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Development of Information and Management System of Student Competition Groups through User-Centered Design Approach 以用户为中心的学生竞赛小组信息管理系统的开发
Pub Date : 2023-04-15 DOI: 10.23917/khif.v9i1.17974
Dinan Yulianto, A. R. C. Baswara, Lugas Alhawariy, Marina Indah Prasasti, Gema Antika Hariadi
The majority of universities in Indonesia make maximum efforts to participate and excel in the implementation of the Student Creativity Program (namely: PKM). PKM requires students to collaborate interdisciplinary or multidisciplinary. The problem at the beginning of PKM implementation is establishing groups, where students find it difficult to have fellow students or supervisors from different disciplines in groups and according to the topic of their PKM. This research develops a user-oriented interaction and interface of information systems and group management. Development was carried out through a User-Centered Design which consisted of the following stages: plan the human-centered process; understand and specify the context of use; specify the user requirements; produce design solutions to meet user requirements; and evaluate the design against the requirements. Testing using System Usability Scale (SUS) and User Experience Questionnaire (UEQ) approach were conducted on 30 respondents who had competencies as business analysts, programmers, and testers. The results of the mean score of the SUS test are 80, and the mean Score of the UEQ test on the Attractiveness variable is 1.922, Clarity is 2.158, Efficiency is 2.042, Accuracy is 1.708, Stimulation is 1.967, and Novelty is 1.917. The system has achieved the goals and user experience because all the testing scores are above the standard provisions.
印度尼西亚的大多数大学都尽最大努力参与并在学生创造力计划(即:PKM)的实施中脱颖而出。PKM要求学生跨学科或多学科合作。PKM实施之初的问题是建立小组,学生发现很难根据他们的PKM主题将来自不同学科的同学或导师分组。本研究开发了一种面向用户的信息系统与群组管理交互界面。开发是通过以用户为中心的设计进行的,该设计包括以下几个阶段:计划以人为中心的过程;理解和指定使用的上下文;明确用户需求;提供满足用户需求的设计方案;并根据需求评估设计。使用系统可用性量表(SUS)和用户体验问卷(UEQ)方法的测试在30名受访者中进行,他们具有业务分析师、程序员和测试人员的能力。SUS测试的平均得分为80分,UEQ测试在吸引力变量上的平均得分为1.922分,清晰度为2.158分,效率为2.042分,准确性为1.708分,刺激为1.967分,新颖性为1.917分。由于所有测试成绩均高于标准规定,系统达到了目标和用户体验。
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引用次数: 0
Aggregate Functions in Categorical Data Skyline Search (CDSS) for Multi-keyword Document Search 分类数据天际线搜索(CDSS)在多关键词文档搜索中的聚合功能
Pub Date : 2023-04-10 DOI: 10.23917/khif.v9i1.18127
Mardiah Mardiah, Annisa Annisa, S. N. Neyman
- Literature review is the first step in starting research for a deep understanding of the research interest. However, finding literature relevant to research interests is difficult and takes time. Skyline query is a method that can be used for filtering. An object p is said to dominate object q if p equals q on all of its attributes, and p is at least better than q on one attribute. Categorical Data Skyline Search (CDSS) is an algorithm that can filter skyline objects in categorical data types such as documents. CDSS uses Extended Distance Wu and Palmer (DEWP) to calculate the distance between the user query and document keywords. The document keywords and user queries are represented as nodes in the ACM CCS ontology, and documents are assumed to be represented by a single keyword. This study aims to use the CDSS algorithm to search for skyline documents represented by more than one keyword by adding an aggregate function (average, minimum, maximum) to the CDSS algorithm, especially in calculating DEWP. This study used the thesis documents from the IPB University computer science department. Document keywords will be extracted using the Term Frequency-Inverse Term Frequency (TF-IDF) method. The collected keywords will be mapped in a mixed ontology tree that refers to the Association of Computing Machinery Computing Classification System 2012 (ACM CCS 2012) and Computer Science Ontology (CSO) as ontology standards in computer science. The skyline query algorithm for determining skyline documents is Block Nested Loop (BNL). The evaluation method uses the skyline ratio of each aggregate function in the CDSS. Based on the ratio value, CDSS using the maximum DEWP has the most relevant skyline results compared to the average DEWP and minimum DEWP.
