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Implementasi Penggunaan Algoritma Weighted Product untuk Sistem Pendukung Keputusan Bantuan Lansia 为老年人援助决策支持系统实施加权乘积算法
Pub Date : 2023-12-08 DOI: 10.30989/teknomatika.v16i2.1249
Ferlinda Yuyung Kusumaningrum, Andika Bayu Saputra, A. Priyanto, Nurul Fatimah
Lansia merupakan suatu siklus hidup yang pasti dialami oleh manusia dan hampir setiap orang. Terdapat permasalahan yang dihadapi oleh lansia dari menurunnya kondisi fisik sampai tidak dapat bekerja, Pemerintah mengeluarkan program untuk mendukung lansia. Bantuan lansia yang dapat diterima setiap tiga bulan atau sesuai informasi dari pemerintah. Namun saat ini program yang ada masih belum efektif karena terdapat kendala seperti belum ada sebuah sistem yang dapat menginputkan data, sehingga pendataan bantuan lansia masih secara manual menggunakan pencatatan di buku yang dapat menghambat waktu pendataan dan perhitungan data. Penelitian ini bertujuan untuk membangun sebuah sistem pendukung keputusan dalam menentukan penerima bantuan lansia guna membantu dalam proses pengambilan keputusan. Algoritma weighted product yang merupakan suatu algoritma yang sering digunakan untuk menganalisa sebuah keputusan. Hasil penelitian ini berupa sebuah Implementasi Penggunaan Algoritma Weighted Product untuk Sistem Pendukung Keputusan Penerima Bantuan Lansia. Sistem diharapkan membantu dalam menentukan keputusan dari barbagai pilihan yang mempertimbangkan beberapa macam kriteria dan dapat diterapkan untuk membantu menyelesaikan permasalahan mengidentifikasi penerima bantuan lansia secara cepat, tepat dan efektif.
老年人是人类和几乎每个人都必须经历的生命周期。老年人面临着从身体状况下降到无法工作等各种问题,因此,政府出台了一项支持老年人的计划。每三个月或根据政府提供的信息可以领取一次老年人援助金。然而,目前现有的计划仍未取得成效,因为存在一些障碍,例如没有可以输入数据的系统,因此老年人援助的数据收集仍需使用书本上的笔记进行手工操作,这可能会妨碍数据收集和数据计算时间。本研究旨在建立一个决策支持系统,用于确定长者援助对象,以协助决策过程。加权乘积算法是一种常用于分析决策的算法。本研究的成果是 "在老年人援助对象决策支持系统中使用加权乘积算法的实施"。预计该系统将有助于从考虑多种标准的各种选择中做出决定,并可用于帮助快速、准确和有效地解决确定老年人援助对象的问题。
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引用次数: 0
Analisis Kerentanan Menggunakan Vulnerability Assessment pada Situs Web Perguruan Tinggi 利用漏洞评估对高校网站进行漏洞分析
Pub Date : 2023-12-08 DOI: 10.30989/teknomatika.v16i2.1248
Danang Prihanto, Adkhan Sholeh, Chanief Budi Setiawan, M. Abu, Amar Al Badawi
Abstrak - Di Indonesia, terdapat beberapa fenomena yang menunjukkan rendahnya tingkat keamanan digital. Pada tahun 2021, terdapat 5.940 kasus web defacement dari beberapa sektor yang menjadi sasaran. Salah satunya dari sektor akademik, yaitu perguruan tinggi dengan total 2.217 kasus, menjadikannya sektor dengan kasus terbanyak. Oleh karena itu, peneliti melakukan pemindaian pada ketiga website FTTI. Penelitian dilakukan dengan tujuan dapat menganalisis dan mengetahui tingkat keamanan serta bentuk-bentuk kerentanan pada website FTTI di Universitas Jenderal Achmad Yani Yogyakarta, yaitu ftti.unjaya.ac.id, elearning.ftti.unjaya.ac.id, dan app.ftti.unjaya.ac.id. Dengan hasil yang diperoleh dari analisis, peneliti harus melaporkan kepada Kepala Pusat Sistem Informasi (PUSI) FTTI. Menggunakan metode vulnerability assessment dengan beberapa alat seperti Nmap, Nessus, dan WPScan. Pada metode ini terdapat beberapa tahapan, seperti persiapan (instalasi alat dan pengumpulan data yang diperlukan), mengidentifikasi kerentanan, dan analisis. Hasil penelitian ini menunjukkan