– This study presents an implementation of automated deployment using Terraform on Google Cloud Compute VM. The aim is to streamline the deployment process and increase efficiency in the deployment of applications. The study involves setting up a cloud environment on Google Cloud, configuring the Terraform code to deploy the necessary resources, and automating the deployment process. The results of the study indicate that using Terraform for deployment automation on Google Cloud Compute VM significantly reduces the deployment time and effort. The implementation of automation deployment also provides benefits such as improved consistency, increased productivity, and reduced errors in the deployment process. From the results of the tests that have been carried out, the author can create 4 VM instances (servers) in Google Cloud at one time with the configured code, the number of VMs can be set as much as needed with specifications that can be set as needed, can also delete all VM that has been created at one time .
{"title":"Implementasi Automation Deployment pada Google Cloud Compute VM menggunakan Terraform","authors":"Debi Gustian, Yuli Fitrisia, Wenda Novayani, Sugeng Purwantoro E.S.G.S","doi":"10.35314/isi.v8i1.3095","DOIUrl":"https://doi.org/10.35314/isi.v8i1.3095","url":null,"abstract":"– This study presents an implementation of automated deployment using Terraform on Google Cloud Compute VM. The aim is to streamline the deployment process and increase efficiency in the deployment of applications. The study involves setting up a cloud environment on Google Cloud, configuring the Terraform code to deploy the necessary resources, and automating the deployment process. The results of the study indicate that using Terraform for deployment automation on Google Cloud Compute VM significantly reduces the deployment time and effort. The implementation of automation deployment also provides benefits such as improved consistency, increased productivity, and reduced errors in the deployment process. From the results of the tests that have been carried out, the author can create 4 VM instances (servers) in Google Cloud at one time with the configured code, the number of VMs can be set as much as needed with specifications that can be set as needed, can also delete all VM that has been created at one time .","PeriodicalId":354905,"journal":{"name":"INOVTEK Polbeng - Seri Informatika","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128442724","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}
- The covid-19 pandemic that swept across the globe had adverse effects in many areas. One of the most affected areas is education in Indonesia. The online learning model became the only option at the time, which had a negative impact on the quality of education in Indonesia. As time went on, conditions are getting better, but there was still a threat of covid-19. In early 2022 governments began to adopt face-to-face or offline learning that attracted opinions on social media. The opinions that are widely written on social media need to be prepared because they could be input to the government. Clustering using the k-means algorithm with the elbow method as its optimizer in determining the best cluster number is one of the opinions processing options on social media for measuring and accounting. Data is treated with two approaches: with and without stemming . Applying the elbow method to the k-means algorithm produces a performance of the clustering model with a DBI value of 0.003 with 4 clusters, and a value of SSE 0.331, for data without stemming . On data with treatment using stemming , it has 3 cluster numbers with a value of DBI at 0.003 and SSE at 0426.
{"title":"Klasterisasi Menggunakan Algoritma K-Means dan Elbow pada Opini Masyarakat Tentang Kebijakan Sekolah Luring Tahun 2022","authors":"Rahmawan Bagus Trianto, A. Nugroho, Eko Supriyadi","doi":"10.35314/isi.v8i1.2756","DOIUrl":"https://doi.org/10.35314/isi.v8i1.2756","url":null,"abstract":"- The covid-19 pandemic that swept across the globe had adverse effects in many areas. One of the most affected areas is education in Indonesia. The online learning model became the only option at the time, which had a negative impact on the quality of education in Indonesia. As time went on, conditions are getting better, but there was still a threat of covid-19. In early 2022 governments began to adopt face-to-face or offline learning that attracted opinions on social media. The opinions that are widely written on social media need to be prepared because they could be input to the government. Clustering using the k-means algorithm with the elbow method as its optimizer in determining the best cluster number is one of the opinions processing options on social media for measuring and accounting. Data is treated with two approaches: with and without stemming . Applying the elbow method to the k-means algorithm produces a performance of the clustering model with a DBI value of 0.003 with 4 clusters, and a value of SSE 0.331, for data without stemming . On data with treatment using stemming , it has 3 cluster numbers with a value of DBI at 0.003 and SSE at 0426.","PeriodicalId":354905,"journal":{"name":"INOVTEK Polbeng - Seri Informatika","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129926193","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}
Faisal Rahutomo, S. Sutrisno, Meiyanto Eko Sulistyo, Josaphat Tetuko Sri Sumantyo, Bambang Harjito
Abstrack - To make the right decisions and policies, university management often requires data. The problem that often arises is scattered data in various existing applications. To get the right point of view, it requires data analysts who master the situation broadly, including the business processes that occur in the organization and the various applications that run in it. People who can handle the problem are very limited or even non-existent, even though the need for data from management is increasingly. It can overcome these problems by building a data analytics system that works in a data warehouse. So that this paper proposes to study the design and implementation of academic and student data analytics applications. Utilization of existing data warehouses can be used as data visualization, data reporting, trend analytics, association analytics, group analytics, decision support systems, forecasting systems, and expert systems. The existing approach uses the Agile Scrum framework to get around time constraints and limited people. The test results show that this application can be built with this framework. A sizable application can be built within 1 month with 1 scrum master, 4 programmers and 2 tester-documentator.