-文献综述是开始研究的第一步,以便深入了解研究兴趣。然而,找到与研究兴趣相关的文献是困难的,而且需要时间。Skyline查询是一种可用于过滤的方法。如果一个对象p在其所有属性上都等于q,并且p至少在一个属性上优于q,那么我们就说它支配对象q。分类数据天际线搜索(CDSS)是一种可以过滤分类数据类型(如文档)中的天际线对象的算法。CDSS使用DEWP (Extended Distance Wu and Palmer)来计算用户查询与文档关键字之间的距离。文档关键字和用户查询用ACM CCS本体中的节点表示,文档假设用单个关键字表示。本研究旨在通过在CDSS算法中加入一个聚合函数(average, minimum, maximum),特别是在计算DEWP时,利用CDSS算法搜索由多个关键字表示的天际线文档。本研究使用IPB大学计算机科学系的论文文件。使用词频-逆词频(TF-IDF)方法提取文档关键词。将收集到的关键词映射到一个混合本体树中,该树以计算机科学本体标准ACM CCS 2012和计算机科学本体CSO作为计算机科学本体标准。确定天际线文档的天际线查询算法是块嵌套循环(BNL)。评价方法采用CDSS中各聚合函数的天际线比值。根据比值值,与平均DEWP和最小DEWP相比,使用最大DEWP的CDSS具有最相关的天际线结果。
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引用次数: 0
Design Development of Detection System and Ro-Ro Ship Notification based on Fuzzy Inference System 基于模糊推理系统的检测系统及滚装船舶通知的设计开发
Pub Date : 2023-04-10 DOI: 10.23917/khif.v9i1.16759
Mochammad Jafar Tri Febriansyah, S. Wahjuni, Indra Jaya
- Ship stability is very important for the safety of ship motion. There are many factors that affect the stability of a ship. One of the causes of accidents on ships is the problem of ship stability, including the ship cannot be controlled, and loses balance due to improper placement of cargo loads. This study combines gyroscopes, accelerometers, compasses, and GPS sensors, so that more accurate ship tilt information is obtained through an Android smartphone application. This study uses the fuzzy inference system (FIS) method with a trapezoidal membership function where there are 2 inputs and 1 output. Ship tilt input uses 3 linguistic variables very tilted, tilted, and stable. The slope duration input uses 5 very fast, fast, fairly fast, slow, and very slow linguistic variables. Ship status output is divided into 3 linguistic variables safe, alert, and dangerous. Testing and implementation with an input slope of 4.8 and a slope duration of 10 seconds using the Sugeno fuzzy method, the ship's crips value of 0.65 with an alert status was obtained. Calculation of the accuracy of the gyroscope sensor error using the MAPE method, the result is an error percentage of 6.55% (very good). The system accuracy error of 39 trials (36 correct and 3 incorrect) is 92.30% (very good). This research is expected to make it easier for the captain to monitor the stability of the ship and can provide notification of the status of the ship to the captain of the ship if there is a condition of the ship that needs to be watched out for. In addition, the notification will also be received by Port officers on land.
