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Tag: universitas digital

  • The Key Success Factor For Implementation

    Smart Campus Based Cloud Computing

    Authors: Muhammad Encep; Martin Roestamy; Irman Suherman; Hilmy Aliy Andra Putra; Senny Luckyardi

    DOI: 10.1109/INCITEST64888.2024.11121420

    Abstract

    Cloud Computing is very helpful for companies or organizations because it does not need to provide physical infrastructure (data center, processing power, storage, to the application) to be able to have a system, everything is provided virtually. Very high dependence on the use of information and communication technology (ICT), as well as the need for cooperative, collaborative learning services and can increase learning time, is an evaluation material to realize needs by integrating technology that is becoming the current trend, where the success of higher education utilizing ICT is known as the term smart campus. The Roadmap for Cloud Computing Adoption (ROCCA), which integrates the factors that are important for adopting cloud computing in businesses or organizations and goes through five stages (phases)-analysis, planning, adoption, migration, and management-is the adoption model that is used as a reference. The research’s findings in the form of suggested tactical actions to streamline and quicken the deployment of cloud computing infrastructure in order to facilitate the creation of a smart campus in a university setting. © 2024 IEEE.

    Author keywords

    cloud computing; higher education; roadmap for cloud computing adoption (ROCCA); smart campus

    Indexed keywords

    Engineering controlled terms

    Collaborative learning; Digital storage; Education computing; Engineering education; Information use

    Engineering uncontrolled terms

    Cloud-computing; Datacenter; High educations; Information and Communication Technologies; Key success factors; Processing power; Roadmap; Roadmap for cloud computing adoption; Smart campus

    Engineering main heading

    Cloud computing

    This article can be accessed at https://www.scopus.com/pages/publications/105015600015

  • The Key Success Factor For Implementation

    The Key Success Factor For Implementation

    Smart Campus Based Cloud Computing

    Authors: Muhammad Encep; Martin Roestamy; Irman Suherman; Hilmy Aliy Andra Putra; Senny Luckyardi

    DOI: 10.1109/INCITEST64888.2024.11121420

    Abstract

    Cloud Computing is very helpful for companies or organizations because it does not need to provide physical infrastructure (data center, processing power, storage, to the application) to be able to have a system, everything is provided virtually. Very high dependence on the use of information and communication technology (ICT), as well as the need for cooperative, collaborative learning services and can increase learning time, is an evaluation material to realize needs by integrating technology that is becoming the current trend, where the success of higher education utilizing ICT is known as the term smart campus. The Roadmap for Cloud Computing Adoption (ROCCA), which integrates the factors that are important for adopting cloud computing in businesses or organizations and goes through five stages (phases)-analysis, planning, adoption, migration, and management-is the adoption model that is used as a reference. The research’s findings in the form of suggested tactical actions to streamline and quicken the deployment of cloud computing infrastructure in order to facilitate the creation of a smart campus in a university setting. © 2024 IEEE.

    Author keywords

    cloud computing; higher education; roadmap for cloud computing adoption (ROCCA); smart campus

    Indexed keywords

    Engineering controlled terms

    Collaborative learning; Digital storage; Education computing; Engineering education; Information use

    Engineering uncontrolled terms

    Cloud-computing; Datacenter; High educations; Information and Communication Technologies; Key success factors; Processing power; Roadmap; Roadmap for cloud computing adoption; Smart campus

    Engineering main heading

    Cloud computing

    This article can be accessed at https://www.scopus.com/pages/publications/105015600015

  • Web-Based Information System of Mail Archiving

    Authors: Rizky Jumansyah, Nizar Rabbi Radilya, Eddy Soeryanto Soegoto, Brandon Nathanael Meliala

    DOI: 10.1109/INCITEST64888.2024.11121430

    Abstract

    Archives have an important role so that administrative processes in the company can run effectively and efficiently. The process of finding and saving documents will not run well and create difficulties that can hinder the work process if the archives are not running optimally. The research aims at creating a web-based filing system that can help and prevent a very long process of processing the required documents. Data collection methods used in this research are interviews, observation, and documents. The results show that this system can help support the process of filing letters at Kesbangpol Kutai Barat. This study concludes that a web-based mail archiving information system can help and simplify the process of storing, searching for letters, so they are not easily damaged and lost. This research is expected to improve the performance of human resources. © 2024 IEEE.