bahwa dari ketiga website, terdapat berbagai tingkat kerentanan seperti Critcal, High, Medium, Low, dan Info. Pada website ftti.unjaya.ac.id yang menggunakan WordPress, tidak terdapat kerentanan yang parah setelah dilakukan pemindaian menggunakan ketiga alat yang digunakan. Sementara itu, pada elearning.ftti.unjaya.ac.id dan app.ftti.unjaya.ac.id, menunjukkan hasil penilaian VPR Top Threats bahwa keduanya berada pada tingkat Medium. Pada ketiga website yang telah dipindai, ditemukan bahwa ftti.unjaya.ac.id adalah website dengan tingkat kerentanan paling aman. Menurut hasil pemindaian, website elearning.ftti.unjaya.ac.id maupun app.ftti.unjaya.ac.id memiliki beberapa kerentanan dengan tingkat risiko High bahkan Critical.
摘要--在印度尼西亚,有几种现象表明数字安全水平较低。2021 年,多个目标部门共发生了 5940 起网络污损案件。其中,学术界(即大学)共发生 2,217 起案件,是发生案件最多的部门。因此,研究人员对 FTTI 的三个网站进行了扫描。研究的目的是分析和确定日惹仁德拉阿奇玛德亚尼大学 FTTI 网站(即 ftti.unjaya.ac.id、elearning.ftti.unjaya.ac.id 和 app.ftti.unjaya.ac.id)的安全级别和漏洞形式。研究人员必须向 FTTI 信息系统中心(PUSI)主任报告分析结果。使用 Nmap、Nessus 和 WPScan 等工具进行漏洞评估。这种方法分为几个阶段,如准备(安装工具和收集必要数据)、识别漏洞和分析。研究结果表明,三个网站存在不同程度的漏洞,如 Critcal、High、Medium、Low 和 Info。在使用 WordPress 的 ftti.unjaya.ac.id 网站上,使用三种工具扫描后没有发现严重漏洞。同时,对 elearning.ftti.unjaya.ac.id 和 app.ftti.unjaya.ac.id 的 VPR 顶级威胁评估结果显示,这两个网站都处于中等级别。在扫描的三个网站中,发现 ftti.unjaya.ac.id 是安全漏洞级别最高的网站。扫描结果显示,elearning.ftti.unjaya.ac.id和app.ftti.unjaya.ac.id网站存在多个漏洞,风险等级为 "高 "甚至 "严重"。
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引用次数: 0
Analisis Tingkat Security Awareness-Personal Threat Terhadap Ancaman Phishing Dengan Metode Technology Threat Avoidance Theory (TTAT) 技术威胁规避理论(TTAT)与网络钓鱼的安全意识--个人威胁分析
Pub Date : 2023-12-08 DOI: 10.30989/teknomatika.v16i2.1250
Indah Daila Sari, Dedy Hariyadi, R. Sahtyawan, Netania Indi Kusumaningtyas
Phishing is a sort of cybercrime that involves obtaining sensitive information through the use of email, SMS, or compromised websites. The effects of phishing are caused by factors in the Technology Threat Avoidance Theory. The single best way to stop phishing attacks is to increase awareness of the risk of them happening among users or end users (human firewall). To determine the next steps in raising user knowledge, it is necessary to measure cybersecurity awareness, particularly against phishing assaults. Identify a few significant cybersecurity awareness of FTTI University of Jenderal Achmad Yani students in Yogyakarta. The investigation in this case included a phishing test and also employed online observation using observers who were asked questions based on the Technology Threat Avoidance Theory (TTAT). Using the MANOVA analysis method, factors influencing cybersecurity awareness analysis is conducted. Based on the analysis and testing of phishing tests as well as online questionnaires from the sample population, it shows that the sample is at a poor level of awareness. While the analysis of cybersecurity influence factors using the MANOVA analysis method shows that the results of the sig.> 0.05 value so that h0 is rejected. Based on the results of the study, it was concluded that FTTI students were still vulnerable to phishing attacks. Factor analysis using the MANOVA method shows that the dependent factor affects the level of cybersecurity awareness of the respondents but there is no significant difference between the dependent factors.
