[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3679":3,"related-3679":58},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"primary_topic":9,"secondary_topics":21,"classification":22,"search_phrases":37,"slug":38,"view_count":39,"doi":40,"paper":41,"created_at":57},3679,"Development of a Decision Support System for Selecting College Majors Based on an Expert System Using the Forward Chaining Method","https:\u002F\u002Fdoi.org\u002F10.37251\u002Fsynapsi.v1i2.3842","Purpose of the study: This study aims to develop a decision support system for selecting higher education majors based on users' personality characteristics using the RIASEC theory. The study also aims to analyze the software quality in terms of correctness, functionality, usability, and maintainability and to examine the suitability of system recommendations with users' preferred majors. Methodology: This study employed a Research and Development (R&D) approach with the Waterfall software development model. The system was developed using Visual Basic 6.0 and MySQL. RIASEC theory was used as the knowledge base, while decision tree representation and forward chaining were applied for the inference process. Software quality was evaluated through correctness, functionality, usability, and maintainability testing, involving 60 respondents and the Computer System Usability Questionnaire (CSUQ). Main Findings: The developed system achieved an error\u002FKLOC value of 0 and passed all 34 functionality tests with a 100% success rate. Usability obtained an average score of 72 and was categorized as feasible. All three maintainability aspects instrumentation, consistency, and simplicity meet the criteria. Furthermore, 46 of 60 respondents showed at least one preference matching the system recommendation, resulting in a feasibility rate of 76.67%. Novelty\u002FOriginality of this study: The novelty of this study lies in integrating RIASEC personality theory, decision tree knowledge representation, and forward chaining inference into a decision support system for higher education major selection. The study also combines recommendation development with comprehensive software quality evaluation, providing an integrated approach for educational decision support based on personality characteristics.","研究目的：本研究旨在开发一个基于RIASEC理论的决策支持系统，用于根据用户的人格特征选择高等教育专业。本研究还旨在从正确性、功能性、可用性和可维护性方面分析软件质量，并考察系统推荐结果与用户偏好专业之间的适配性。方法：本研究采用研究与开发（R&D）方法，并结合瀑布式软件开发模型。系统使用Visual Basic 6.0和MySQL开发。RIASEC理论被用作知识库，同时采用决策树表示和前向链推理进行推理过程。软件质量通过正确性、功能性、可用性和可维护性测试进行评估，涉及60名受访者，并使用计算机系统可用性问卷（CSUQ）。主要发现：所开发的系统实现了每千行代码0个错误（error\u002FKLOC）的值，并通过了全部34项功能测试，成功率为100%。可用性获得平均分72分，被归类为可行。可维护性的三个方面——可测性、一致性和简单性——均符合标准。此外，60名受访者中有46人至少有一项偏好与系统推荐相匹配，可行性率为76.67%。本研究的创新性\u002F原创性：本研究的创新之处在于将RIASEC人格理论、决策树知识表示和前向链推理整合到一个高等教育专业选择决策支持系统中。本研究还将推荐系统开发与全面的软件质量评估相结合，为基于人格特征的教育决策支持提供了一种集成方法。",null,"SYNAPSI Journal of Information Systems and Informatics Education","2026-09-26T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"该论文研究高校专业选择决策支持系统，与三农、农业信息化、智慧农业等主题无关，不予入选。",[19],{"name":10,"url":6},[12],[],{"status":23,"locked":14,"version":24,"method":25,"evidence":26},"needs_review","2026-10-22.2","rules",{"candidates":27,"agricultural_evidence":14,"reason":36},[28],{"code":29,"score":30,"supported":31,"title":32,"abstract":34,"tags":35},"I2",11,true,[33],"decision support",[33],[],"农业相关性需要复核",[],"DevelopmentofaDecisionSupportSystemforSe-3679",1,"10.37251\u002Fsynapsi.v1i2.3842",{"doi":40,"openalex_id":42,"authors":43,"venue":10,"cited_by_count":15,"oa_url":48,"card":49,"direction":55,"ingested_from":56},"W7214436605",[44,46],{"name":45,"orcid":9},"Cahyana",{"name":47,"orcid":9},"Nahrun Hartono","https:\u002F\u002Fcahaya-ic.com\u002Findex.php\u002FSYNAPSI\u002Farticle\u002Fdownload\u002F3842\u002F2220",{"tldr":50,"method":51,"finding":52,"direction":53,"opportunity":54},"开发基于RIASEC性格与正向推理的专家系统，为高校专业选择提供决策支持。","R&D与瀑布模型，Visual Basic 6.0和MySQL，决策树与正向推理","系统功能测试全通过，可用性可行，76.67%用户偏好与推荐匹配。","其他","可将性格-专业匹配框架迁移至农业信息化人才培养或农户技术采纳决策支持。","农业人工智能与决策模型","openalex","2026-09-28T23:30:48.352932Z",{"total":15,"page":39,"page_size":39,"items":59},[]]