船舶的稳定性对船舶的运动安全至关重要。影响船舶稳定性的因素有很多。船舶发生事故的原因之一是船舶的稳定性问题,包括船舶无法控制,由于货物装载位置不当而失去平衡。本研究结合陀螺仪、加速度计、罗盘和GPS传感器,通过Android智能手机应用程序获得更准确的船舶倾斜信息。本研究采用具有梯形隶属函数的模糊推理系统(FIS)方法,其中有2个输入和1个输出。船舶倾斜输入使用3个语言变量非常倾斜,倾斜和稳定。斜率持续时间输入使用5个非常快、快速、相当快、慢和非常慢的语言变量。船舶状态输出分为安全、警戒和危险三个语言变量。采用Sugeno模糊法在输入坡度为4.8、坡度持续时间为10秒的情况下进行测试与实现,得到了该船的crips值为0.65,处于警戒状态。利用MAPE方法计算陀螺仪传感器的精度误差,结果误差率为6.55%(非常好)。39次试验(正确36次,错误3次)的系统精度误差为92.30%(很好)。通过这项研究,船长可以更容易地监测船舶的稳定性,如果船舶有需要注意的情况,可以向船长提供船舶状态的通知。此外,岸上的港务人员也会收到通知。
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引用次数: 0
Serious Game to Training Focus for Children with Attention Deficit Hyperactivity Disorder: “Tanji Adventure to the Diamond Temple” 严肃游戏对注意缺陷多动障碍儿童训练重点的影响:“丹次钻寺历险”
Pub Date : 2023-04-10 DOI: 10.23917/khif.v9i1.18393
S. Mulyati
Attention Deficit Hyperactivity Disorder (ADHD) affects the academic performance of youngsters. Children with ADHD struggle to remain focused during learning due to decreased attention and concentration. They are highly active and have trouble remembering teachers' instructions. Attention difficulties, focus disorders, and hyperactivity might hinder learning. This work aims to observe the impact of serious games with a platformer genre and puzzles titled "Tanji Adventure to the Diamond Temple" on the learning activities of kids with ADHD. The goal is to create a fun and engaging learning environment to boost the motivation and focus of those with ADHD. Game development process utilizes iterative prototyping. Each iteration yields a prototype that refines in the next iteration. The game was tested on children with ADHD by examining their behavior before and after playing to evaluate whether new game mechanics were necessary. The review procedure includes observing youngsters and interviewing teachers and involves specialists to evaluate its contents. The study confirms that the concentration of children with ADHD increase after playing the game. The game incorporates elements that help youngsters with ADHD concentrate and increase their attention span
注意缺陷多动障碍(ADHD)影响青少年的学习成绩。患有多动症的儿童在学习过程中很难保持专注,因为注意力和集中力下降。他们非常活跃,很难记住老师的指示。注意力困难、注意力障碍和多动症可能会阻碍学习。本研究旨在观察平台游戏类型的严肃游戏和益智游戏《Tanji Adventure to the Diamond Temple》对ADHD儿童学习活动的影响。我们的目标是创造一个有趣和吸引人的学习环境,以提高多动症患者的学习动力和注意力。游戏开发过程利用迭代原型。每次迭代都会产生一个原型,在下一次迭代中进行细化。这款游戏是在患有多动症的儿童身上测试的,通过检查他们在玩游戏前后的行为来评估新的游戏机制是否必要。审查程序包括观察青少年和采访教师,并邀请专家对其内容进行评估。该研究证实,患有多动症的儿童在玩完游戏后注意力更加集中。这个游戏包含了一些元素,可以帮助患有多动症的青少年集中注意力,增加他们的注意力
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引用次数: 1
Batik Pattern Classification using Naïve Bayes Method Based on Texture Feature Extraction 基于纹理特征提取的蜡染图案分类Naïve贝叶斯方法
Pub Date : 2023-04-10 DOI: 10.23917/khif.v9i1.21207
I. Riadi, A. Fadlil, Izzan Julda D.E Purwadi Putra
One of the arts in Surakarta culture is batik cloth. A batik is a form of heritage from the nation's ancestors whose manufacturing process must use specific tools and materials. Surakarta's typical batik has many patterns and motifs, such as Sawat, Satriomanah, and Semenrante. The pattern is a picture framework whose results will display the type of batik. A batik may resemble one type and another, so a classification technique is needed to determine the type of batik. This study aims to develop a classification method for batik cloth using the Naïve Bayes classification technique. The feature extraction used is the Gray Level Co-Occurrence Matrix (GLCM) to obtain texture values in each image. The stages in this research include pre-processing, feature extraction, classification, and testing. The training data in this study were 200 images for each Sawat, Satriomanah, and Sementrante class obtained from the data augmentation method by flipping, zooming, cropping, shifting, and changing the brightness of the images. The total sample data is 600 images. The amount of training data and data testing was divided three times (60% training and 40% testing), (70% training and 30% testing), and (80% training and 20% testing) for accuracy. In this study, the Naïve Bayes method using WEKA 3.8.6 tools obtained the best accuracy of 97.22% using a 70% percentage split compared to using 80% and 60% percentage splits with a result of 96.66%, this difference occurs due to differences in training data and test data. The results of this study indicate that the Naïve Bayes method can be used to classify batik cloth patterns based on texture feature extraction.
