[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117848-en":3,"doc-seo-117848-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117848,962075006959,"Anda","https://ap-avatar.wpscdn.com/avatar/e0002397efbe92a78e?_k=1776741047341049297",8,"Research & Report","Product Overview Sentiment Analysis Using Lexicon Hybrid-Based Approach and Machine Learning - Sentiment Analysis for Game Reviews","Sentiment analysis methods aim to capture opinion in review text using machine learning and lexicon-based vocabulary. Prior work relying only on machine learning produced unsatisfactory accuracy when a lexical/lexicon hybrid setup was used. This study proposes machine learning enhancements through a hybrid lexical approach that combines lexicon-based sentiment with probabilistic and SVM classification. Experiments on game reviews show the best-performing combination: Hybrid Lexicon with Naïve Bayes, reaching 70% accuracy.","| Al Qalam: Jurnal Ilmiah Keagamaan dan Kemasyarakatan\u003Cbr>[https://jurnal.stiq-amuntai.ac.id/index.php/al-qalam](https://jurnal.stiq-amuntai.ac.id/index.php/al-qalam)\u003Cbr>[P-ISSN: 1907-4174](P-ISSN: 1907-4174); E-ISSN: 2621-0681\u003Cbr>DOI : 10.35931/aq.v17i3.2131 |  |\n| --- | --- |\n\nPRODUCT OVERVIEW SENTIMENT ANALYSIS USING LEXICON HYBRIDBASED APPROACH AND MACHINE LEARNING  \nDaniel Kumala  \nComputer Science Department, BINUS Graduate Program, Master of Computer Science, Bina Nusantara University, Jakarta, Indonesia  \n[daniel.kumala@binus.ac.id](daniel.kumala@binus.ac.id)  \nAntoni Wibowo  \nComputer Science Department, BINUS Graduate Program, Master of Computer Science, Bina Nusantara University, Jakarta, Indonesia  \n[anwibowo@binus.edu](anwibowo@binus.edu)  \nAbstract  \nVarious sentiment analysis methods have been proposed to obtain reviewing opinions from machine learning and vocabulary-based sentiment. In previous research using only machine learning methods, I got an unsatisfactory accuracy score because a lexical / lexicon hybrid method was used in this study. Machine learning is proposed that can improve the performance of existing sentiment analysis. With this proposal the researcher was able to obtain experimental results that showed that the classifiers that produced the best results for the game review were Hybrid Lexicon and Nave Bayes with an accuracy of 70%.  \nKeywords : Sentiment Analysis, Naïve Bayes, Support Vector Machine, Lexicon Based Sentiment  \nAbstrak  \nBerbagai metode analisis sentimen telah diusulkan untuk mendapatkan opini ulasan dari pembelajaranmesin dan sentimen berbasis kosa kata. Pada penelitian sebelumnya yang hanya menggunakan metode machine learning, saya mendapatkan nilai akurasi yang kurang memuaskan karena pada penelitian ini digunakan metode hybrid leksikal/leksikon. Pembelajaran mesin diusulkan yang dapat meningkatkan kinerja analisis sentimen yang ada. Dengan proposal tersebut peneliti dapat memperoleh hasil eksperimen yang menunjukkan bahwa pengklasifikasi yang menghasilkan hasil terbaik untuk game review adalah Hybrid Lexicon dan Nave Bayes dengan akurasi sebesar 70%.  \nKata Kunci : Analisis Sentimen, Naïve Bayes, Support Vector Machine, Sentiment Based Lexicon  \nINTRODUCTION  \nA review is a rating of a publication, service, or company, such as a movie (movie review), video game (video game review), musical composition (musical review of a composition or recording), books (review of a book), shows and others. In this modern era, reviews are used as a tool to determine a selling point. Reviews are usually done by a user, but there are several websites that provide reviews, such as Rotten Tomatoes (Movie Reviews), IMDB (Internet Movie Database), Metacritics (Game Reviews), IGN (Game Reviews) . of games) and others. The purpose of a review is to criticize something that will be useful and beneficial to the community and users in general. The ratings or reviews that can be made are not arbitrary, because in the future they will have a significant impact on the audience's response to a  \nAl Qalam: Jurnal Ilmiah Keagamaan dan Kemasyarakatan Vol. 17, No. 3  \nMei-Juni 2023  \nproduct or article under study. The text of the review plays a very important role or has a big impact on the reader's knowledge. With the growing amount of information available on the internet and the substantial increase in the number of internet users, it has become important forecommerce sites to use a referral system to keep their customers informed about the products they are most likely to purchase. In the context of information filtering, the Recommendation System must be able to provide accurate recommendations to users by extracting valuable facts from the vast amount of information created on the Internet every day. 1 Nonetheless, it is difficult to analyze because each review consists of unstructured text of low descriptive quality and only a third of it is truly informative.2,3 And popular applications can receive up","cbCaieQzyED41AHF","https://ap.wps.com/l/cbCaieQzyED41AHF","pdf",497951,1,12,"English","en",105,"# Introduction\n## Review systems and opinion mining\n## Challenges of unstructured review text\n## Proposed hybrid lexicon and machine learning approach","[{\"question\":\"What is the main goal of this sentiment analysis study?\",\"answer\":\"To build a system that identifies reviewers’ opinions (opinion mining) for a product or service using a hybrid sentiment approach based on learning and vocabulary.\"},{\"question\":\"Why do prior machine-learning-only methods get unsatisfactory accuracy?\",\"answer\":\"Because review text is unstructured and often of low descriptive quality, with only a portion being truly informative, making sentiment inference more difficult.\"},{\"question\":\"Which classifier combination produced the best results and what accuracy was achieved?\",\"answer\":\"Hybrid Lexicon combined with Naïve Bayes produced the best results for game reviews with an accuracy of 70%.\"}]","Product Overview Sentiment Analysis Using Lexicon Hybrid-Based Approach and Machine Learning - Sentiment Analysis for Game Reviews | PDF",1785679986,30,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"product-overview-sentiment-analysis-using-lexicon-hybrid-based-approach-and-machine-learning-sentiment-analysis-for-game-reviews","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/product-overview-sentiment-analysis-using-lexicon-hybrid-based-approach-and-machine-learning-sentiment-analysis-for-game-reviews/117848/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05","2026-08-02",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What is the main goal of this sentiment analysis study?","Question",{"text":76,"@type":77},"To build a system that identifies reviewers’ opinions (opinion mining) for a product or service using a hybrid sentiment approach based on learning and vocabulary.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Why do prior machine-learning-only methods get unsatisfactory accuracy?",{"text":81,"@type":77},"Because review text is unstructured and often of low descriptive quality, with only a portion being truly informative, making sentiment inference more difficult.",{"name":83,"@type":74,"acceptedAnswer":84},"Which classifier combination produced the best results and what accuracy was achieved?",{"text":85,"@type":77},"Hybrid Lexicon combined with Naïve Bayes produced the best results for game reviews with an accuracy of 70%.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":29,"slug":122},"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":107,"slug":138},19,"General","general"]