Pub Date : 2024-01-11DOI: 10.52088/ijesty.v3i4.468
Piter Titirloloby
Technology in the 21st century is valid in human social life. Almost all people all over the world use technology to complete their needs. Using the WhatsApp application on mobile phones or social media connected with a network of students in SMA Xaverius Ambon is more beneficial. This research focuses on the actual condition related to the impact of WhatsApp in EFL classes on The learning performance of second-grade students of SMA Negeri Xaverius Ambon. The researcher used a survey design to find the results of the students in the EFL Classroom perspective in using WhatsApp on students' learning performance. Fifty students' perspective answers from class A and class B of the second grade of SMA Negeri Xaverius Ambon were interviewed, and 50 questionnaires were given to students in the classroom. This research maintained that harmful purpose impacts the student's learning performance more. This research revealed that WhatsApp can be used to communicate easier and faster, providing specific and practical information and sharing knowledge among students; instead, it is acquired negatively on the performance of SMA Xaverius Ambon students. The findings of this research can be beneficial to SMA Xaverius EFL students and classroom teachers in developing WhatsApp in the teaching and learning process.
技术在 21 世纪的人类社会生活中发挥着重要作用。全世界几乎所有的人都使用技术来满足自己的需求。使用手机上的 WhatsApp 应用程序或社交媒体与 Xaverius Ambon SMA 的学生网络连接会带来更多益处。本研究的重点是 WhatsApp 在 EFL 课堂上对 SMA Negeri Xaverius Ambon 二年级学生学习成绩的影响。研究人员采用了调查设计，以了解学生在 EFL 课堂上使用 WhatsApp 对学生学习成绩的影响。研究人员采访了来自SMA Negeri Xaverius Ambon二年级A班和B班的50名学生，并向课堂上的学生发放了50份调查问卷。本研究认为，有害的目的对学生的学习成绩影响更大。本研究显示，WhatsApp 可用于更方便快捷的沟通，提供具体实用的信息，并在学生之间分享知识；相反，WhatsApp 却对安汶岛国立自治大学学生的学习成绩产生了负面影响。本研究的结果将有助于 SMA Xaverius EFL 学生和任课教师在教学和学习过程中开发 WhatsApp。
{"title":"The Impact of WhatsApp in EFL Class on Student's Learning Performance of Second-Grade Students of SMA Xaverius Ambon","authors":"Piter Titirloloby","doi":"10.52088/ijesty.v3i4.468","DOIUrl":"https://doi.org/10.52088/ijesty.v3i4.468","url":null,"abstract":"Technology in the 21st century is valid in human social life. Almost all people all over the world use technology to complete their needs. Using the WhatsApp application on mobile phones or social media connected with a network of students in SMA Xaverius Ambon is more beneficial. This research focuses on the actual condition related to the impact of WhatsApp in EFL classes on The learning performance of second-grade students of SMA Negeri Xaverius Ambon. The researcher used a survey design to find the results of the students in the EFL Classroom perspective in using WhatsApp on students' learning performance. Fifty students' perspective answers from class A and class B of the second grade of SMA Negeri Xaverius Ambon were interviewed, and 50 questionnaires were given to students in the classroom. This research maintained that harmful purpose impacts the student's learning performance more. This research revealed that WhatsApp can be used to communicate easier and faster, providing specific and practical information and sharing knowledge among students; instead, it is acquired negatively on the performance of SMA Xaverius Ambon students. The findings of this research can be beneficial to SMA Xaverius EFL students and classroom teachers in developing WhatsApp in the teaching and learning process.","PeriodicalId":14149,"journal":{"name":"International Journal of Engineering, Science and Information Technology","volume":" 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139626037","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}
“Metaverse” is the idea of a shared virtual environment that is “parallelized” to the real world thanks to advances in technology. The metaverse world is currently not only used as a platform for playing games but has also been used as a place for doing business. The purpose of this research is to identify articles that study the metaverse in marketing and provide an overview of the Metaverse knowledge domain as a new marketing world and to show and explain the research mapping. This mapping will help researchers explore and develop research related to the metaverse as a new marketing world landscape. Marketing is a promotional activity that can attract consumers to increase sales. Metaverse is a virtual universe that imitates real world procedures. In this 3D virtual environment, users can carry out activities in the digital world like in the real world, as is done with the Gucci brand which uses the metaverse as a marketing medium based on blockchain TheSandbox. This will have a major impact on how companies implement marketing in the future and how people communicate with each other. In Industry 5.0, metaverse has entered the world of marketing and has begun to be used by several companies. So, metaverse becomes a new world in marketing. This research uses qualitative methods with bibliometric techniques by utilizing Visualization of Similarities (Vosviewers) as an application. By entering keywords such as Metaverse; Metaverse marketing; Digital Marketing; New Marketing Universe; Gen z to search for articles via Publish or Perish with a total of 940 articles which were then processed using VosViewers. The results of the analysis found scientific mapping and possible future studies regarding the metaverse as a new marketing world that can be used as variable recommendations for future researchers as a reference for subsequent articles.