网络钓鱼是一种网络犯罪,涉及通过使用电子邮件、短信或受损网站获取敏感信息。网络钓鱼的影响是由技术威胁规避理论中的因素造成的。阻止网络钓鱼攻击的唯一最佳方法就是提高用户或最终用户对发生网络钓鱼攻击风险的认识(人类防火墙)。为确定提高用户知识的下一步措施,有必要衡量网络安全意识,尤其是针对网络钓鱼攻击的意识。确定日惹 Jenderal Achmad Yani FTTI 大学学生的几个重要网络安全意识。本案例的调查包括网络钓鱼测试,还采用了在线观察法,观察者根据技术威胁规避理论(TTAT)提出问题。利用 MANOVA 分析方法,对影响网络安全意识的因素进行了分析。根据对网络钓鱼测试以及样本人群在线问卷的分析和检测,结果显示样本人群的网络安全意识水平较低。而利用 MANOVA 分析方法对网络安全影响因素进行分析,结果显示 sig.>0.05 值,因此拒绝 h0。根据研究结果,可以得出结论:快三学院学生仍然容易受到网络钓鱼攻击。利用 MANOVA 方法进行的因子分析显示,因果因子会影响受访者的网络安全意识水平,但因果因子之间没有显著差异。
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引用次数: 0
Desain User Interface Dan User Experience Prototype Mobile Learning Menggunakan Metode Design Thinking Metode Design Thinking 设计用户界面和用户体验原型 移动学习设计思维模式设计思维模式
Pub Date : 2023-12-08 DOI: 10.30989/teknomatika.v16i2.1254
Muhamad Arabi Rizki Angkotasan, A. Murdiyanto, A. Himawan, Fajar Syahruddin
Abstract - Do Up uses the website as online learning. users complain about the accessibility of the website with some minimal features and an unattractive UI when accessed via a smartphone will make the UX limited and will limit user interaction in using Do Up. Designing UI and UX prototypes of mobile learning at startup Do Up, using the design thinking method to solve problems and find the right solution according to the user's wishes. The author applies design thinking in this research. The author makes an illustration in the form of a Do Up mobile learning UI design that is in accordance with user needs and provides the design to Do Up stakeholders. In SEQ there are 4 scales given by users, namely 4.5, 6 and 7 scale. Most users give a 7 scale on the UI/UX design of the Do Up mobile learning prototype. On SUS which shows that the final score is 87 It means that the prototype has been well received by the users. The author has applied design thinking which consists of empathize, define, ideate, prototype and test stages in this study.
