[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119504-en":3,"doc-seo-119504-105":30,"detail-sidebar-cat-0-en-105":95},{"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":4,"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},119504,962075114101,"Seraphina","https://ap-avatar.wpscdn.com/avatar/e000253a75eb197efd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780044092746381165",8,"Research & Report","Exploring the Role of Machine Learning and Big Data Analytics in Enhancing Decision-Making Processes - A Systematic Literature Review","A systematic literature review examines how machine learning (ML) and big data analytics (BDA) influence decision-making processes across multiple industries. The study evaluates potential benefits, the tools and platforms used, and the deployment challenges reported in prior work. Using PRISMA with Scopus as the principal database, 31 publications from 2019–2024 are selected. Results show improvements in predictive accuracy, operational efficiency, data privacy measures, and integration with existing systems, with growing suitability for SMEs, while highlighting the need for more cost-effective solutions and opportunities for further research in less studied domains like logistics and manufacturing.","INTERNATIONAL JOURNAL ON INFORMATICS VISUALIZATION  \n[journal homepage : www.joiv.org/index.php/joiv](journal homepage : www.joiv.org/index.php/joiv)  \nExploring the Role of Machine Learning and Big Data Analyticsin Enhancing Decision-Making Processes:  \nA Systematic Literature Review  \nNicholas Prawira a, Wella a,*, Friska Natalia a  \na Information Systems Study Program, Universitas Multimedia Nusantara, Gading Serpong, Tangerang Selatan, Indonesia  \nCorresponding author:*[wella@umn.ac.id](wella@umn.ac.id)  \nAbstract—This Systematic Literature Review (SLR) analyzes the influence of Machine Learning (ML) and Big Data Analytics (BDA) on decision-making processes in several industries. The study aims to explore the potential of machine learning and big data analyticsin enhancing decision-making, examining the tools and platforms used, and identifying the challenges encountered during deployment. Employing the PRISMA technique, 31 publications published from 2019 to 2024 were meticulously selected through a stringent screening process, using Scopus asthe principal database. The results indicate that machine learning and big data analytics substantially enhance predictive accuracy, operational efficiency, and data privacy measures, while facilitating seamless integration with current systems. Furthermore, these technologies are becoming progressively accessible to Small and Medium Enterprises (SMEs). In the healthcare sector, machine learning models have exhibited a diagnosis accuracy of 99% in detecting breast cancer. Nonetheless, thereport underscores other research deficiencies, particularly the necessity for more cost-effective solutions designed for SMEs. These limitations signify opportunities for future study to investigate ML and BDA applications in underexamined areas, such as logistics and manufacturing. This research highlights the necessity of creating economical, scalable, and industry-specific machine learning and big data analytics solutions to address existing difficulties. This systematic literature review (SLR) seeks to elucidate the function of machine learning (ML) and big data analytics (BDA) in decision-making, thereby assisting researchers and practitioners in enhancing the utilization of these technologies across many industrial applications.  \nKeywords—Machine learning; big data analytics; decision-making; data privacy; PRISMA; SMEs.  \nManuscript received 16 Oct. 2024; revised 7 Jan. 2025; accepted 3 Feb. 2025. Date of publication 31 Jul. 2025.  \nInternational Journal on Informatics Visualization is licensed under a Creative Commons Attribution-Share Alike 4.0 International License.  \nI. INTRODUCTION  \nIn recent years, machine learning and big data analyticshave evolved into highly advanced tools for decision-making across numerous industrial sectors [1]. Machine learning and big data analytics are employed to handle extensive datasets, identify pertinent information, and facilitate strategic decision-making for organizations [2], [3] . As industries encounter rising worldwide demands and leverage advanced analytical tools, the integration of machine learning and big data analytics has emerged as a vital goal for attaining  \nmaximum performance and precise decision-making [4].  \nThe capabilities of machine learning and big data analytics are most apparent in data-intensive industries like retail, banking, and healthcare, where extensive databases are utilized to enhance results. Electronic health records are utilized to improve pediatric care and facilitate prompt  \nclinical decision support [5], [6]. In agriculture and transportation, predictive models have shown the ability of machine learning to enhance resource optimization and facilitate the advancement of infrastructure [7] .  \nNotwithstanding its potential, the implementation of machine learning and big data analytics presents considerable hurdles. This encompasses the amalgamation of new technologies with legacy systems, apprehensions regarding dat","cbCainRNAynEutUn","https://ap.wps.com/l/cbCainRNAynEutUn","pdf",3660273,1,9,"English","en",105,"# Introduction\n# Materials and Methods\n## Machine Learning and Big Data Analytics","[{\"question\":\"What is the main goal of this systematic literature review?\",\"answer\":\"To analyze how ML and BDA contribute to decision-making processes, including benefits, tools/platforms used, and deployment challenges across industries.\"},{\"question\":\"How were the publications selected for the review?\",\"answer\":\"The review applies the PRISMA technique and selects 31 publications from 2019 to 2024 using Scopus as the principal database.\"},{\"question\":\"What benefits of ML and BDA are reported in the findings?\",\"answer\":\"They substantially enhance predictive accuracy and operational efficiency, strengthen data privacy measures, and support integration with current systems.\"},{\"question\":\"What limitations and research gaps does the review identify?\",\"answer\":\"It notes a need for more cost-effective solutions for SMEs and suggests future research in underexamined areas such as logistics and manufacturing.\"}]","Exploring the Role of Machine Learning and Big Data Analytics in Enhancing Decision-Making Processes - A Systematic Literature Review | PDF",1785724686,23,{"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":90,"head_meta":92,"extra_data":94,"updated_unix":28},"exploring-the-role-of-machine-learning-and-big-data-analytics-in-enhancing-decision-making-processes-a-systematic-literature-review","",{"@graph":36,"@context":89},[37,54,68],{"@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/exploring-the-role-of-machine-learning-and-big-data-analytics-in-enhancing-decision-making-processes-a-systematic-literature-review/119504/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81,85],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main goal of this systematic literature review?","Question",{"text":75,"@type":76},"To analyze how ML and BDA contribute to decision-making processes, including benefits, tools/platforms used, and deployment challenges across industries.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How were the publications selected for the review?",{"text":80,"@type":76},"The review applies the PRISMA technique and selects 31 publications from 2019 to 2024 using Scopus as the principal database.",{"name":82,"@type":73,"acceptedAnswer":83},"What benefits of ML and BDA are reported in the findings?",{"text":84,"@type":76},"They substantially enhance predictive accuracy and operational efficiency, strengthen data privacy measures, and support integration with current systems.",{"name":86,"@type":73,"acceptedAnswer":87},"What limitations and research gaps does the review identify?",{"text":88,"@type":76},"It notes a need for more cost-effective solutions for SMEs and suggests future research in underexamined areas such as logistics and manufacturing.","https://schema.org",{"og:url":52,"og:type":91,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":93,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":96},[97,101,105,109,114,119,124,127,131,134,138],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},"Exam",70,"exam",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},5,"Comic",60,"comic",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},6,"Technology",50,"technology",{"id":120,"doc_module":4,"doc_module_name":46,"category_name":121,"show_sort_weight":122,"slug":123},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":125,"slug":126},30,"research-report",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":129,"slug":130},"Religion & Spirituality",20,"religion-spirituality",{"id":129,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":129,"slug":133},"World Cup","world-cup",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":135,"slug":137},10,"Lifestyle","lifestyle",{"id":139,"doc_module":4,"doc_module_name":46,"category_name":140,"show_sort_weight":110,"slug":141},19,"General","general"]