{"title":"Mapping The Knowledge Domain of Metaverse The New Marketing Universe: A Bibliometric Analysis","authors":"Eilen Monika, Adi Setiawan, Iges Triasnita Miranda, Tasya Monica, Widhea Ayu Santika, Chalirafi Chalirafi","doi":"10.52088/ijesty.v3i4.467","DOIUrl":"https://doi.org/10.52088/ijesty.v3i4.467","url":null,"abstract":"“Metaverse” is the idea of a shared virtual environment that is “parallelized” to the real world thanks to advances in technology. The metaverse world is currently not only used as a platform for playing games but has also been used as a place for doing business. The purpose of this research is to identify articles that study the metaverse in marketing and provide an overview of the Metaverse knowledge domain as a new marketing world and to show and explain the research mapping. This mapping will help researchers explore and develop research related to the metaverse as a new marketing world landscape. Marketing is a promotional activity that can attract consumers to increase sales. Metaverse is a virtual universe that imitates real world procedures. In this 3D virtual environment, users can carry out activities in the digital world like in the real world, as is done with the Gucci brand which uses the metaverse as a marketing medium based on blockchain TheSandbox. This will have a major impact on how companies implement marketing in the future and how people communicate with each other. In Industry 5.0, metaverse has entered the world of marketing and has begun to be used by several companies. So, metaverse becomes a new world in marketing. This research uses qualitative methods with bibliometric techniques by utilizing Visualization of Similarities (Vosviewers) as an application. By entering keywords such as Metaverse; Metaverse marketing; Digital Marketing; New Marketing Universe; Gen z to search for articles via Publish or Perish with a total of 940 articles which were then processed using VosViewers. The results of the analysis found scientific mapping and possible future studies regarding the metaverse as a new marketing world that can be used as variable recommendations for future researchers as a reference for subsequent articles.","PeriodicalId":14149,"journal":{"name":"International Journal of Engineering, Science and Information Technology","volume":"36 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139442740","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}
Pub Date : 2023-09-20DOI: 10.52088/ijesty.v3i3.463
Rina Refianti, Novia Anggraeni
Zoom Cloud Meetings is an application that is used to conduct video conferencing. On the Google Play Store, the Zoom Cloud Meeting application received a rating of 3.8, with 500 million more downloads as of March 2021. The application has many advantages, such as not being disturbed by pauses in conversation and having good video and audio quality. The advantages possessed by these applications require development so that application services are getting better. For this reason, user reviews are needed to see user satisfaction with the application so that they can determine services that can be developed in the future. Based on this, this research was created to create a web-based application that can classify user reviews of the Zoom Cloud Meetings application using the Convolutional Neural Network (CNN) method and calculate the accuracy value. This application is built using the Flask framework and the Python programming language. Model training is carried out using the TensorFlow library. Applications that have been made are then tested using two stages of testing, namely system testing with black box and data testing. Based on system testing, it was found that the website can run well, and for data testing using test data, the accuracy result is 91.5%.