{"title":"Pendekatan Agile Scrum pada Pengembangan Aplikasi Analitik Akademik dan Kemahasiswaan","authors":"Faisal Rahutomo, S. Sutrisno, Meiyanto Eko Sulistyo, Josaphat Tetuko Sri Sumantyo, Bambang Harjito","doi":"10.35314/isi.v7i2.2880","DOIUrl":"https://doi.org/10.35314/isi.v7i2.2880","url":null,"abstract":"Abstrack - To make the right decisions and policies, university management often requires data. The problem that often arises is scattered data in various existing applications. To get the right point of view, it requires data analysts who master the situation broadly, including the business processes that occur in the organization and the various applications that run in it. People who can handle the problem are very limited or even non-existent, even though the need for data from management is increasingly. It can overcome these problems by building a data analytics system that works in a data warehouse. So that this paper proposes to study the design and implementation of academic and student data analytics applications. Utilization of existing data warehouses can be used as data visualization, data reporting, trend analytics, association analytics, group analytics, decision support systems, forecasting systems, and expert systems. The existing approach uses the Agile Scrum framework to get around time constraints and limited people. The test results show that this application can be built with this framework. A sizable application can be built within 1 month with 1 scrum master, 4 programmers and 2 tester-documentator.","PeriodicalId":354905,"journal":{"name":"INOVTEK Polbeng - Seri Informatika","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128114542","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}
Abstrack - Book lending is the most important service in the library. So far, book borrowing data is often used as a statistical report, has not been analyzed further to find patterns/knowledge to deepen the insight of library managers. With the rapid growth of big data, social network analysis and community detection have been studied intensively by many researchers over the past few years. However, little research has been done on social network analysis and community detection of borrowing books at the library, and no one has even conducted a comparison analysis of community detection algorithms on book lending. In this paper, we propose an analysis of the library's book borrowing database using social network analysis and community detection methods. The purpose of this study is to find book clusters and borrower clusters by utilizing the best community detection method obtained. The research step begins with collecting data on borrowing books, constructing it into a bipartite graph model, projecting the bipartite graph into a book graph and a book borrowing graph. Then conduct experiments comparing several community detection algorithms for the two graphs, with evaluation metrics in the form of modularity, performance, coverage, density and entropy. The experimental results of Louvain's algorithm and Eva's algorithm have the best performance for book graphs and book borrowers. The application of community detection to the book graph obtained 16 clusters of books, while the book borrower graph obtained 21 clusters of book borrowers. The results of this clustering can be used as recommendations for library management in making library programs to increase the utility of books and increase user loyalty.