腊惹文化的艺术之一是蜡染布。蜡染是一个民族祖先的遗产,它的制作过程必须使用特定的工具和材料。泗水的典型蜡染有许多图案和图案,如Sawat、Satriomanah和Semenrante。图案是一个图片框架,其结果将显示蜡染的类型。蜡染可能类似于一种类型和另一种类型,因此需要一种分类技术来确定蜡染的类型。本研究旨在发展一种利用Naïve贝叶斯分类技术的蜡染布料分类方法。所使用的特征提取是灰度共生矩阵(GLCM),以获得每个图像的纹理值。本研究包括预处理、特征提取、分类和测试四个阶段。本研究的训练数据是采用数据增强方法,通过对图像进行翻转、缩放、裁剪、移动、改变亮度,得到的Sawat、Satriomanah、Sementrante类各200张图像。样本数据总数为600张图像。训练数据和数据测试的数量分为三次(60%训练和40%测试),(70%训练和30%测试)和(80%训练和20%测试)用于准确性。在本研究中,Naïve贝叶斯方法使用WEKA 3.8.6工具,使用70%百分比分割得到的准确率为97.22%,而使用80%和60%百分比分割得到的准确率为96.66%,这种差异是由于训练数据和测试数据的差异造成的。本研究结果表明,Naïve贝叶斯方法可用于基于纹理特征提取的蜡染图案分类。
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引用次数: 0
Measuring Usability on User-Centered Mobile Web Application: Case Study on Financial Mathematics Calculator 衡量以用户为中心的移动Web应用的可用性:以金融数学计算器为例
Pub Date : 2023-04-10 DOI: 10.23917/khif.v9i1.19409
Ati Suci Dian Martha, Ezar Rizqullah Tsaqif Setyawan, Rosa Reska Riskiana
Financial literacy is a person's skills regarding financial knowledge and behavior. In 2019, the National Survey of Financial Literacy and Inclusion (SNLIK) stated that Indonesia had a low level of financial literacy with a percentage of 38.03%. In 2016, the Indonesian government incorporated financial literacy into the K13 curriculum for the high school level to improve financial literacy at the student level. In line with that, students need facilities to help them learn financial literacy. This study aims to build an interaction design of financial mathematics calculators using the User-Centered Design method. The limitation of this study is the design uses a mobile web platform that targets high school students. The results of usability testing on effectiveness get an average task-completion rate score of 92.3%, an average efficiency of 92.0% overall relative efficiency, user satisfaction using the System Usability Scale (SUS) gets a score of 93.2 for the usability factor and a score of 74 for the learnability factor. The findings of this study indicate that the application is easy to use and provides a positive experience in learning financial literacy. The current study's results will support this application's use in future research as a new tool for providing financial literacy.
金融素养是一个人在金融知识和行为方面的技能。2019年,全国金融素养和包容性调查(SNLIK)表明,印度尼西亚的金融素养水平较低,比例为38.03%。2016年,印尼政府将金融知识纳入高中K13课程,以提高学生的金融知识水平。与此相一致,学生需要设施来帮助他们学习金融知识。本研究旨在运用以用户为中心的设计方法,构建金融数学计算器的交互设计。本研究的局限性在于设计使用的是针对高中生的移动网络平台。有效性可用性测试的平均任务完成率为92.3%,总体相对效率平均为92.0%,使用系统可用性量表(SUS)的用户满意度在可用性因子上得到93.2分,在可学习性因子上得到74分。本研究结果显示,本应用程式易于使用,并提供学习财务知识的正面体验。目前的研究结果将支持该应用程序作为提供金融知识的新工具在未来的研究中使用。
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引用次数: 0
Android-Based Short Message Service Filtering using Long Short-Term Memory Classification Model 基于长短期记忆分类模型的android短消息服务过滤
Pub Date : 2022-10-30 DOI: 10.23917/khif.v8i2.17995
M. L. Mustagfirin, G. W. Wiriasto, I. M. B. Suksmadana, I. P. Kinasih
Short Message Service (SMS) is a technology for sending messages in text format between two mobile phones that support such a facility. Despite the emergence of many mobile text messaging applications, SMS still finds its use in communication among people and broadcasting messages by governments and mobile providers. SMS users often receive messages from parties, particularly for marketing and business purposes, advertisements, or elements of fraud. Many of those messages are irrelevant and fraudulent spam. This research aims at developing android-based applications that enable the filtering of SMS in Bahasa Indonesia. We investigate 1469 SMS text data and classify them into three categories: Normal, Fraudulent, and Advertisement. The classification or filtering method is the long short-term memory (LSTM) model from TensorFlow. The LSTM model is suitable because it has cell states in the architecture that are useful for storing previous information. The feature is applicable for use on sequential data such as SMS texts because every word in the texts constructs a sequential form to complete a sentence. The observation results show that the classification accuracy level is 95%. This model is then integrated into an Android-based mobile application to execute a real-time classification.