摘要--Do Up 使用网站作为在线学习平台。用户抱怨网站的可访问性差,功能少,通过智能手机访问时用户界面不美观,这将使用户体验受到限制,并限制用户在使用 Do Up 时的互动。在初创公司 Do Up 设计移动学习的用户界面和用户体验原型,使用设计思维方法解决问题,并根据用户的意愿找到正确的解决方案。作者在本研究中应用了设计思维。作者以图解的形式,设计了符合用户需求的Do Up移动学习用户界面,并将设计方案提供给Do Up的利益相关者。在 SEQ 中,用户给出了 4 个等级,即 4.5、6 和 7 级。大多数用户对 Do Up 移动学习原型的 UI/UX 设计给出了 7 分。在 SUS 中,最终得分是 87 分。作者在本研究中运用了设计思维,包括移情、定义、构思、原型和测试等阶段。
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引用次数: 0
CParts Platform Analisis Harga Komponen Komputer pada Marketplace CParts Marketplace 计算机组件价格分析平台
Pub Date : 2023-12-08 DOI: 10.30989/teknomatika.v16i2.1251
Anas Sufi, Hasan Manahingati, Puji Winar Cahyo, Kartika Kusumaningtyas, Alfun Roehatul Jannah
Amidst the fluctuations in computercomponent prices brought about by the Covid-19pandemic, a comprehensive analysis platform hasbeen developed to address this challenge. Thisinnovative platform harnesses historical datasourced from prominent e-commerce platforms suchas Shopee, Blibli, and Tokopedia, presenting userswith insightful average price graphs categorized bycomponent series and types. The researchmethodology adopted follows a prototype approach,encompassing meticulous phases ranging fromneeds analysis, application design, prototyping,testing, evaluation, prototype refinement, through toimplementation and ongoing maintenance. Thesuccessful implementation of this system, powered bythe Python programming language, features robustfunctionalities including product search anddynamic graphical representations derived fromhistorical data. The data retrieval process, utilizingthe Scraping method, occurs at regular intervals ona weekly basis. Upon meticulous analysis ofhistorical data spanning from January to July 2022,a noteworthy trend emerged, highlighting thatShopee and Tokopedia consistently offer computercomponents at relatively more affordable pricescompared to Blibli. The conclusive findings of thisresearch underscore the platform's efficacy inproviding an essential tool for users navigating thecomplex landscape of computer component pricedynamics, particularly in the unprecedented contextof the ongoing pandemic. This platform not onlyfacilitates monitoring but also empowers users withvaluable insights crucial for informed purchasingdecisions based on stable and budget-friendly pricingstructures.
在 "Covid-19 "大流行带来的计算机组件价格波动中,一个综合分析平台应运而生。这一创新平台利用了从 Shopee、Blibli 和 Tokopedia 等著名电子商务平台获取的历史数据,为用户提供了按组件系列和类型分类的具有洞察力的平均价格图表。所采用的研究方法遵循原型方法,包括从需求分析、应用设计、原型开发、测试、评估、原型完善到实施和持续维护的各个细致阶段。该系统由 Python 编程语言驱动,具有强大的功能,包括产品搜索和源自历史数据的动态图形表示。数据检索过程采用 Scraping 方法,每周定期进行。在对 2022 年 1 月至 7 月的历史数据进行细致分析后,发现了一个值得注意的趋势,即与 Blibli 相比,Shopee 和 Tokopedia 始终以相对更实惠的价格提供计算机组件。这项研究的结论强调了该平台的功效,它为用户提供了一个重要工具,帮助他们驾驭复杂的计算机组件价格动态,尤其是在前所未有的大流行病背景下。该平台不仅便于监控,而且还能为用户提供宝贵的见解,这些见解对于用户在稳定和预算友好的定价结构基础上做出明智的采购决策至关重要。
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引用次数: 0
Metode Hybrid Menggunakan Pendekatan Lexicon Based dan Naive Bayes Classifier Untuk Analisis Sentimen Terkait Jaminan Hari Tua 使用基于词典的方法和 Naive Bayes 分类器的混合方法进行老年安全相关情感分析
Pub Date : 2023-12-08 DOI: 10.30989/teknomatika.v16i2.1247
Rizky Fauzi Akbar, Muhammad Habibi, Puji Winar Cahyo, Nafisa Alfi Sa'diya