    Author keywords

    administrative processes; information system; web-based

    This article can be accessed at https://www.scopus.com/pages/publications/105015815046

  • Enhancing Aspect Detection Using BLSTM and Random Oversampling in Marketplace Application Review

    Authors: Nelly Indriani Widiastuti; Bagus Perdana Yusuf; Kania Evita Dewi

    DOI: 10.1109/INCITEST59455.2023.10396931

    Abstract

    Aspect-based sentiment Analysis (ABSA) has been contributing to a more nuanced understanding of sentiment-related issues and offering enhanced opportunities for sentiment analysis. The number of aspects in data sets are often unbalanced. This causes results that tend towards the majority class and ignore the minority class This research uses Bi-LSTM to classify the aspects and sentiments because Bi-LSTM is able to handle problems in LSTM. The primary objective of this research was to assess the efficacy of the Bidirectional Long Short-Term Memory method in the context of Aspect-Based Sentiment Analysis applied to reviews of Marketplace applications and common problems in machine learning in unbalanced datasets. The preprocessing of input data involved word embedding through Word2Vec Continuous Bag of Words (CBOW). Primarily, the training dataset encompassed 2250 instances, while the test dataset comprised 750. The evaluation enclosed a comparative analysis involving the proposed method (Bi-LSTM+CBOW+ROS), on Bi-LSTM+CBOW, Bi- LSTM+CBOW+RUS and Bi-LSTM+CBOW+SMOTE. The test results show that the proposed method is superior to all comparison methods. Bi-LSTM+CBOW+ROS produces the highest accuracy, namely the usability aspect of 92.40%, the maximum precision is 98.03%, the maximum recall is 100% and the maximum f1-score is 98.68%. The Usability aspect got the best results for all the methods tested. © 2023 IEEE.

    Author keywords

    Aspect-based sentiment analysis; Bidirectional Long Short-term Memory; Random Oversampling; Word2Vec CBOW

    This article can be accessed at: https://www.scopus.com/pages/publications/85185201670

  • Designing High School Academic Information System Based on Android

    Authors: Agus Supandi Soegoto ; Yudistira Soegoto ; D S Soeikromo ; Candra Herdiana ; Seka Diasnoriga Koswara ; Mamed Seonggono Adji ; Agis Abhi Rafdhi ; Muhammad Nizar Nur Ikhsan

    DOI: 10.1109/INCITEST64888.2024.11121432

    Abstract

    This research aims to design mobile application for student academic development that can assist parents in monitoring their children. This research used a descriptive method. This android application is designed with an objectoriented approach, using the Prototype method. Then this application is made using Android Studio software, using the Java programming language, and the database using firebase. The results showed that the parents of students had difficulty in monitoring the academic development of their children. The parents of students can only see their children’s academic development when the report cards are distributed. An academic information system’s existence makes it easier for students’ parents to monitor their children’s academic development. © 2024 IEEE.

    Author keywords

    Android; high school academic; information system

    Indexed keywords

    Engineering controlled terms

    Application programs; Information systems; Information use; Mobile applications; Students

    Engineering uncontrolled terms

    Android; Android applications; High school academic; Higher School; Java programming; Mobile applications; Object oriented approach; Report cards

    Engineering main heading

    Android (operating system)

    This article can be accessed at https://www.scopus.com/pages/publications/105015859732

  • Designing High School Academic Information System Based on Android

    Authors: Agus Supandi Soegoto ; Yudistira Soegoto ; D S Soeikromo ; Candra Herdiana ; Seka Diasnoriga Koswara ; Mamed Seonggono Adji ; Agis Abhi Rafdhi ; Muhammad Nizar Nur Ikhsan

    DOI: 10.1109/INCITEST64888.2024.11121432

    Abstract

    This research aims to design mobile application for student academic development that can assist parents in monitoring their children. This research used a descriptive method. This android application is designed with an objectoriented approach, using the Prototype method. Then this application is made using Android Studio software, using the Java programming language, and the database using firebase. The results showed that the parents of students had difficulty in monitoring the academic development of their children. The parents of students can only see their children’s academic development when the report cards are distributed. An academic information system’s existence makes it easier for students’ parents to monitor their children’s academic development. © 2024 IEEE.

    Author keywords

    Android; high school academic; information system

    Indexed keywords

    Engineering controlled terms

    Application programs; Information systems; Information use; Mobile applications; Students

    Engineering uncontrolled terms

    Android; Android applications; High school academic; Higher School; Java programming; Mobile applications; Object oriented approach; Report cards

    Engineering main heading

    Android (operating system)

    This article can be accessed at https://www.scopus.com/pages/publications/105015859732

  • Design and Implementation of Virtual Laboratory Infrastructure for Indonesia Skill Competition using Cloud Computing

    Authors: Angga Friyanto; Susmini Indriani Lestariningati

    DOI: 10.1109/INCITEST59455.2023.10397061

    Abstract

    Indonesia Skill Competition, also known as “Lomba Kompetensi Siswa (LKS)”, is a vocational student skill competition program for students in 10th-12th grade. Students competes in a variety of competition categories. In the 2020 to 2022 academic year, due to the COVID-19 Pandemic, Committee designed an innovative and novel IT Network System Administration using Cloud Computing rather than cancelling the National Competition. The purpose of this paper is to show how to designed, implemented Virtual Laboratory using Cloud implementation. Competitor from their respective regions is connected via the Internet with Virtual Private Network access to Computer and Server Infrastructure that has been prepared by the committee according to the needs of the Test Project. During the competition, the competitor made configurations or settings directly on all servers and computers in Cloud Computing. Thus, even though the competition is held from their respective provinces, they can still maintain honesty and fairness because the competitor completes their work on a centralized cloud infrastructure under the supervision of the central committee. © 2023 IEEE.