{"title":"Klasterisasi Buku dan Peminjam Buku di Perpustakaan dengan Metode Analisis Jejaring Sosial dan Deteksi Komunitas","authors":"T. Setiadi","doi":"10.35314/isi.v7i2.2780","DOIUrl":"https://doi.org/10.35314/isi.v7i2.2780","url":null,"abstract":"Abstrack - Book lending is the most important service in the library. So far, book borrowing data is often used as a statistical report, has not been analyzed further to find patterns/knowledge to deepen the insight of library managers. With the rapid growth of big data, social network analysis and community detection have been studied intensively by many researchers over the past few years. However, little research has been done on social network analysis and community detection of borrowing books at the library, and no one has even conducted a comparison analysis of community detection algorithms on book lending. In this paper, we propose an analysis of the library's book borrowing database using social network analysis and community detection methods. The purpose of this study is to find book clusters and borrower clusters by utilizing the best community detection method obtained. The research step begins with collecting data on borrowing books, constructing it into a bipartite graph model, projecting the bipartite graph into a book graph and a book borrowing graph. Then conduct experiments comparing several community detection algorithms for the two graphs, with evaluation metrics in the form of modularity, performance, coverage, density and entropy. The experimental results of Louvain's algorithm and Eva's algorithm have the best performance for book graphs and book borrowers. The application of community detection to the book graph obtained 16 clusters of books, while the book borrower graph obtained 21 clusters of book borrowers. The results of this clustering can be used as recommendations for library management in making library programs to increase the utility of books and increase user loyalty.","PeriodicalId":354905,"journal":{"name":"INOVTEK Polbeng - Seri Informatika","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134245225","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}
- The Academic Information System (SIMAK) of UIN Raden Fatah Palembang is a service information system provided by PUSTIPD (Center for Information Technology and Databases) to help Students and Lecturers, one of which is to view personal data, value data, KRS data. In implementing this SIMAK, there can be risks due to errors in implementing its use, one of which is system connection errors, damaged hardware, failed network, failed data backup, power failure, misuse of access rights, cybercrime. To minimize the effects of these threats can apply risk management that aims to overcome risks by anticipating losses that occur and implementing procedures that are able to minimize the occurrence of losses. With the management risk management of this information system, the author uses the Failure Mode and Effect Analysis (FMEA) method with a qualitative approach method. FMEA which is used to capture potential failures, risks and impacts is prioritized with a priority number called risk priority number (RPN). The results of this study show that there are 6 categories in the priority rpn value in SIMAK, namely, 1 very high category value, 3 high category values, 4 medium category values, 3 low category values, 6 very low category values and 1 category value with almost no failures.
- UIN Raden Fatah Palembang的学术信息系统(SIMAK)是由PUSTIPD(信息技术和数据库中心)为学生和讲师提供的服务信息系统，其中之一是查看个人数据，价值数据，KRS数据。在实施SIMAK时，由于实施过程中的错误，可能存在风险，其中之一是系统连接错误、硬件损坏、网络故障、数据备份失败、电源故障、访问权限滥用、网络犯罪。为了最大限度地减少这些威胁的影响，可以应用风险管理，旨在通过预测可能发生的损失和实施能够最大限度地减少损失发生的程序来克服风险。针对该信息系统的管理风险管理，笔者采用了失效模式与影响分析(FMEA)方法和定性方法。用于捕获潜在故障、风险和影响的FMEA用一个称为风险优先级号(RPN)的优先级编号进行优先级排序。本研究结果表明，SIMAK的优先级rpn值有6个类别，即1个非常高的类别值，3个高的类别值，4个中等的类别值，3个低的类别值，6个非常低的类别值和1个几乎没有故障的类别值。
{"title":"Analisa Manajemen Resiko Keamanan Pada Sistem Informasi Akademik (Simak) Uin Raden Fatah Palembang Menggunakan Metode Failure Mode And Effect Analysis (FMEA)","authors":"Yesi Ramayani","doi":"10.35314/isi.v7i2.2631","DOIUrl":"https://doi.org/10.35314/isi.v7i2.2631","url":null,"abstract":"- The Academic Information System (SIMAK) of UIN Raden Fatah Palembang is a service information system provided by PUSTIPD (Center for Information Technology and Databases) to help Students and Lecturers, one of which is to view personal data, value data, KRS data. In implementing this SIMAK, there can be risks due to errors in implementing its use, one of which is system connection errors, damaged hardware, failed network, failed data backup, power failure, misuse of access rights, cybercrime. To minimize the effects of these threats can apply risk management that aims to overcome risks by anticipating losses that occur and implementing procedures that are able to minimize the occurrence of losses. With the management risk management of this information system, the author uses the Failure Mode and Effect Analysis (FMEA) method with a qualitative approach method. FMEA which is used to capture potential failures, risks and impacts is prioritized with a priority number called risk priority number (RPN). The results of this study show that there are 6 categories in the priority rpn value in SIMAK, namely, 1 very high category value, 3 high category values, 4 medium category values, 3 low category values, 6 very low category values and 1 category value with almost no failures.","PeriodicalId":354905,"journal":{"name":"INOVTEK Polbeng - Seri Informatika","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127443777","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}