短消息服务(SMS)是一种在支持这种功能的两个移动电话之间以文本格式发送消息的技术。尽管出现了许多移动短信应用程序,SMS仍然在人们之间的通信和政府和移动提供商的广播消息中使用。SMS用户经常收到来自各方的消息,特别是出于营销和商业目的、广告或欺诈元素。其中许多消息是无关的和欺诈性的垃圾邮件。这项研究的目的是开发基于android的应用程序,使短信过滤在印尼语。我们调查了1469条短信数据,并将其分为三类:正常、欺诈和广告。分类或过滤方法是来自TensorFlow的长短期记忆(LSTM)模型。LSTM模型是合适的,因为它在体系结构中具有对存储以前的信息有用的单元状态。该特性适用于SMS文本等顺序数据,因为文本中的每个单词都构建了一个顺序形式来完成一个句子。观察结果表明,分类准确率达到95%。然后将该模型集成到基于android的移动应用程序中,以执行实时分类。
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引用次数: 0
Recommendation System to Propose Final Project Supervisors using Cosine Similarity Matrix 基于余弦相似矩阵的项目导师推荐系统
Pub Date : 2022-10-30 DOI: 10.23917/khif.v8i2.16235
Zulfa Fajrul Falah, Fajar Suryawan
- The selection of a supervisor is an important thing and one of the determinants of whether or not a student's final project research is successful. At the location of this research, students select a supervisor by considering his academic records and recommendations from classmates or seniors. Words of mouth dominate their motivation, and many students do not have a basis for their choice. Selection of the best-fit supervisor significantly impacts a student's progression. Students will be more enthusiastic about doing the final project and may get facilitation in their research because the topics of the student projects match the supervisor's interests and ongoing work. This study aims to make a recommendation system that suggests a supervisor for a student. The student fills in the title, abstract, and keywords of his proposal. The system gives suggestions to prospective supervisors by calculating the similarity of the data with titles, abstracts, and keywords of published articles found in Google Scholar. The recommendation system uses the content-based filtering method to produce a list of recommendations. The cosine similarity algorithm calculates how similar the topic proposed by students is to the lecturers' interests. In building a website-based recommendation system, the authors use Django web framework as the backend and ReactJs as the frontend. The application succeeds in suggesting final project supervisors that match lecturers' interests and expertise with students' proposals.
