meanwhile, in other cases, the best method is also Random Forest, with an accuracy of 80%. Our research shows that the use of feature embedding and TF-IDF has a significant positive impact on the accuracy of the resulting model.
An Extensive Exploration into the Multifaceted Sentiments Expressed by Users of the myIM3 Mobile Application, Unveiling Complex Emotional Landscapes and Insights Hayadi, B Herawan; Henderi, Henderi; Budiarto, Mukti; Sofiana, Sofa; Padeli, Padeli; Setiyadi, Didik; Swastika, Rulin; Arifin, Rita Wahyu
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.187

Abstract

This study investigates user sentiment towards the myIM3 application, an application used for telecommunication service management in Indonesia. Using text analysis and machine learning methods, we analyzed user reviews to identify dominant sentiment patterns and evaluate different classification models. Word cloud analysis, sentiment distribution, and donut plots were utilized to gain deeper insights into user preferences and issues. Results indicate that the majority of user reviews are neutral (52.2%), with 37% positive reviews and 33.4% negative reviews. Users consistently pay attention to aspects such as internet connection (Neutral: 92%, Positive: 95%, Negative: 87%) and pricing (Neutral: 92%, Positive: 92%, Negative: 93%) in their reviews. Evaluation of classification models like Decision Tree Classifier, Support Vector Machine (SVM), and Random Forest shows that the SVM model performs the best with an accuracy of 93%, high precision (Negative: 93%, Neutral: 92%, Positive: 95%), recall (Negative: 93%, Neutral: 95%, Positive: 91%), and F1-score (Negative: 93%, Neutral: 94%, Positive: 93%). These findings can serve as a basis for service improvement and better product development in the future, while also affirming the capability of text analysis and machine learning techniques in providing valuable insights for telecommunication service providers.
Unsupervised Learning Methods for Topic Extraction and Modeling in Large-scale Text Corpora using LSA and LDA Henderi, Henderi; Hayadi, B Herawan; Sofiana, Sofa; Padeli, Padeli; Setiyadi, Didik
Journal of Applied Data Sciences Vol 4, No 3: SEPTEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i3.102

Abstract

This research compares unsupervised learning methods in topic extraction and modeling in large-scale text corpora. The methods used are Singular Value Decomposition (SVD) and Latent Dirichlet Allocation (LDA). SVD is used to extract important features through term-document matrix decomposition, while LDA identifies hidden topics based on the probability distribution of words. The research involves data collection, data exploratory analysis (EDA), topic extraction using SVD, data preprocessing, and topic extraction using LDA. The data used were large-scale text corpora. Data explorative analysis was conducted to understand the characteristics and structure of text corpora before topic extraction was performed. SVD and LDA were used to identify the main topics in the text corpora. The results showed that SVD and LDA were successful in topic extraction and modeling of large-scale text corpora. SVD reveals cohesive patterns and thematically related topics. LDA identifies hidden topics based on the probability distribution of words. These findings have important implications in text processing and analysis. The resulting topic representations can be used for information mining, document categorization, and more in-depth text analysis. The use of SVD and LDA in topic extraction and modeling of large-scale text corpora provides valuable insights in text analysis. However, this research has limitations. The success of the methods depends on the quality and representativeness of the text corpora. Topic interpretation still requires further understanding and analysis. Future research can develop methods and techniques to improve the accuracy and efficiency of topic extraction and text corpora modeling.
Co-Authors -, Basorudin Abdi Rahim Damanik Adyanata Lubis Adyanata Lubis Adyanata Lubis, Adyanata agung setiawan Agus Perdana Windarto Agustina Akhmad Zulkifli Alvin, Muhammad Ambarsari, Yuke Aramiko Kayanie Nenden Atryana Arifin, Rita Wahyu Arman Basri Asep Supriyanto Asyahri Hadi Nasyuha Bachtiar, Marsellinus Bayu Kusuma Budi Yanto Budi Yanto Budi Yanto, Budi Budiarto, Mukti Cindy Paramitha Dahliyusmanto, Dahliyusmanto David Setaiwan Dede Nurhasanah Devi Delawati Didik Setiyadi Dwi ASTUTI Dwiastuti, Dwiastuti Edi Roseno Eghar Shafiera Eko Priyanto Engkos Kosasih Enny Widawati Erna Armita, NST Erni Rouza, Erni fatimah Fatimah Franciska, Yuni Furtasan Ali Yusuf Handayani, Meli Hartono Hartono Hayatul Masquroh Henderi . Hendrawati, Tuti Heni Pujiastuti Herlina Latipa Sari Hermawansyah, Hermawansyah Husni Teja Sukmana I Gede Iwan Sudipa Ichsan Firmansyah Ihlas Ahmad Subarkah Ilham Arifin Irawati Irawati irfan, mursyid ISKANDAR JAKA KUSUMA Jaka Kusuma Jaka Tirta Samudra Jaka Tirta Samudra Jin-Mook Kim Jufri -, Jufri Jufri Jufri Juhriah Juhriah, Juhriah Junaesih, R. Karina Andriani Kasman Rukun Kelvin Leonardi Kohsasih Khodijah Hulliyah Kim, Jin-Mook Luth Fimawahib Luth Fimawahib M Haidar Husein Mahdi, Ahmad Masquroh, Hayatul Muadifah, Muadifah muflihah muflihah Muhammad Sadikin Mulyadi, Dadi Musadad Musadad Novendra Adisaputra Sinaga Ovi Sakti Cahyaningtyas P. Eko Prasetyo P.P.P.A.N.W Fikrul Ilmi R.H. Zer Padeli Padeli Pardede, Doughlas Prasiwiningrum, Elyandri Pratama, Gelard Untirtha Puji Sari Ramadhan Rahmulyana, Anjar Raman Raman Raman, Raman Riandini, Meisarah RIKA ROSNELLY Rika Rosnelly Rinanda Rizki Pratama Rinanda Rizki Pratama Rindi Genesa Hatika Rizky Ema Wulansari Rohim, Rouf Rubianto Rudi Gunawan Saepudin Saepudin Safril Safril Sartika Mandasari Sepriyanti, Sepriyanti Siregar, Pariang Sonang Sofiana, Sofa sono, Aji Sudar Suheti, Suheti Suirat, Suirat Sumiyati SUMIYATI SUMIYATI Suwarni Suwarni Swastika, Rulin Tambunan, Fazli Nugraha Teddy Surya Gunawan Toyibah, Toyibah Tutut Herawan Uniba, Muadifah Utomo, Ahmar Dwi Wahdi, Adi Wanayumini Wiwik Handayani Wiwik Novianawati Yuke Ambarsari Yuni Franciska Tarigan Yuningsih, Yuyun Yustiva, Fitriyatul Zakarias Situmorang