Badan Penyelenggara Jaminan Sosial (BPJS) Ketenagakerjaan adalah badan aturan publik yang dibuat melalui Undang-Undang No 24 Tahun 2011 Tentang Badan Penyelenggaran Jaminan Sosial menggunakan tujuan untuk mewujudkan terselenggaranya pemberian jaminan terpenuhinya kebutuhan dasar yang layak bagi setiap peserta atau anggota keluarganya. Dalam pelaksanaannya terdapat informasi yang tersebar khususnya pada tweet di Twitter mengenai keputusan Kementrian Kesehatan yaitu mengenai Jaminan Hari Tua (JHT) yang hanya bisa dicairkan/diambil setelah peserta (BPJS) Ketenagakerjaan menginjak usia 56 tahun, menyebabkan adanya pro dan kontra yang ada dikalangan masyarakat. Berdasarkan tweet-tweet pada Twitter yang belum dianalisis maka perlu di analisis secara mendalam untuk mendapatkan informasi yang sesuai berdasarkan opini netizen. Berdasarkan hasil penelitian ini diperoleh nilai akurasi data testing sebesar 92% untuk metode Lexicon Based dan 95% untuk data testing pada metode Naïve Bayes Classifier lalu untuk data training Naïve Bayes Classifier mendapatkan akurasi 82%.  Penelitian ini mendapatkan kesimpulan bahwa jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan mendapat sentimen negatif dari netizen yang banyak membahas mengenai penolakan peraturan baru dimana jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan, hanya bisa dicairkan atau diambil ketika peserta BPJS Ketenagakerjaan menginjak usia 56 tahun.
社会保障组织机构(BPJS)就业部是根据 2011 年关于社会保障组织机构的第 24 号法律成立的一个公共监管机构,其目的是实现为满足每个参保人或其家庭成员的基本需求提供保障。在实施过程中,有一些信息传播开来,尤其是推特上关于卫生部决定的推文,即关于老年保障(JHT)的决定,只有在参保人(BPJS)就业年龄达到 56 岁后才能提取/领取,这在公众中引起了利弊的争论。基于推特上尚未分析的推文,有必要进行深入分析,以获得基于网民意见的适当信息。根据本研究的结果,基于词典的方法测试数据的准确率值为 92%,奈伊夫贝叶斯分类器方法测试数据的准确率值为 95%,然后对奈伊夫贝叶斯分类器训练数据的准确率值为 82%。 本研究得出的结论是,网民对就业养老保障(JHT)的负面情绪,即就业养老保障(JHT)只能在就业参保人年满 56 岁时才能发放或领取的新规定,进行了大量的讨论。
{"title":"Metode Hybrid Menggunakan Pendekatan Lexicon Based dan Naive Bayes Classifier Untuk Analisis Sentimen Terkait Jaminan Hari Tua","authors":"Rizky Fauzi Akbar, Muhammad Habibi, Puji Winar Cahyo, Nafisa Alfi Sa'diya","doi":"10.30989/teknomatika.v16i2.1247","DOIUrl":"https://doi.org/10.30989/teknomatika.v16i2.1247","url":null,"abstract":"Badan Penyelenggara Jaminan Sosial (BPJS) Ketenagakerjaan adalah badan aturan publik yang dibuat melalui Undang-Undang No 24 Tahun 2011 Tentang Badan Penyelenggaran Jaminan Sosial menggunakan tujuan untuk mewujudkan terselenggaranya pemberian jaminan terpenuhinya kebutuhan dasar yang layak bagi setiap peserta atau anggota keluarganya. Dalam pelaksanaannya terdapat informasi yang tersebar khususnya pada tweet di Twitter mengenai keputusan Kementrian Kesehatan yaitu mengenai Jaminan Hari Tua (JHT) yang hanya bisa dicairkan/diambil setelah peserta (BPJS) Ketenagakerjaan menginjak usia 56 tahun, menyebabkan adanya pro dan kontra yang ada dikalangan masyarakat. Berdasarkan tweet-tweet pada Twitter yang belum dianalisis maka perlu di analisis secara mendalam untuk mendapatkan informasi yang sesuai berdasarkan opini netizen. Berdasarkan hasil penelitian ini diperoleh nilai akurasi data testing sebesar 92% untuk metode Lexicon Based dan 95% untuk data testing pada metode Naïve Bayes Classifier lalu untuk data training Naïve Bayes Classifier mendapatkan akurasi 82%.  Penelitian ini mendapatkan kesimpulan bahwa jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan mendapat sentimen negatif dari netizen yang banyak membahas mengenai penolakan peraturan baru dimana jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan, hanya bisa dicairkan atau diambil ketika peserta BPJS Ketenagakerjaan menginjak usia 56 tahun.","PeriodicalId":508475,"journal":{"name":"Teknomatika: Jurnal Informatika dan Komputer","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139185381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PEMODELAN TOPIK TERKAIT BANJIR PADA TWITTER DENGAN MENGGUNAKAN LATENT DIRICHLET ALLOCATION 使用潜在德里赫利分配对 twitter 上的洪水相关主题进行建模