{"title":"Sentiment Analysis Using Convolutional Neural Network Method to Classify Reviews on Zoom Cloud Meetings Application Based on Reviews on Google Playstore","authors":"Rina Refianti, Novia Anggraeni","doi":"10.52088/ijesty.v3i3.463","DOIUrl":"https://doi.org/10.52088/ijesty.v3i3.463","url":null,"abstract":"Zoom Cloud Meetings is an application that is used to conduct video conferencing. On the Google Play Store, the Zoom Cloud Meeting application received a rating of 3.8, with 500 million more downloads as of March 2021. The application has many advantages, such as not being disturbed by pauses in conversation and having good video and audio quality. The advantages possessed by these applications require development so that application services are getting better. For this reason, user reviews are needed to see user satisfaction with the application so that they can determine services that can be developed in the future. Based on this, this research was created to create a web-based application that can classify user reviews of the Zoom Cloud Meetings application using the Convolutional Neural Network (CNN) method and calculate the accuracy value. This application is built using the Flask framework and the Python programming language. Model training is carried out using the TensorFlow library. Applications that have been made are then tested using two stages of testing, namely system testing with black box and data testing. Based on system testing, it was found that the website can run well, and for data testing using test data, the accuracy result is 91.5%.","PeriodicalId":14149,"journal":{"name":"International Journal of Engineering, Science and Information Technology","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136263216","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}
Pub Date : 2023-09-20DOI: 10.52088/ijesty.v3i3.462
Zekri Fitra Ramadhan, Achmad Benny Mutiara
Online games are a type of entertainment that is done by humans to have fun and forget all the problems in everyday life. Honkai: Star Rail is a new online game application owned by miHoYo which is currently popular and widely downloaded on the Google Play Store. Reviews on the Honkai: Star Rail app are increasing over time so this makes it difficult for app developers to know past user reviews on their apps. Therefore, the author conducted a study to analyze sentiment towards Honkai: Star Rail application reviews in Indonesian on the Google Play Store using the Bidirectional Encoder Representations from Transformers (BERT) method to determine user sentiment towards the Honkai: Star Rail application and then processed further so that it becomes a record for developers, users, and prospective users of the Honkai: Star Rail application. This study uses Indonesian language review data from users of the Honkai: Star Rail application found on the Google Play Store website as many as 6000 reviews. The BERT method applied in this study consisted of data collection, dataset labeling, data preprocessing, dataset splitting, modeling, model training, and evaluation. Based on the evaluation results that have been carried out on the test data, 97 data are true positive with 27 data are false positive, 4 data are true neutral with 47 data are false neutral, and 381 data are true negative with 37 data are false negative. So, it can be concluded that the model still has difficulty predicting reviews with neutral sentiment but is good enough at predicting reviews with positive and negative sentiment. In addition, the accuracy of the model is 81% with a precision of 63% for positive sentiment reviews, 36% for neutral sentiment reviews, and 89% for negative sentiment reviews.
