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  • Design and Development of Intelligent Tutoring System Model

    for Learning System in The Indonesian National Armed Forces

    Authors: Bobi Kurniawan ; Meyliana ; Harco Leslie Hendric Spits Warnars ; Bambang Suharjo

    DOI: 10.1109/INCITEST64888.2024.11121466

    Abstract:

    The purpose of this study is to develop and design an intelligent tutoring system (ITS) based on student personalization by considering learning styles and emotional conditions during the learning process in the Indonesian National Armed Forces environment. With a learning system that is personal and adaptive, it is expected to improve the quality of education provided to students in the Indonesian National Armed Forces environment. This study was formed from the identification of components and sub-components in the ITS model, the development of this ITS model takes into account the state and emotional conditions of students and evaluates the model’s performance. This project, it is expected to provide new knowledge or insights about the implementation of the Intelligent Tutoring System (ITS) in the field of military education and training and contribute significantly to the development of learning systems in the Indonesian National Armed Forces environment. © 2024 IEEE.

    Author Keywords:

    adaptive learning; artificial intelligence in education; Indonesian army learning system; intelligent tutoring system; learning personalization

    Indexed Keywords:

    Engineering controlled terms

    Computer aided instruction; Education computing; Intelligent systems; Learning systems; Teaching

    Engineering uncontrolled terms

    Adaptive learning; Armed forces; Artificial intelligence in education; Indonesian army learning system; Intelligent tutoring; Intelligent tutoring system; Learning personalization; Personalizations; System models; Tutoring system

    Engineering main heading

    Students

    This article can be accessed at https://www.scopus.com/pages/publications/105015865594?

  • Palm Oil Commodity Traceability System to Support the Implementation of EUDR Policies in Indonesia

    Author: Julian Chandra Wibawa ; Muhammad Eko Utomo ; Vita Harlan Bachtiar; Nizar Rabbi Radilya ; Rauf Fauzan

    DOI: 10.1109/INCITEST64888.2024.11121512

    Abstract

    The palm oil commodity traceability system allows for tracking the palm oil product trail from upstream to the end consumer. The aim of this research is to increase the added value of Indonesian palm oil products in the international market which is increasingly prioritizing sustainability. By meeting global requirements and standards, palm oil producers and exporters can access wider markets and increase the competitiveness of their products. This not only helps to avoid illegal land use and deforestation that are detrimental to the environment, but also supports efforts to preserve habitats and biodiversity that are often threatened by plantation expansion. The method applied in developing this system is the prototype method, which begins with needs analysis, followed by the design stage, development implementation, testing, and ends with the finalization stage. The output of this research is to produce a palm oil commodity traceability system to support the implementation of the EUDR policy in Indonesia. © 2024 IEEE.

    Author keywords

    deforestation; EUDR policy; palm oil; traceability

    Indexed keywords

    Engineering controlled terms

    Competition; Financial markets; International trade; Oil shale; Palmprint recognition; Sustainable development

    Engineering uncontrolled terms

    Added values; End consumers; EUDR policy; Indonesia; International markets; Need analysis; Oil producers; Oil product; Traceability; Traceability systems

    Engineering main heading

    Palm oil

    This article can be acessed at: https://www.scopus.com/pages/publications/105015798356

  • Decision Support System for Providing Indonesia Smart Card College Assistance Using the Weighted Product Method

    Authors: Abdul Majid Gaffar, Yeffry Handoko Putra

    DOI: 10.1109/INCITEST64888.2024.11121473

    Abstract

    Government programs that aim to provide assistance to underprivileged Indonesian children include the PIP or Smart Indonesia Programme. This PIP helps continue children’s education to college, this assistance is shown through ownership of the Indonesia Smart Card (KIP) Lecture. The provision of KIP Lecture assistance for underprivileged students is not all able to get this assistance, because the quota given is very limited, especially for private universities, so universities have difficulty in determining the worthiest recipients based on the applicable criteria, namely as many as 12 assessment criteria. The purpose of this research is to form a decision support system (SPK) using the Weighted Product method. Based on the results of Alpha testing, the results are 100% valid in accordance with the analysis and design made and based on the results of interviews, it is found that the SPK that has been built can facilitate and assist the BAAK section of Ichsan Gorontalo University in determining the provision of KIP Lecture assistance for students who are most deserving of receiving transparently, accountably and objectively so that this decision support system can be used. © 2024 IEEE.