Pub Date : 2023-11-29 DOI: 10.30989/teknomatika.v16i1.1139
M. Irwansyah, Muhammad Habibi, Fajar Syahruddin
In this background discusses the topic of tweet about Flooding on Twitter using the keyword "Flood". Tweet data was taken from June 1, 2021 to June 2, 2021 with the number of tweet data obtained, which was 2000 tweets. The number of tweets related to flooding has not been analyzed so that the topics contained in it are not yet known. Research . Modeling topics related to floods in Indonesia on Twitter social media with the LDA method. Research. This study uses experimental methods with several variables to test hypotheses. Then the data is processed with stages, namely web data extraction, preprocessing, feature extraction, topic modeling using latent dirichlet allocation algorithms, visualization, and analysis. Research. The results of the topic coherence stage were carried out a search for the most optimal topic from the 20 topics that had been determined at the beginning. The results of topic coherence for 20 topics concluded that for topic 10 it has a total topic value of 0.41 and has an ideal topic modeling result and is in accordance with the provisions. Conclusion : Based on the results of the discussion of topic coherence, it can be concluded that the most ideal number of topics is topic 10 because it has the highest value compared to other topics. The advice here is to be able to display or get flood information in Indonesia in real time and accurately.
在本背景中,使用关键词 "洪水 "讨论了 Twitter 上有关洪水的推文主题。推文数据取自 2021 年 6 月 1 日至 2021 年 6 月 2 日,获得的推文数据数量为 2000 条。与洪水相关的推文数量尚未分析,因此其中包含的主题尚不得而知。研究 .利用 LDA 方法对 Twitter 社交媒体上与印度尼西亚洪灾相关的话题进行建模。研究。本研究采用实验方法,使用多个变量来检验假设。然后分阶段处理数据,即网络数据提取、预处理、特征提取、使用潜在德里克利特分配算法进行话题建模、可视化和分析。研究。主题一致性阶段的结果是从一开始确定的 20 个主题中寻找最优主题。20 个主题的主题一致性结果认为,主题 10 的总主题值为 0.41,具有理想的主题建模结果,符合规定。结论:根据话题一致性的讨论结果,可以得出结论,最理想的话题数量是话题 10,因为与其他话题相比,它的话题值最高。这里的建议是能够实时、准确地显示或获取印尼的洪水信息。
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引用次数: 0
Analisis Pola Konsumen Dalam Bertransaksi Bisnis di Bengkel Resmi AHASS Total Honda Motor 在 AHASS 全面本田汽车官方研讨会上的消费者交易模式分析
Pub Date : 2023-11-29 DOI: 10.30989/teknomatika.v16i1.1133
Budi Wardoyo, Puji Winar Cahyo, Muhammad Habibi, M. Abu, Amar Al Badawi
The accumulated data, which consists of facts and transaction events in a business, should be processed and utilized for the progress of business development. Currently, the data owned by AHASS THM has not been optimized and further processed to provide broader benefits, such as promotion and forming loyal AHASS customers. The objective of this research is to analyze the existing transaction data to identify consumer transaction patterns at AHASS THM. The research methodology used is Market Basket Analysis (MBA), a method for analyzing consumer transaction data by finding associative relationships between different items in the consumer's shopping cart. By applying a minimum parameter limitation of support = 0.001, confidence = 0.8, and sorting based on the magnitude of the confidence parameter, 62 associative rules of consumer transaction patterns in AHASS THM business were obtained. By selecting the top 10 associative rules based on the highest confidence values, generally, these associative rules have a confidence parameter greater than 0.95 or 95%. Additionally, there are 3 associative rules with a confidence value of 1 or 100%, indicating that consumers will purchase Bearing Needle 20x29x218 after buying Bearing Ball 6902U, or a combination of Bearing Ball 6902U with CVT Grease 10 gr or Oli MPX2 0.8 lt.