网络游戏是一种娱乐方式，是人类为了娱乐和忘记日常生活中的所有问题而做的。Honkai: Star Rail是miHoYo旗下的一款新在线游戏应用，目前在Google Play Store上很受欢迎并被广泛下载。随着时间的推移，对Honkai: Star Rail应用的评论越来越多，这使得应用开发者很难了解过去用户对其应用的评论。因此，作者进行了一项研究，利用变形金刚的双向编码器表示(BERT)方法来分析谷歌Play商店中印度尼西亚语对Honkai: Star Rail应用程序的评论，以确定用户对Honkai: Star Rail应用程序的情绪，然后进一步处理，使其成为Honkai: Star Rail应用程序的开发者，用户和潜在用户的记录。本研究使用了来自用户的印尼语评论数据，这些用户在Google Play Store网站上发现了多达6000条评论。本研究采用的BERT方法包括数据收集、数据标注、数据预处理、数据分割、建模、模型训练和评估。根据已对测试数据进行的评价结果，97个数据为真阳性，27个数据为假阳性，4个数据为真中性，47个数据为假中性，381个数据为真阴性，37个数据为假阴性。因此，可以得出结论，该模型仍然难以预测中性情绪的评论，但在预测积极和消极情绪的评论方面足够好。此外，该模型的准确率为81%，正面情绪评论的准确率为63%，中性情绪评论的准确率为36%，负面情绪评论的准确率为89%。
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Pub Date : 2023-09-13DOI: 10.52088/ijesty.v3i2.461
Dede Herman Suryana, Wahyu Kusuma Raharja
Coffee is a highly popular beverage worldwide. The quality of coffee is often judged based on its aroma and taste. Good coffee quality is influenced by various parameters during the coffee bean roasting process. Roasting is a crucial step where green coffee beans are heated at high temperatures, undergoing chemical reactions such as hydrolysis, polymerization, and pyrolysis. The color changes during the roasting process are caused by melanoidin, which results from Maillard and caramelization reactions, also impacting the flavor profile. Therefore, it is essential to accurately classify the level of coffee bean maturity. In the development of supercomputer technology, particularly with high-speed GPU microprocessors and large memory capacities, artificial intelligence algorithms have been widely implemented in various applications. Research on smart machines has been conducted to create systems resembling human intelligence. One of its applications is in recognizing the maturity level of coffee beans during roasting. In this study, image segmentation using ROI (Region Of Interest) and RGB color features are utilized to identify the characteristics of each coffee bean image. Additionally, CNN (Convolutional Neural Network) is employed for the classification stage, and this model is implemented into an Android smartphone device to detect the type of coffee bean being roasted. After the training process with 100 epochs, the model achieved a loss of 0.12 and a training accuracy of 94.79%. The model is capable of classifying images from the test data with an average accuracy of 85.83% and a loss value of 0.35.
咖啡是一种全世界都很受欢迎的饮料。人们常常根据咖啡的香气和味道来判断咖啡的好坏。咖啡的品质受咖啡豆烘焙过程中各种参数的影响。烘焙是至关重要的一步，绿咖啡豆在高温下加热，经历水解、聚合和热解等化学反应。烘烤过程中的颜色变化是由美拉德和焦糖化反应产生的类黑素引起的，也影响了风味特征。因此，对咖啡豆的成熟度进行准确的分级是十分必要的。在超级计算机技术的发展中，特别是高速GPU微处理器和大容量内存的出现，使得人工智能算法得到了广泛的应用。智能机器的研究已经在进行，以创造类似人类智能的系统。它的一个应用是在烘焙过程中识别咖啡豆的成熟度。在本研究中，利用ROI (Region Of Interest)和RGB颜色特征对图像进行分割，识别每个咖啡豆图像的特征。此外，在分类阶段使用CNN(卷积神经网络)，并将该模型实现到Android智能手机设备中，以检测被烘焙咖啡豆的类型。经过100次epoch的训练过程，该模型的训练损失为0.12，训练准确率为94.79%。该模型能够从测试数据中对图像进行分类，平均准确率为85.83%，损失值为0.35。
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Pub Date : 2023-08-18DOI: 10.52088/ijesty.v3i2.456
Khairullah Yusuf, F. Fasdarsyah, Nura Usrina, M. Fauzan, Rahmi Nurahim
Multi-storey buildings are very susceptible to lateral forces, so reinforcement is needed to stiffen the building by adding a system of stiffeners to the building structure. In steel building structures, the system of stiffeners bracing and confessor shearwall can provide rigidity and strength by limiting the movement of the structure. In addition, the placement of stiffener systems in the right locations can also increase the rigidity of the building structure. This study aims to compare the effectiveness of structural behavior using a stiffener system based on the value of the fundamental period (T), the base shear force (V), the drift between stories (?x). In this research using a steel structure model that functions as an office building with a height of 10 levels, one variation of the model without stiffeners and four models with stiffeners, with two variations of the position of the stiffeners, namely in the middle and on the edge of the structure. The results of this study indicate that the addition of a stiffener system can increase the rigidity of the structure. The most effective structural model is found in the structural model with stiffeners shearwall the stiffener position in the middle which has a fundamental period value in the X and Y directions of 17.67% and 18.32% is better than the other models. For the base shear force values in the X and Y directions are 0.95% and 0.95% smaller than the other models. The deviation values between floor levels in the X and Y directions are 9.67% and 34.17% better than the other models. Meanwhile, the inefficient structural model is found in the structural model with stiffeners bracing on the edge which has a fundamental period value in the X and Y directions of 8.96% and 9.32% which is no better than the other models. For the base shear force values in the X and Y directions are 18.02% and 18.02% greater than the other models. The deviation values between floor levels in the X and Y directions are 1.69% and 13.15%, not better than the other models. So in this study it can be concluded that the stiffener system with a position in the middle is better than the position on the edge.
