[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-186218-en":3,"doc-seo-186218-105":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},186218,962085570644,"Melati","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","Research Mathematics","This document presents research in mathematics, focusing on the structure of ANFIS (Adaptive Neuro-Fuzzy Inference System) models. It includes tables detailing parameter settings for directional input and output, as well as performance metrics for different language subjects (Bahasa Indonesia, English, Mathematics) using various fuzzy logic membership functions such as Trimf, Gbellmf, and Gaussmf. These metrics are expressed as percentages and likely represent the accuracy or effectiveness of the fuzzy models in processing linguistic data. The ANFIS model structure is visually depicted, illustrating input layers, fuzzy rule layers, and output layers, highlighting the complex interconnections within the system. The document also contains a journal logo with the text \"FACTOR M - Focus on Areas of Research Mathematics,\" suggesting it is part of a publication dedicated to advancing mathematical research and applying fuzzy logic and neural network principles to data analysis and modeling.","| Parameter | Arah Maju | Arah\u003Cbr>Mundur |\n| --- | --- | --- |\n| Parameter Premis | Tetap | Gradient\u003Cbr>Distance |\n| Parameter\u003Cbr>Konsekuen | RLSE | Tetap |\n\n| Mata\u003Cbr>Pelajaran | Trimf\u003Cbr>(%) | Gbellmf\u003Cbr>(%) | Gaussmf\u003Cbr>(%) |\n| --- | --- | --- | --- |\n| Bahasa Indonesia | 27,24 | 30.60 | 29.16 |\n| Bahasa\u003Cbr>Inggris | 38,74 | 35,91 | 33,98 |\n| Matematika | 26,90 | 32,16 | 32.56 |","cbCaisgeIulD2ScP","https://ap.wps.com/l/cbCaisgeIulD2ScP","pdf",400924,1,9,"English","en",105,"# ANFIS Model Structure\n## Parameter Settings\n## Performance Metrics","[{\"question\":\"What is the main topic of research presented in this document?\",\"answer\":\"The main topic of research presented is the application of ANFIS (Adaptive Neuro-Fuzzy Inference System) models in mathematics, specifically detailing the model structure and performance metrics.\"},{\"question\":\"What are the performance metrics presented for different subjects?\",\"answer\":\"The document presents performance metrics for Bahasa Indonesia, English, and Mathematics, indicating percentages achieved using Trimf, Gbellmf, and Gaussmf membership functions.\"},{\"question\":\"What does the ANFIS model structure illustrate?\",\"answer\":\"The ANFIS model structure visually depicts the input, fuzzy rule, and output layers of the system, showing the complex interconnections essential for its operation.\"}]","Research Mathematics | 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