积累的数据由业务中的事实和交易事件组成,应加以处理和利用,以促进业务发展。目前,AHASS THM 拥有的数据尚未得到优化和进一步处理,以提供更广泛的效益,如促销和形成忠诚的 AHASS 客户。本研究的目的是分析现有的交易数据,以确定 AHASS THM 的消费者交易模式。使用的研究方法是市场篮子分析法(MBA),这是一种通过发现消费者购物车中不同商品之间的关联关系来分析消费者交易数据的方法。通过应用支持度 = 0.001、置信度 = 0.8 的最小参数限制,并根据置信度参数的大小进行排序,得到了 AHASS THM 企业消费者交易模式的 62 条关联规则。根据最大置信度值选出前 10 条关联规则,一般来说,这些关联规则的置信度参数大于 0.95 或 95%。此外,有 3 条关联规则的置信度值为 1 或 100%,表明消费者在购买轴承滚珠 6902U 或轴承滚珠 6902U 与 CVT 润滑脂 10 克或 Oli MPX2 0.8 公升的组合后会购买轴承滚针 20x29x218。
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引用次数: 0
Sistem Prediksi Kasus Covid-19 di Indonesia Menggunakan Algoritma Linear Regression 使用线性回归算法的印度尼西亚 Covid-19 病例预测系统
Pub Date : 2023-11-27 DOI: 10.30989/teknomatika.v16i1.1099
Yusriyah Isnaini Mufidah, A. Saputra, Netania Indi Kusumaningtyas
The Coronavirus disease outbreak caused by severe acute respiratory syndrome by coronavirus 2 was first reported in Wuhan, Hubei province, China in December 2019, until March 2, 2020, President Joko Widodo announced the first case of an Indonesian citizen who was confirmed positive for COVID-19. The development of new cases of COVID-19 patients in Indonesia is still being reported even though the pandemic has lasted for almost two years. Then need a way to determine predictions or predict the number of increases in Indonesia’s COVID-19 cases in the future using machine learning technology with the Linear Regression algorithm. Estimating the number of active cases adding positive COVID-19 cases in Indonesia over the next 3 months using the machine learning method using the Linear Regression algorithm. This study predicts COVID-19 cases using machine learning with the Linear Regression algorithm. The model results have a linear coefficient, so the model predicts very well for linear data on days 0 – 300, and on the day after that, the number of positive cases of the national COVID-19 virus does not continue to show a linear relationship, the model becomes inaccurate again. The results of the parameter evaluation show that the level of accuracy is low, but this model can be used as a reference for case predictions for the next month with the results of comparison of predicted data and actual data not much different.