    Author keywords

    decision support system; Ichsan Gorontalo University; Indonesia smart college card; weighted product

    This article can be accessed at https://www.scopus.com/pages/publications/105015872414

  • Development of Multimedia Applications Colonial War History in Indonesia

    as Interactive Learning Media For High School Students

    Authors: Diana Effendi ; Rani Puspita  Dhaniawaty ; Mufti Muhammad Pratadina ; Rahmat Hidayat ; Muhammad Alghani ; Bella Hardiyana

    DOI: 10.1109/INCITEST64888.2024.11121459

    Abstract:

    This research aims to build a multimedia-based learning application program for the history of a colonial war in Indonesia. The object of research was conducted at SMAN 24 Bandung, class XI as many as 8 classes. The problem faced at this time is that students get material on the history of war in Indonesia only by capitalizing on materials from books and or PowerPoint soft files as references. In delivering the material by the teacher only face to face in class, lecturing, holding question and answer sessions, and not having a variety of interactive learning media, learning history becomes less interesting. Multimedia is an innovative learning system that requires teachers to be more creative in combining multimedia elements such as text, images, sound, video, and animation to unite and achieve learning objectives. The method used in developing this application is the Multimedia Development Life Cycle (MDLC). In the alpha and beta testing stages, testing was carried out by 4 evaluators, namely learning material experts (vice principal), learning design experts and communication media experts from multimedia industry practitioners, and users represented by history teaching teachers. Three aspects are assessed, namely audio media, video media, and multimedia with a value > =3, multimedia applications are said to be suitable for use as learning aids. From the results of the evaluator’s assessment, the three aspects are obtained around the average value of the evaluator 5.18, which means that this application is feasible to use as a learning media in the history of colonial wars in Indonesia. © 2024 IEEE.

    Author Keywords:

    assessment; multimedia; Multimedia Development Life Cycle

    Indexed Keywords:

    Engineering controlled terms

    Application programs; Audio acoustics; Computer aided instruction; E-learning; Education computing; Educational technology; Learning systems; Multimedia systems; Students; Teaching

    Engineering uncontrolled terms

    Assessment; High school students; Indonesia; Interactive learning; Learning media; Multimedia applications; Multimedia development; Multimedium; Multimedium development life cycle; Teachers’

    Engineering main heading

    Life cycle

    This article can be accessed at https://www.scopus.com/pages/publications/105015673205?

  • Measurement Of Maturity Model Using The Service Operation Of SIAKBA in ITIL V3 At KPU

    Authors: Tria Khaerunisa; Irfan Dwiguna Sumitra

    DOI: 10.1109/INCITEST59455.2023.10396859

    Abstract

    The General Election Commission (KPU) is utilizing the advancing information technology (IT) to construct an Information System for KPU and the Ad hoc Board members known as SIAKBA. This IT system is progressively becoming more sophisticated as it undergoes further development. This study aims to assess the maturity model of the information system developed by the KPU and the Ad hoc Agency, employing the ITIL framework and adopting a Service Operation methodology. This study employs pertinent facts and information to assess the maturity of the information system. The research methodology employed in this study encompasses the utilization of questionnaires administered to relevant stakeholders, employing the RACI framework, as well as quantitative analysis to assess practices and procedures within the respective domain. Moreover, many metrics are utilized to assess performance within the KPU and Ad hoc Agency information systems. These metrics include incident resolution time, problem management effectiveness, change success rate, and service availability. The findings from the study on the KPU Information System and the ad hoc agency indicate a maturity level of 2.36, explicitly corresponding to level 2 as per the repeating table. Hence, it is imperative to conduct additional identification processes for the KPU to enhance its operational capabilities and deliver high-quality IT services. © 2023 IEEE.

    Author keywords

    General Election Commissions; ITIL V3; RACI; Service Operation; SIAKBA

    This article can be accessed at: https://www.scopus.com/pages/publications/85185197729

  • Comparison of K-Nearest Neighbor and Multiple Linear Regression for Beauty Product Sales Prediction

    Authors: Ade Ismayani Rahman, Rahma Wahdiniwaty

    DOI: 10.1109/INCITEST64888.2024.11121461

    Abstract

    Sales predictions constitute a critical component in establishing and expanding a business entity. Accurate sales projections enhance the quality of decisionmaking processes, increase profitability, and improve customer service results. The main objective of this research is to assess the efficacy of K-Nearest Neighbor and Multiple Linear Regression methodologies in predicting beauty product sales. The methodological approach employed in this research is of a quantitative method. The dataset incorporated encompasses variables such as product specifications, pricing, stock, and number of sold. Data preprocessing methodologies are employed to clean the data, handle missing data and detect outliers. The research findings show that both methods can predict product sales. However, the Multiple Linear Regression model has a better advantage than K-Nearest Neighbor. The Multiple Linear Regression method has smaller average values of RMSE, MAE, and MAPE than K-Nearest Neighbor, which are 4.637, 3.990 and 0.077. Meanwhile, the average value of R2 generated by Multiple Linear Regression is greater than K-Nearest Neighbor, which is 0.820. This proves that the Multiple Linear Regression method is more suitable for predicting beauty product sales. © 2024 IEEE.