    Author keywords

    Cloud Computing; IaaS; Virtual Lab

    This article can be accessed at: https://www.scopus.com/pages/publications/85185199477

  • Utilization of Context Aware System: Enhancing Book Selection 

    Recommendations in Smart Libraries

    Authors: Hanhan Maulaa ; Ridwan Caesarahman Julian ; Hideaki Kanai ; Richi Dwi Agustia

    DOI: 10.1109/INCITEST64888.2024.11121493

    Abstract

    This study aims to utilize a context-aware system to improve book recommendations in a smart digital library. The system is expected to help library visitors in choosing books. This study provides book recommendations based on visitor preferences. This study has four main stages. The first stage is data collection, done by recording all the books in the library. The second stage is to classify books and group them into certain categories. The third stage is to determine book recommendations. The last stage is testing and drawing conclusions. This study uses content-based filtering and makes recommendations using the term frequency-inverse document frequency (TF-IDF) algorithm. With a context-aware system, Smart Libraries can recommend readings according to user preferences. This study conducted testing with two methods. The first method is system testing on the developer side. The second test is the user acceptance test. Based on the test results, The system can help users get book recommendations according to user preferences. This algorithm is quite effective in providing book recommendations in the library; The system can help optimize access to the book in library; and This system can make managing books that suit users in the library easier and more effective. © 2024 IEEE.

    Author keywords

    content-based filtering; context-aware system; recommendation; smart library; TF-IDF algorithm

    Indexed keywords

    Engineering controlled terms

    Digital libraries; Inverse problems; Libraries; Recommender systems

    Engineering uncontrolled terms

    Book selections; Content based filtering; Context-aware systems; Data collection; Frequency algorithms; Recommendation; Smart library; Term frequency-inverse document frequency algorithm; Term frequencyinverse document frequency (TF-IDF); User’s preferences

    Engineering main heading

    Acceptance tests

    This article can be accessed at https://www.scopus.com/pages/publications/105015806858

  • Structured Methods in Analysis and Design for Motor Rental Information Systems

    Authors: Adi Rachmanto, Putri Melissa

    DOI: 10.1109/INCITEST64888.2024.11121475

    Abstract

    Operational Management: This sector and its operations face the challenge of professional management leading to how effective its services. The study is analyzing and designing a system information of motorbike lending. Our research method: qualitative descriptive data gathered through observation and interview with motorbike rental owners in Ubud, Bali. The development of a system must adhere to a methodology to ensure all plans are aligned with the business. The study showed that the application of an information system can enhance material handling, ordering process and vehicle safety. Meaning, more productivity, less errors and higher customer satisfaction. By maximizing the utilization of information technology in forecasting business processes, then your motorbike rental industry can further enhance its own competitiveness and bring a positive impact on the operation, also it may continue to help improving with all these benefits. © 2024 IEEE.

    Keywords: car rental; front desk; information systems; structured methods

    This article can be accessed at https://www.scopus.com/pages/publications/105015875528

  • Comparative Study of Model Efficiency for Sentiment Analysis on BRImo Reviews

    Authors: Ma’Shum Abdul Jabbar ; Martin Roestamy ; Himmatul Miftah ; Irman Suherman ; Muhammad Encep ; Bobi Kurniawan Soegoto

    DOI: 10.1109/INCITEST64888.2024.11121469

    Abstract

    This study aims to overcome the challenges in selecting the most efficient machine learning model to analyze user sentiment towards the BRImo application on the Google Play Store. User review data on BRImo, an application owned by PT Bank Rakyat Indonesia, was collected through web scraping techniques from a total of 1.55 million reviews, and then 150,000 relevant samples were used. The results showed that Support Vector Machine (SVM) had the highest accuracy rate (87.13%) but required the longest training time (1310.70 seconds). In contrast, Naive Bayes had the shortest training time (0.59 seconds) but the lowest accuracy (75.00%). Logistic Regression emerged as a model that provides a balance between high accuracy and fast execution time. The contribution of this study is to provide a comprehensive guide to the efficiency and reliability of models in sentiment analysis, which can be used to assist in selecting the right model in new user review analysis. © 2024 IEEE.

    Author keywords

    BRImo; machine learning; sentiment analysis; web scraping

    Indexed keywords

    Engineering controlled terms

    Barium compounds; Efficiency; Intelligent systems; Learning systems; Logistic regression; Reliability analysis; Reviews; Support vector regression

    Engineering uncontrolled terms

    BRImo; Comparatives studies; High-accuracy; Machine learning models; Machine-learning; Model efficiency; Sentiment analysis; Training time; User reviews; Web scrapings

    Engineering main heading

    Sentiment analysis

    This article can be accessed at https://www.scopus.com/pages/publications/105015736072