{"title":"Comparative Study of Strengthened Steel Structure Behavior Using Bracing and Shearwall","authors":"Khairullah Yusuf, F. Fasdarsyah, Nura Usrina, M. Fauzan, Rahmi Nurahim","doi":"10.52088/ijesty.v3i2.456","DOIUrl":"https://doi.org/10.52088/ijesty.v3i2.456","url":null,"abstract":"Multi-storey buildings are very susceptible to lateral forces, so reinforcement is needed to stiffen the building by adding a system of stiffeners to the building structure. In steel building structures, the system of stiffeners bracing and confessor shearwall can provide rigidity and strength by limiting the movement of the structure. In addition, the placement of stiffener systems in the right locations can also increase the rigidity of the building structure. This study aims to compare the effectiveness of structural behavior using a stiffener system based on the value of the fundamental period (T), the base shear force (V), the drift between stories (?x). In this research using a steel structure model that functions as an office building with a height of 10 levels, one variation of the model without stiffeners and four models with stiffeners, with two variations of the position of the stiffeners, namely in the middle and on the edge of the structure. The results of this study indicate that the addition of a stiffener system can increase the rigidity of the structure. The most effective structural model is found in the structural model with stiffeners shearwall the stiffener position in the middle which has a fundamental period value in the X and Y directions of 17.67% and 18.32% is better than the other models. For the base shear force values in the X and Y directions are 0.95% and 0.95% smaller than the other models. The deviation values between floor levels in the X and Y directions are 9.67% and 34.17% better than the other models. Meanwhile, the inefficient structural model is found in the structural model with stiffeners bracing on the edge which has a fundamental period value in the X and Y directions of 8.96% and 9.32% which is no better than the other models. For the base shear force values in the X and Y directions are 18.02% and 18.02% greater than the other models. The deviation values between floor levels in the X and Y directions are 1.69% and 13.15%, not better than the other models. So in this study it can be concluded that the stiffener system with a position in the middle is better than the position on the edge.","PeriodicalId":14149,"journal":{"name":"International Journal of Engineering, Science and Information Technology","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90638131","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}
Pub Date : 2023-07-02DOI: 10.52088/ijesty.v3i2.448
R. Syahputra, M. Sayuti, F. Fatimah, Sri Mutia
Paper is generally made of cellulose fibers derived from wood raw materials. Increased demand for production will have an impact on forest exploitation which can lead to environmental stability. Alternative natural fibers containing cellulose fiber are biomass waste such as Galangal Stems (Alpinia Galanga), Pineapple Leaves (Ananas Cosmosus), Banana Stems (Musa Paradisiaca), and others. The use of natural fibers can reduce the exploitation of wood as a raw material for paper. The purpose of this study was to determine the effect of natural fibers consisting of galangal stems, pineapple leaves, banana contains, and waste paper on the tensile strength of paper using ANOVA. The ratio of the percentage of fiber passed is galangal stems 50:10 and 50:40, pineapple leaves 50:10 and 50:40, banana contains 50:10 and 50:40, and waste paper 100% or without comparison. Tensile strength was carried out according to ASTM-D638, then data processing was carried out using the One Way ANOVA method. The results showed that the highest tensile strength value of banana stem paper and waste paper with a ratio of 50:10 was obtained at 7.04262 MPa resulting in the best tensile strength compared to other fibers. Factors that affect the tensile strength are the length of the fiber, and the bonds between the fibers are related to the fiber content. The results of this study concluded that the greater the number of material components in the manufacture of recycled paper, the greater the tensile strength of the report produced.