Perkembangan teknologi yang cepat menyebabkan kebutuhan penyimpanan data semakin berkembang. Salah satu untuk memperbesar kapasitas penyimpanannya dengan metode Clustered file system. Pada pengujian ini membandingkan kecepatan upload dan download file dan write/read file pada GlusterFS dan Ceph. Pengujian transfer file menggunakan file dengan ukuran 500MB, 10 kali pengujian, dan menggunakan aplikasi teracopy. Dari pengujian maka diperoleh hasil untuk upload file bahwa metode GlusterFS lebih cepat 11,5% daripada Ceph dengan rata-rata upload file GlusterFS lebih tinggi sebesar 3,57MB/s dan CephFS sebesar 3,20MB/s, hasil yang diperoleh untuk download file bahwa metode GlusterFS lebih cepat 11,3% daripada Ceph dengan rata-rata upload file GlusterFS lebih tinggi 4,13MB/s dan CephFS sebesar 3,71MB/s, hasil yang diperoleh untuk write file bahwa metode GlusterFS lebih cepat 106% daripada Ceph dengan perbandingan sebesar 11,34kB/s dan 8,05kB/s, untuk read file bahwa metode GlusterFS lebih cepat 37% daripada Ceph dengan perbandingan sebesar 3,10kB/s dan 2,25kB/s. Dari analisis tersebut bahwa metode GlusterFS lebih baik 100% dengan menggunakan 2 node yang masing-masing memiliki virtual disk yang dapat digabung dan mempercepat performancenya, sedangkan Ceph terbagi 3 node dimana 1 node digunakan sebagai MON yang berisikan penyimpanan metadata dan pool data yang memiliki proses lebih banyak sehingga mengakibatkan turunnya performance pada file system tersebut
{"title":"Perbandingan Kinerja Clustered File System pada Cloud Storage menggunakan GlusterFS dan Ceph","authors":"Sugeng Purwantoro E.S.G.S","doi":"10.35314/isi.v7i2.2753","DOIUrl":"https://doi.org/10.35314/isi.v7i2.2753","url":null,"abstract":"Perkembangan teknologi yang cepat menyebabkan kebutuhan penyimpanan data semakin berkembang. Salah satu untuk memperbesar kapasitas penyimpanannya dengan metode Clustered file system. Pada pengujian ini membandingkan kecepatan upload dan download file dan write/read file pada GlusterFS dan Ceph. Pengujian transfer file menggunakan file dengan ukuran 500MB, 10 kali pengujian, dan menggunakan aplikasi teracopy. Dari pengujian maka diperoleh hasil untuk upload file bahwa metode GlusterFS lebih cepat 11,5% daripada Ceph dengan rata-rata upload file GlusterFS lebih tinggi sebesar 3,57MB/s dan CephFS sebesar 3,20MB/s, hasil yang diperoleh untuk download file bahwa metode GlusterFS lebih cepat 11,3% daripada Ceph dengan rata-rata upload file GlusterFS lebih tinggi 4,13MB/s dan CephFS sebesar 3,71MB/s, hasil yang diperoleh untuk write file bahwa metode GlusterFS lebih cepat 106% daripada Ceph dengan perbandingan sebesar 11,34kB/s dan 8,05kB/s, untuk read file bahwa metode GlusterFS lebih cepat 37% daripada Ceph dengan perbandingan sebesar 3,10kB/s dan 2,25kB/s. Dari analisis tersebut bahwa metode GlusterFS lebih baik 100% dengan menggunakan 2 node yang masing-masing memiliki virtual disk yang dapat digabung dan mempercepat performancenya, sedangkan Ceph terbagi 3 node dimana 1 node digunakan sebagai MON yang berisikan penyimpanan metadata dan pool data yang memiliki proses lebih banyak sehingga mengakibatkan turunnya performance pada file system tersebut","PeriodicalId":354905,"journal":{"name":"INOVTEK Polbeng - Seri Informatika","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132483094","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}
Handrian Azhar, Muhamad Sadar, Lucky Lhaura Van FC, Pandu Pratama Putra
– Application of Documentation Method for Monitoring Interns’ Logbooks and Attendance at Politeknik Negeri Bengkalis is expected to provide solutions to existing problems so that internship activities can be implemented more effectively. The Unified Modeling Language (UML) and interface design were used in the development of this system. This is a web-based application and was developed using the PHP programming language, HTML, CSS, Javascript, and the MySQL database. The application was developed using the waterfall method, with the documentation method used for monitoring and the black box method for testing. The result of this study is a web application. The conclusion of the study is that in order to facilitate the process of monitoring interns in real time, an application which can store attendance data, logbooks, notes, and internship assessment results online is required.