-导师的选择是一件重要的事情,也是学生最终项目研究是否成功的决定因素之一。在本研究的地点,学生通过考虑他的学习成绩和同学或学长的推荐来选择导师。口碑主导了他们的动机,许多学生没有选择的依据。选择最合适的导师对学生的进步有很大的影响。学生将更热衷于做期末项目,并可能在他们的研究中得到便利,因为学生项目的主题与导师的兴趣和正在进行的工作相匹配。本研究旨在建立一个为学生推荐导师的推荐系统。学生填写提案的题目、摘要和关键词。该系统通过计算数据与谷歌Scholar中已发表文章的标题、摘要和关键词的相似度,为未来的导师提供建议。推荐系统使用基于内容的过滤方法生成推荐列表。余弦相似度算法计算学生提出的话题与讲师的兴趣有多相似。在构建基于网站的推荐系统时,作者使用Django web框架作为后端,ReactJs作为前端。该应用程序成功地建议最终项目主管,将讲师的兴趣和专业知识与学生的建议相匹配。
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引用次数: 0
Application of Low Back Pain Myogenic Therapy Based on Multimedia 基于多媒体的腰痛肌源性治疗的应用
Pub Date : 2022-10-13 DOI: 10.23917/khif.v8i2.15645
Alfian Gema Negara, N. S. Puspitasari
Low back pain restricts activity and causes work absenteeism. Cases of low back pain are common worldwide. This paper presents the design of multimedia-based low back pain myogenic therapy aids. Data collection involves observation and interviews with medical rehabilitation specialists and physiotherapists. The collected data is represented using a production ruler in the form of if - then.  Rule-based reasoning can be used as an expert system knowledge base in cases of myogenic low back pain. Forward chaining can be used as an inference engine for similar cases because the reasoning starts from the facts section before reaching the hypothesis. Design of this assistive device model is expected to provide information regarding the choice of therapy for low back pain myogenic by patients, independently at home or with the help of close family. Application design is multimedia-based to make it easier for users to look at examples visually. The expert system application is well accepted by users. Ten physiotherapists and one doctor consider the application performance good because it attains an acceptable value of 0.80 or 80%. The physiotherapists suggest that this assistive device model will likely increase the intensity of therapy because it can be carried out by the patient's family independently.
腰痛限制活动并导致旷工。腰痛在全世界都很常见。本文介绍了基于多媒体的腰痛肌源性治疗辅助装置的设计。数据收集包括观察和与医疗康复专家和物理治疗师的访谈。收集到的数据使用if - then形式的生产标尺表示。基于规则的推理可以作为肌源性腰痛病例的专家系统知识库。前向链可以用作类似情况的推理引擎,因为推理从事实部分开始,然后到达假设。这种辅助装置模型的设计有望为患者在家中独立或在家人的帮助下选择治疗下腰背痛的方法提供信息。应用程序设计是基于多媒体的,使用户更容易直观地查看示例。专家系统的应用得到了用户的认可。10名物理治疗师和1名医生认为应用程序性能良好,因为它达到了0.80或80%的可接受值。物理治疗师建议,这种辅助装置模型可能会增加治疗的强度,因为它可以由患者的家人独立进行。
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引用次数: 0
Object Detection to Identify Shapes of Swallow Nests Using a Deep Learning Algorithm 使用深度学习算法识别燕窝形状的目标检测
Pub Date : 2022-10-13 DOI: 10.23917/khif.v8i2.16489
Denny Indrajaya, Adi Setiawan, Djoko Hartanto, Hariyanto Hariyanto
- Object detection is basic research in the field of computer vision to detect objects in an image or video. the TensorFlow framework is a widely adopted framework to create object detection programs and models. In this study, an object detection program and model are designed to detect the shape of a swallow's nest which consists of three classes, namely oval, angular, and bowl. The purpose model creation is to find out the likeliness of the swallow's nest to the three classes for the swallow's nest sorting machine. The adopted architecture in the modeling is the MobileNet V2 FPNLite SSD since the model obtained from this architecture results in a good speed in detecting objects. Based on the evaluation results that has been carried out, the model can detect the shape of the swallow's nest which is divided into 3 classes, but in some cases swallow's nest are detected into two classes. This issues can still be handled by adjustmenting several parameterss to the object detection program. Results shows that the obtained mAP value of 61.91%, indicating the model can detect the shape of a swallow's nest moderately.
-目标检测是计算机视觉领域的基础研究,用于检测图像或视频中的目标。TensorFlow框架是一个被广泛采用的框架,用于创建对象检测程序和模型。本研究设计了一个物体检测程序和模型来检测燕窝的形状,燕窝的形状分为椭圆形、棱角形和碗形三种类型。创建模型的目的是为了找出燕窝分类机对三类的似然度。建模采用的体系结构是MobileNet V2 FPNLite SSD,该体系结构得到的模型具有较好的对象检测速度。根据已经进行的评价结果,该模型可以检测燕窝的形状,将燕窝分为3类,但在某些情况下,燕窝被检测为2类。这个问题仍然可以通过调整目标检测程序的几个参数来处理。结果表明,得到的mAP值为61.91%,表明该模型能较好地检测出燕窝的形状。
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引用次数: 2
期刊
Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika
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