{"title":"The Effect of Natural Fiber Percentage on the Tensile Strength of Paper Using ANOVA","authors":"R. Syahputra, M. Sayuti, F. Fatimah, Sri Mutia","doi":"10.52088/ijesty.v3i2.448","DOIUrl":"https://doi.org/10.52088/ijesty.v3i2.448","url":null,"abstract":"Paper is generally made of cellulose fibers derived from wood raw materials. Increased demand for production will have an impact on forest exploitation which can lead to environmental stability. Alternative natural fibers containing cellulose fiber are biomass waste such as Galangal Stems (Alpinia Galanga), Pineapple Leaves (Ananas Cosmosus), Banana Stems (Musa Paradisiaca), and others. The use of natural fibers can reduce the exploitation of wood as a raw material for paper. The purpose of this study was to determine the effect of natural fibers consisting of galangal stems, pineapple leaves, banana contains, and waste paper on the tensile strength of paper using ANOVA. The ratio of the percentage of fiber passed is galangal stems 50:10 and 50:40, pineapple leaves 50:10 and 50:40, banana contains 50:10 and 50:40, and waste paper 100% or without comparison. Tensile strength was carried out according to ASTM-D638, then data processing was carried out using the One Way ANOVA method. The results showed that the highest tensile strength value of banana stem paper and waste paper with a ratio of 50:10 was obtained at 7.04262 MPa resulting in the best tensile strength compared to other fibers. Factors that affect the tensile strength are the length of the fiber, and the bonds between the fibers are related to the fiber content. The results of this study concluded that the greater the number of material components in the manufacture of recycled paper, the greater the tensile strength of the report produced.","PeriodicalId":14149,"journal":{"name":"International Journal of Engineering, Science and Information Technology","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80794506","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}
Pub Date : 2023-06-24DOI: 10.52088/ijesty.v3i2.447
S. Suryati, Rizka Mulyawan, Sulhatun Sulhatun, Muhammad Muhammad, Nikmat Wanda
This study aims to analyze the processing of chitosan-pectin biocomposite hydrogel with the addition of citric acid to improve the quality of the biocomposite for primary wound dressing applications. The method is printing the biopolymer solution in a glass mold, then drying at 50oC. Chitosan 90.2% DD and pectin dissolved in 1% acetic acid with a ratio (w/w) of 50:50. The two ingredients were mixed using a magnetic stirrer at room temperature for 30 minutes until completely dissolved, then added citric acid crosslinking agent with various concentrations of 2,4, 6,8,10 (%). The test results for the characteristics of the chitosan-pectin-acid biocomposite Citrate obtained the best thickness in the composition variation (50:50:8) of 0.31 mm. The analysis results of the best absorption of the chitosan-pectin-citric acid biocomposite on the composition variation (50:50:6) were 185%. In the swelling analysis of the chitosan-pectin-citric acid biocomposite, the variation in composition (50:50:10) was 403%. The tensile strength test results of the chitosan-pectin-citric acid biocomposite decreased with the addition of citric acid, the best obtained was 20.76 MPa, and the best elongation was 76.0%. Test results for the functional group of the chitosan-pectin-CaCl2 biocomposite for the presence of O-H, C-H, N-H bonds in the fact of O-H, C-H, N-H bonds at a wavelength of 4000-2500 cm-1, C=O, C=N, C=C at a wavelength of 2000 -1500, and the specific absorption of the chitosan-pectin-citric acid biocomposite 400-1400 cm-1 indicates that the resulting membrane tends to be polar, hydrophilic and environmentally friendly because it can be degraded. Based on the expected test results, it was shown that the chitosan-pectin-CaCl2 biocomposite has the potential to be applied as an ideal primary wound dressing for wound healing and protection.
