Implementasi Chatbot Untuk Rekomendasi Tema Tugas Akhir Program Studi Informatika Menggunakan Metode Simple Additive Weight

S. Aryanto, Anton Setiawan Honggowibowo, Jabbar Akhmad
{"title":"Implementasi Chatbot Untuk Rekomendasi Tema Tugas Akhir Program Studi Informatika Menggunakan Metode Simple Additive Weight","authors":"S. Aryanto, Anton Setiawan Honggowibowo, Jabbar Akhmad","doi":"10.22441/format.2022.v11.i2.003","DOIUrl":null,"url":null,"abstract":"Many of courses that have been taken makes it difficult for students to determine one area to focus on in determining the theme of the final project. The case study of this research is the Informatics Study Program at the Adisutjipto Aerospace Technology Institute, Yogyakarta. For this reason, a chatbot with a decision support system was made using the simple additive weighting (SAW) method which adds up the weights of the performance of each object that is different and has the same opportunity on all the criteria it has. This method requires the process of normalizing the decision matrix (X) to a scale that can be compared with all existing alternative ratings. The number of observation scores is the sum of the scores of each observation statement multiplied by the weight of the score according to the Likert scale. The maximum score is the maximum score on the Likert scale multiplied by the number of questions, so 5 x 9 = 45. The expected score is the maximum score multiplied by the number of respondents, so 45 x 30 = 1,200. Based on the feasibility test of the chatbot system for the final project recommendation using this method, it succeeded in calculating the feasibility of an application of 1074 (89.5%) with the formula for calculating the percentage of eligibility which was tested by 30 students of the 2017 class of Informatic Study Program, Adisutjipto Aerospace Technology Institute.","PeriodicalId":381291,"journal":{"name":"Format : Jurnal Ilmiah Teknik Informatika","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Format : Jurnal Ilmiah Teknik Informatika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22441/format.2022.v11.i2.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Many of courses that have been taken makes it difficult for students to determine one area to focus on in determining the theme of the final project. The case study of this research is the Informatics Study Program at the Adisutjipto Aerospace Technology Institute, Yogyakarta. For this reason, a chatbot with a decision support system was made using the simple additive weighting (SAW) method which adds up the weights of the performance of each object that is different and has the same opportunity on all the criteria it has. This method requires the process of normalizing the decision matrix (X) to a scale that can be compared with all existing alternative ratings. The number of observation scores is the sum of the scores of each observation statement multiplied by the weight of the score according to the Likert scale. The maximum score is the maximum score on the Likert scale multiplied by the number of questions, so 5 x 9 = 45. The expected score is the maximum score multiplied by the number of respondents, so 45 x 30 = 1,200. Based on the feasibility test of the chatbot system for the final project recommendation using this method, it succeeded in calculating the feasibility of an application of 1074 (89.5%) with the formula for calculating the percentage of eligibility which was tested by 30 students of the 2017 class of Informatic Study Program, Adisutjipto Aerospace Technology Institute.
Chatbot的执行是使用简单的adad标量方法推荐信息课程的最终主题
许多已经修过的课程使得学生在确定期末项目的主题时很难确定一个要关注的领域。本研究的案例研究是日惹adisutjito航空航天技术研究所的信息学研究计划。为此,使用简单加性加权(SAW)方法制作具有决策支持系统的聊天机器人,该方法将每个对象的性能权重相加,这些对象在所有标准上都是不同的,并且具有相同的机会。这种方法需要将决策矩阵(X)归一化到可以与所有现有替代评级进行比较的尺度。观察得分数是每个观察语句的得分之和乘以根据李克特量表得分的权重。最高分数是李克特量表上的最高分数乘以问题数,所以5 x 9 = 45。期望分数是最高分数乘以应答者的数量,因此45 × 30 = 1200。在利用该方法对聊天机器人系统进行最终项目推荐可行性测试的基础上,利用合格百分比计算公式,成功计算出1074个(89.5%)申请的可行性,该公式由30名航天航空技术学院2017级信息学专业的学生进行测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信