    Author keywords

    data mining; k-nearest neighbor; multiple linear regression; sales prediction

    This article can be accessed at https://www.scopus.com/pages/publications/105015857048

  • Prediction of Raw Material Usage for Hijab Production Using k-Nearest Neighbors and Random Forest Methods

    Authors: Luthfi Rifqi Zulfiqar, Geraldi Catur Pamuji, Hengky Saputra, Fithrah Syawaludin

    DOI: 10.1109/INCITEST64888.2024.11121429

    Abstract

    Accurate demand forecasting will optimize the supply chain management in the hijab industry, since demand forecasting is highly required for maintaining efficient and effective production and inventory processes. This study investigates the k-Nearest Neighbors (k-NN) and Random Forest (RF) for the purpose of predicting demands regarding raw materials in the hijab production process. Key performance metrics considered for evaluating both models include the RMSE, MAE, MAPE, and R2. These findings indicate that k-NN outperforms RF in terms of superior prediction accuracy with K=2. In this respect, the root mean square error from k-NN was 1.768 against the RF’s RMSE of 1.801, proving that it is always more reliable in capturing local variations in data. On top of this, even incomplete data or those occasions when demand shifts all over the place were handled well by k-NN with more consistent and thus more accurate results. These results offer valuable insights for hijab manufacturers, allowing them to optimize their supply chain management by optimizing material shortages and overstock inventory. This research further highlights the importance of choosing the right predictive model according to the context and data characteristics to improve operational efficiency and enhance customer satisfaction. © 2024 IEEE.

    Author keywords

    Hijab Production; k-Nearest Neighbors; Prediction; Random Forest; Supply Chain Optimization

    This article can be accessed at https://www.scopus.com/pages/publications/105015887825

  • UI/UX Design Using User-Centered Design Method on Staycation Website

    Authors: Herry Saputra, Mohamad Algipani, Alfi Naga Mulya, Halena Fauziah Zafira

    DOI: 10.1109/INCITEST64888.2024.11121477

    Abstract

    This study focuses on creating a UI/UX design for a web-based Staycation (You Can Stay Plus Staycation) application. This research is a UI/UX design for Staycation, which can help users find hotels, apartments, and houses. The method used for the staycation application is User-Centered Design (UCD) method. UCD method focuses on user needs which the designs developed through can be optimized and focus on end-user needs. This research aims to create a friendly design that is easy to use and comfortable. This design is expected to make it easier for users to find vacation spots and places to stay. It can be concluded that with this application, users can find it easier to find vacation spots and places to visit. © 2024 IEEE.

    Author keywords

    – ; UCD; UI/UX design; web-based staycation

    This article can be accessed at https://www.scopus.com/pages/publications/105015654435

  • Prediction Models of Acceptance Student Scholarships in University for Students K-12 Using Decision Tree Learning

    Authors: Agus Nursikuwagus, Tono Hartono, Agus Setiana, Muhammad Agil Alfariski, Refaldi Satria Gumelar, Muhammad Rizdky Maulady

    DOI: 10.1109/INCITEST64888.2024.11121501

    Abstract

    Receiving scholarships for high school students is one of the key processes in obtaining scholarships at a university; therefore, the process of monitoring and evaluating scholarship recipients at the high school level is very necessary. We haven’t used machine learning for prediction yet. A fair and suitable process is crucial to support the justification candidate. This research aims to provide prediction learning models based on the proposed dataset. We leveraged classification techniques like decision trees base, naive bayes learning, and support vector learning. As a result of the task, we received a variety of accuracy levels, ranging from tree learning to support vector machine. Each model presents accuracy values of 1.00,1.00, 1.00,0.81, and 0.99, in that order. SVM outperforms the other models, particularly in reducing false predictions. The dataset consists of 547 instances, with 70% of them in the training dataset and 30% in the testing dataset. Future research can leverage deep learning methods or large language machines. Providing the tuning parameter is crucial for enhancing classification accuracy. © 2024 IEEE.

    Author keywords

    classification learning; confusion matrix; decision tree; models; prediction

    This article can be accessed at https://www.scopus.com/pages/publications/105015870242

  • The Utilization of Data Visualization in Klinik Keluarga within the Cianjur District

    Authors: Alif Finanditha, Dian Dharmayanti, Juliadit Syahputra

    DOI: 10.1109/INCITEST64888.2024.11121481

    Abstract

    The objective of this research is to develop effective and efficient visualizations to assist the Promkes & Marketing Coordinator, and Warehouse Coordinator in acquiring the necessary information in a more quick and precise manner to improve the decision-making process. Based on the results of interviews conducted with the Promkes & Marketing Coordinator, the Warehouse Coordinator said that the current form of information presentation is a graph. However, this form of presentation has not helped the Promkes & Marketing Coordinator and Warehouse Coordinator perform their duties and misinterpret the information. With so much data that needs to be processed, this results in the Promkes & Marketing Coordinator and Warehouse Coordinator taking longer to get information, which hinders the tasks of the Promkes & Marketing Coordinator and Warehouse Coordinator. In this research, the method used adapts from 7 steps of data visualization adapted to the research to build a good visualization according to the needs. The knowledge extraction process is performed using descriptive statistics and data mining techniques. The implementation of the visualization design is done through the creation of a prototype, which is then tested through the usability testing method. The test results indicate that the data visualization prototype enables health promotion & marketing and warehouse coordinators to grasp the necessary information more swiftly. © 2024 IEEE.

    Author keywords

    data mining; data visualization; usability testing

    This article can be accessed at https://www.scopus.com/pages/publications/105015855737