{"title":"Penerapan Metode Dokumentasi Untuk Monitoring Logbook dan Presensi Mahasiswa Kerja Praktek di Politeknik Negeri Bengkalis","authors":"Handrian Azhar, Muhamad Sadar, Lucky Lhaura Van FC, Pandu Pratama Putra","doi":"10.35314/isi.v7i2.2595","DOIUrl":"https://doi.org/10.35314/isi.v7i2.2595","url":null,"abstract":"– Application of Documentation Method for Monitoring Interns’ Logbooks and Attendance at Politeknik Negeri Bengkalis is expected to provide solutions to existing problems so that internship activities can be implemented more effectively. The Unified Modeling Language (UML) and interface design were used in the development of this system. This is a web-based application and was developed using the PHP programming language, HTML, CSS, Javascript, and the MySQL database. The application was developed using the waterfall method, with the documentation method used for monitoring and the black box method for testing. The result of this study is a web application. The conclusion of the study is that in order to facilitate the process of monitoring interns in real time, an application which can store attendance data, logbooks, notes, and internship assessment results online is required.","PeriodicalId":354905,"journal":{"name":"INOVTEK Polbeng - Seri Informatika","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133387188","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}
Balita membutuhkan asupan gizi yang baik, oleh karena itu pemilihan menu makanan yang bergizi sangat penting untuk memaksimalkan pertumbuhan dan perkembangan pada balita. Kebutuhan energi pada balita yang dianjurkan untuk memenuhi Angka Kecukupan Gizi. Untuk membantu orang tua dalam menentukan kebutuhan energi pada balita dibutuhkan suatu sistem yang dapat membantu dalam menentukan menu makanan yang bergizi untuk balita. Tujuan dari penelitian ini adalah untuk merancang Sistem Pendukung Keputusan penentuan menu makanan balita dengan menerapkan perhitungan Metode Weight Product untuk menghasilkan keputusan terbaik. Hasil perhitungan berdasarkan Metode Weight Product diperoleh nilai terbesar yaitu 0,078 pada paket menu J, dengan kriteria yang digunakan yaitu 5 kriteria dan 15 paket menu. Sehingga paket menu J mendapatkan peringkat 1 dan merupakan paket menu terbaik yang diputuskan oleh sistem.
{"title":"Sistem Pendukung Keputusan Pemilihan Menu Makan untuk Balita Menggunakan Metode Weight Product","authors":"Esi putri Silmina, Tikaridha Hardiani","doi":"10.35314/isi.v7i2.2647","DOIUrl":"https://doi.org/10.35314/isi.v7i2.2647","url":null,"abstract":"Balita membutuhkan asupan gizi yang baik, oleh karena itu pemilihan menu makanan yang bergizi sangat penting untuk memaksimalkan pertumbuhan dan perkembangan pada balita. Kebutuhan energi pada balita yang dianjurkan untuk memenuhi Angka Kecukupan Gizi. Untuk membantu orang tua dalam menentukan kebutuhan energi pada balita dibutuhkan suatu sistem yang dapat membantu dalam menentukan menu makanan yang bergizi untuk balita. Tujuan dari penelitian ini adalah untuk merancang Sistem Pendukung Keputusan penentuan menu makanan balita dengan menerapkan perhitungan Metode Weight Product untuk menghasilkan keputusan terbaik. Hasil perhitungan berdasarkan Metode Weight Product diperoleh nilai terbesar yaitu 0,078 pada paket menu J, dengan kriteria yang digunakan yaitu 5 kriteria dan 15 paket menu. Sehingga paket menu J mendapatkan peringkat 1 dan merupakan paket menu terbaik yang diputuskan oleh sistem.","PeriodicalId":354905,"journal":{"name":"INOVTEK Polbeng - Seri Informatika","volume":"241 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133746869","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}
- Learning activities at SD Islam Plus Masyithoh that teachers apply tend to be conventional, as in the introduction of computer hardware. The learning requires teaching aids to improve students' understanding, but the limited facilities make it difficult for students to understand computer hardware. Augmented Reality technology can provide a solution by applying markers as targets to visualize computer hardware into 3D objects in the system using the Multimedia Development Life Cycle and Prototype software development methods. This method uses the black box testing method to develop multimedia software systems in testing the application. The results obtained from BlackBox testing show that all application features' functions can run well. Then usability testing with the System Usability Scale method. The data taken are 30 samples of questionnaire data that 4th-grade students have filled out. In the test obtained, the average value of SUS is 83.1. So it can interpretation that the application testing receives a grade of "B" with the predicate "Excellent", and the conclusion in the Acceptability Ranges category is "High", with a high range of user acceptance of the application.