{"title":"Synthesis and Characterization of Chitosan-Pectin-Citric Acid-Based Hydrogels for Biomedical Applications (Primary Wound Dressings)","authors":"S. Suryati, Rizka Mulyawan, Sulhatun Sulhatun, Muhammad Muhammad, Nikmat Wanda","doi":"10.52088/ijesty.v3i2.447","DOIUrl":"https://doi.org/10.52088/ijesty.v3i2.447","url":null,"abstract":"This study aims to analyze the processing of chitosan-pectin biocomposite hydrogel with the addition of citric acid to improve the quality of the biocomposite for primary wound dressing applications. The method is printing the biopolymer solution in a glass mold, then drying at 50oC. Chitosan 90.2% DD and pectin dissolved in 1% acetic acid with a ratio (w/w) of 50:50. The two ingredients were mixed using a magnetic stirrer at room temperature for 30 minutes until completely dissolved, then added citric acid crosslinking agent with various concentrations of 2,4, 6,8,10 (%). The test results for the characteristics of the chitosan-pectin-acid biocomposite Citrate obtained the best thickness in the composition variation (50:50:8) of 0.31 mm. The analysis results of the best absorption of the chitosan-pectin-citric acid biocomposite on the composition variation (50:50:6) were 185%. In the swelling analysis of the chitosan-pectin-citric acid biocomposite, the variation in composition (50:50:10) was 403%. The tensile strength test results of the chitosan-pectin-citric acid biocomposite decreased with the addition of citric acid, the best obtained was 20.76 MPa, and the best elongation was 76.0%. Test results for the functional group of the chitosan-pectin-CaCl2 biocomposite for the presence of O-H, C-H, N-H bonds in the fact of O-H, C-H, N-H bonds at a wavelength of 4000-2500 cm-1, C=O, C=N, C=C at a wavelength of 2000 -1500, and the specific absorption of the chitosan-pectin-citric acid biocomposite 400-1400 cm-1 indicates that the resulting membrane tends to be polar, hydrophilic and environmentally friendly because it can be degraded. Based on the expected test results, it was shown that the chitosan-pectin-CaCl2 biocomposite has the potential to be applied as an ideal primary wound dressing for wound healing and protection.","PeriodicalId":14149,"journal":{"name":"International Journal of Engineering, Science and Information Technology","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87232354","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}
Pub Date : 2023-06-14DOI: 10.52088/ijesty.v3i2.445
Amri Amri
One of the factors that affect employee performance is workload. If employees are given too much work, problems will arise. For example, some representatives have too high responsibilities ( overloaded ), while other workers have small responsibilities ( underloaded ). This kind of problem also occurs at PT. XZY, so it is essential to research the status of responsibility, which can then be used to design the Number of employees. The workload of each station is calculated using the Full Time Equivalent (FTE) method, which converts workload hours into the Number of people needed to complete a particular task. From the results of the review, it was found that there were deviations in responsibility at five workstations where three stations had overloaded workloads or values between 1.28 found at the wedding, cutting, and packing stations. A further two stations have standard work with values 1-1.28 found at co-gas filling stations and packaging and vacuum. The findings show that 18 employees are the ideal workforce. Changing the composition of the Number of workers according to the calculation of the optimal Number of workers can improve employee performance. The manuscript should contain an abstract. The abstract should be self-contained and citation-free and should not exceed 250 words. The abstract should state the work's purpose, approach, results, and conclusions. The author should assume that the reader has some knowledge of the subject but has not read the paper. Thus, the abstract should be intelligible and complete (no numerical references); it should not cite figures, tables, or sections of the paper. The abstract should be written using the third person instead of the first person.