2019年12月,中国湖北省武汉市首次报告由冠状病毒2型引起的严重急性呼吸系统综合征所导致的冠状病毒疾病疫情,直到2020年3月2日,印尼总统佐科-维多多宣布首例印尼公民确诊COVID-19阳性病例。尽管疫情已持续近两年,但印尼仍有新的 COVID-19 患者病例报告。因此需要一种方法,利用线性回归算法的机器学习技术来确定预测或预测印度尼西亚 COVID-19 病例在未来的增加数量。使用线性回归算法的机器学习方法,估算未来 3 个月印度尼西亚 COVID-19 阳性病例增加的活跃病例数。本研究利用线性回归算法的机器学习技术预测 COVID-19 病例。模型结果具有线性系数,因此模型对 0 - 300 天的线性数据预测非常准确,而在之后的日子里,全国 COVID-19 病毒阳性病例数没有继续呈现线性关系,模型又变得不准确。参数评估结果表明,该模型的准确度较低,但可以作为下一个月病例预测的参考,预测数据与实际数据的比较结果相差不大。
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引用次数: 0
EVALUASI PADA WEBSITE SRAGENKAB.GO.ID MENGGUNAKAN METODE WEB USABILITY EVALUATION (WEBUSE) DAN WEB CONTENT ACCESSIBILITY GUIDELINES (WCAG) 2.1 对 sragenkab.go.id 网站的评估采用了网络可用性评估 (webuse) 和网络内容可访问性指南 (wcag) 2.1 的方法。
Pub Date : 2023-11-27 DOI: 10.30989/teknomatika.v16i1.1105
Siti Fatimah, Ahmad Hanafi, Kharisma, Alfun Roehatul Jannah
The sragenkab.go.id website serves as a vital platform supporting the operations of the Sragen district government, disseminating accurate and prompt information to the public. However, various issues hamper its functionality, such as interface display problems, unclear layout, non-functional links, excessively simple design, and slow response times. To address these concerns, this study aims to evaluate the sragenkab.go.id website's usability and accessibility aspects using the Website Usability Evaluation (WEBUSE) method and the Web Content Accessibility Guideline (WCAG) 2.1 method, respectively. Using the WEBUSE method, a survey questionnaire was distributed to 100 respondents from Sragen to assess the usability level of the website. The obtained score of 0.65 indicated that the website's usability is categorized as "good" and has been accepted by the users. On the other hand, the accessibility evaluation using the WCAG 2.1 method, with the assistance of the WAVE tool and accessibilitychecker, revealed a score below 75%, indicating a significant risk of non-compliance with international accessibility standards. In conclusion, the sragenkab.go.id website exhibits commendable usability; however, it falls short in terms of accessibility. The findings emphasize the importance of optimizing the website's accessibility to adhere to international regulatory standards, ensuring equitable access to information and services for all users. Future improvement efforts should focus on rectifying accessibility issues to enhance the overall user experience and inclusivity of the website.
sragenkab.go.id网站是支持斯拉根区政府运作的重要平台,向公众发布准确、及时的信息。然而,各种问题阻碍了网站功能的发挥,如界面显示问题、布局不清晰、链接功能缺失、设计过于简单以及响应速度缓慢等。为了解决这些问题,本研究旨在分别使用网站可用性评估(WEBUSE)方法和《网站内容可访问性指南》(WCAG)2.1 方法对 sragenkab.go.id 网站的可用性和可访问性进行评估。使用 WEBUSE 方法,向来自 Sragen 的 100 名受访者发放了调查问卷,以评估网站的可用性水平。所得分数为 0.65,表明网站的可用性被归类为 "良好",并得到了用户的认可。另一方面,在 WAVE 工具和可访问性检查器的帮助下,使用 WCAG 2.1 方法进行的可访问性评估显示,得分低于 75%,表明存在不符合国际可访问性标准的重大风险。总之,sragenkab.go.id 网站的可用性值得称赞,但在无障碍性方面却存在不足。调查结果强调了优化网站无障碍性的重要性,以符合国际监管标准,确保所有用户都能公平地获取信息和服务。今后的改进工作应侧重于纠正无障碍问题,以提高网站的整体用户体验和包容性。
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Teknomatika: Jurnal Informatika dan Komputer
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