-在SD Islam Plus masythoh，老师们采用的学习活动往往是传统的，比如引入计算机硬件。学习需要教学辅助来提高学生的理解能力，但是有限的设备使得学生很难理解计算机硬件。增强现实技术可以通过使用多媒体开发生命周期和原型软件开发方法，将标记作为目标，将计算机硬件可视化为系统中的3D对象，从而提供解决方案。该方法采用黑盒测试方法开发多媒体软件系统中的测试应用。BlackBox测试结果表明，应用程序的所有功能都能很好地运行。然后用系统可用性量表法进行可用性测试。选取的数据为30份四年级学生填写的问卷数据样本。在得到的测试中，SUS的平均值为83.1。因此可以解释，应用程序测试获得“B”级，谓词为“优秀”，可接受范围类别中的结论为“高”，用户接受该应用程序的范围较高。
{"title":"Implementasi Augmented Reality Media Pengenalan Hardware Dengan Metode Multimedia Development Life Cycle Dan Prototype","authors":"Melinia Dini Afrian, Pradana Ananda Raharja","doi":"10.35314/isi.v7i2.2633","DOIUrl":"https://doi.org/10.35314/isi.v7i2.2633","url":null,"abstract":"- Learning activities at SD Islam Plus Masyithoh that teachers apply tend to be conventional, as in the introduction of computer hardware. The learning requires teaching aids to improve students' understanding, but the limited facilities make it difficult for students to understand computer hardware. Augmented Reality technology can provide a solution by applying markers as targets to visualize computer hardware into 3D objects in the system using the Multimedia Development Life Cycle and Prototype software development methods. This method uses the black box testing method to develop multimedia software systems in testing the application. The results obtained from BlackBox testing show that all application features' functions can run well. Then usability testing with the System Usability Scale method. The data taken are 30 samples of questionnaire data that 4th-grade students have filled out. In the test obtained, the average value of SUS is 83.1. So it can interpretation that the application testing receives a grade of \"B\" with the predicate \"Excellent\", and the conclusion in the Acceptability Ranges category is \"High\", with a high range of user acceptance of the application.","PeriodicalId":354905,"journal":{"name":"INOVTEK Polbeng - Seri Informatika","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125892917","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}
- Data mining is a process of finding essential and unique information, as well as operational business management that requires knowledge to increase the effectiveness and efficiency of the company. CV. XYZ is a bicycle and motorcycle spare parts shop located in West Java since 1999 and has had a transaction management system since 2012. However, the system is only used for recording and archiving, which should be used more optimally to improve the quality of operational management. The management of the layout of goods is not well planned by CV. XYZ, which should be able to be analyzed with existing transaction data. Therefore, this study focuses on transaction analysis to determine the layout of goods using the a priori algorithm with a minimum support of 4% and a minimum confidence of 50%. The research produces 21 association rules that can be used as a priority product placement on the CV. XYZ with a matching percentage of 57.1% for the minimum support and confidence that has been tested.
{"title":"Analisis Data Transaksi untuk Penempatan Produk Prioritas Oli Motor Menggunakan Algoritma Apriori","authors":"Gigih Prima Subakti, Yessica Nataliani","doi":"10.35314/isi.v7i2.2684","DOIUrl":"https://doi.org/10.35314/isi.v7i2.2684","url":null,"abstract":"- Data mining is a process of finding essential and unique information, as well as operational business management that requires knowledge to increase the effectiveness and efficiency of the company. CV. XYZ is a bicycle and motorcycle spare parts shop located in West Java since 1999 and has had a transaction management system since 2012. However, the system is only used for recording and archiving, which should be used more optimally to improve the quality of operational management. The management of the layout of goods is not well planned by CV. XYZ, which should be able to be analyzed with existing transaction data. Therefore, this study focuses on transaction analysis to determine the layout of goods using the a priori algorithm with a minimum support of 4% and a minimum confidence of 50%. The research produces 21 association rules that can be used as a priority product placement on the CV. XYZ with a matching percentage of 57.1% for the minimum support and confidence that has been tested.","PeriodicalId":354905,"journal":{"name":"INOVTEK Polbeng - Seri Informatika","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128712379","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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