{"title":"Workforce Design And Employee Workload Using The Full-Time Equivalent Method At PT XZY","authors":"Amri Amri","doi":"10.52088/ijesty.v3i2.445","DOIUrl":"https://doi.org/10.52088/ijesty.v3i2.445","url":null,"abstract":"One of the factors that affect employee performance is workload. If employees are given too much work, problems will arise. For example, some representatives have too high responsibilities ( overloaded ), while other workers have small responsibilities ( underloaded ). This kind of problem also occurs at PT. XZY, so it is essential to research the status of responsibility, which can then be used to design the Number of employees. The workload of each station is calculated using the Full Time Equivalent (FTE) method, which converts workload hours into the Number of people needed to complete a particular task. From the results of the review, it was found that there were deviations in responsibility at five workstations where three stations had overloaded workloads or values between 1.28 found at the wedding, cutting, and packing stations. A further two stations have standard work with values 1-1.28 found at co-gas filling stations and packaging and vacuum. The findings show that 18 employees are the ideal workforce. Changing the composition of the Number of workers according to the calculation of the optimal Number of workers can improve employee performance. The manuscript should contain an abstract. The abstract should be self-contained and citation-free and should not exceed 250 words. The abstract should state the work's purpose, approach, results, and conclusions. The author should assume that the reader has some knowledge of the subject but has not read the paper. Thus, the abstract should be intelligible and complete (no numerical references); it should not cite figures, tables, or sections of the paper. The abstract should be written using the third person instead of the first person.","PeriodicalId":14149,"journal":{"name":"International Journal of Engineering, Science and Information Technology","volume":"119 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90773196","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}
Pub Date : 2023-06-05DOI: 10.52088/ijesty.v3i2.444
R. Refianti, Faradilla Mahardi
The development of digital music, especially in genre classification has helped in the ease of studying and searching for a song. There are many ways that can be used to classify the songs/music into genres. Deep Learning is one of the Machine Learning implementation methods that can be used to classify the genre of music. The author managed to create a deep learning-based program using the MLP model with two extraction features, Chroma Feature and MFCC which can classify song/ music genres. Pre-processing of the song is done to take the features of the existing value then the value will be incorporated into the model to be trained and tested. The model was trained and tested with data of 3000 songs which were divided into 10 genres. The model was also tested using the Confusion Matrix with 600 songs of the total available data. The models with Chroma Features as extraction features have an accuracy rate of 53 %, while the MFCC extraction features have an accuracy rate of 80.2 %.
{"title":"Comparison of Music Genre Classification Results Using Multilayer Perceptron With Chroma Feature and Mel Frequency Cepstral Coefficients Extraction Features","authors":"R. Refianti, Faradilla Mahardi","doi":"10.52088/ijesty.v3i2.444","DOIUrl":"https://doi.org/10.52088/ijesty.v3i2.444","url":null,"abstract":"The development of digital music, especially in genre classification has helped in the ease of studying and searching for a song. There are many ways that can be used to classify the songs/music into genres. Deep Learning is one of the Machine Learning implementation methods that can be used to classify the genre of music. The author managed to create a deep learning-based program using the MLP model with two extraction features, Chroma Feature and MFCC which can classify song/ music genres. Pre-processing of the song is done to take the features of the existing value then the value will be incorporated into the model to be trained and tested. The model was trained and tested with data of 3000 songs which were divided into 10 genres. The model was also tested using the Confusion Matrix with 600 songs of the total available data. The models with Chroma Features as extraction features have an accuracy rate of 53 %, while the MFCC extraction features have an accuracy rate of 80.2 %.","PeriodicalId":14149,"journal":{"name":"International Journal of Engineering, Science and Information Technology","volume":"18 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72560987","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}
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