1 10 8 https://repository.horizon.ac.id/files/original/67fcee44c55aee43c072f209233ad8c0.pdf 0fade5b514d814f4a14964308525a7c4 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 6 NO. 2 (2024) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Android-Based Detection Application ofIndonesian Sign Language System (SIBI) Using Rapid Application Development Method Subject The topic of the resource ndonesian Sign Language System Application (SIBI), Real-Time Object Detection, Tensorflow Lite, Sign Language Translator, RAD Description An account of the resource Deaf individuals face communication challenges with the general public due to their limited hearing, which necessitates the use of sign language. The gap in sign language understanding between deaf individuals and the general public often hinders their social interactions. Thisresearch develops the SIBI sign object detection model into an Android-based application that can detect and translate the Indonesian Sign Language System (SIBI) features into spoken language. The development of this application employs the Rapid Application Development (RAD) method, which includes the stages of requirements planning, user design, construction, and completion. The application was built using the Kotlin programming language and a TensorFlow Lite-based gesture detection model with three mainfeatures: real-time SIBI gesture detection, SIBI information, and Indonesian to SIBI translation. Testing involved 30 respondents with normal hearing and utilized the Blackbox Testing method. Usability testing results reached 85.6%, indicating the feasibility and effectiveness of the application. Blackbox Testing achieved a score of 100%, confirming the system's very high functionality. The Indonesian Sign Language (SIBI) Detection Application was successfully developed using the RAD method. This application has proven to be effective as a communication tool that bridges deaf individuals with the wider community in Indonesi Creator An entity primarily responsible for making the resource Sadr Lufti Mufreni1, Tikaridha Hardiani2, Muhammad Ircham Maulana Source A related resource from which the described resource is derived https://ijicom.respati.ac.id/index.php/ijicom/article/view/92/64 Date A point or period of time associated with an event in the lifecycle of the resource December 2024 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/a4a6101b2ef08c9ec888fcfc1af1ca48.pdf e03b80a117d0311bbd87111dfc80115e Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 6 NO. 2 (2024) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Comparative Analysis of K-Means and K-Medoids Algorithms in New Student Admission Subject The topic of the resource K-Means, K-Medoids, CRISP-DM, Data Mining, Clustering Description An account of the resource Universitas ‘AisyiyahYogyakarta is one of the private universities in Yogyakarta. The large number of private universities in Yogyakarta has intensified the competition for new student admissions. In this situation, every university requires the right strategy to attract prospective students. One of the strategies used by Universitas ‘Aisyiyah Yogyakarta to capture the interest of potential students is by conducting direct promotions to schools in Yogyakarta, Java, and Sumatra. In the admission process for new students in the Information Technology Study Program, a common problem arises, which is the number of prospective students who do not complete re-registration each year. These students pass the selection and are declared accepted, but they do not proceed with re-registration. The school presentation strategy contributes to student admissions, making it a good strategy, but it requires significant operational costs. Promotion area segmentation is needed so that this strategy can be more targeted, resulting in more efficientspending. Segmenting or grouping promotion areas can be addressed using data mining techniques, specifically clustering. This study aims to segment promotion areas using clustering algorithms, namely K-Means and K-Medoids, along with the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology. The evaluation of DBI (Davies-Bouldin Index) showed that the K-Means algorithm performed better than the K-Medoids algorithm. The comparison between the K-Means and K-Medoids algorithms was assessed based on the DBI evaluation results, with the smallest DBI value observed in the K-Means algorithm. The DBI value for K-Medoids was 0.196, while for K-Means it was 0.170 Creator An entity primarily responsible for making the resource Tikaridha Hardiani1, Esi Putri Silmina Source A related resource from which the described resource is derived https://ijicom.respati.ac.id/index.php/ijicom/article/view/91/63 Date A point or period of time associated with an event in the lifecycle of the resource December 2024 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/40998b985e5fd59ac6ef24bdd68242da.pdf 232523d32fedb32ccce7d65f091bee3f Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 6 NO. 2 (2024) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Mobile Application Development for Chili Disease Detection with Convolutional Neural Network Subject The topic of the resource Chili Plant Disease, Convolutional Neural Network, System Mobile Description An account of the resource The demand for chili continues to increase along with population growth and the industrial sector, but the supply is unstable due to weather factors such as high rainfall and humidity. This condition causes the spread of diseases in chili plants such as anthracnose fruit rot, begomovirus yellow virus, and leaf spots. This study aimsto develop a chili plant disease identification system and evaluate the accuracy of chili plant disease image classification. This study is expected to help experts provide recommendations for accurately controlling the spread of disease, assisting farmers in identifying diseases early,and improving the quality and quantity of chili plant harvests. The method used is Transfer Learning using the Convolutional Neural Network (CNN) MobileNet V2 architecture. The research stages include data collection, needs analysis, preprocessing design,model design, architecture stages, accuracy testing, system implementation, and system testing. These stages are carried out sequentially withoutany being skipped. Accuracy testing is calculated using a confusion matrix. In addition, the system that has been created will be tested by functional and user testing. Chili plant disease image data was obtained from chili plantations in Sumowono District, Semarang Regency. A dataset of 4,500 chili plant disease images was used, and 70% of the data was divided intotraining data and 30% for validation data. The accuracy results obtained were 99% in the training process and 94% in the validation process. Model evaluation using a new dataset of 150 chili plant disease images showed an accuracy result of 94%. Functional testing and user testing by 10 farmers produced an average value of 90. Thus, it can be concluded that the system can identify chili plant diseases well, as well as support agricultural activities and farmer needs Creator An entity primarily responsible for making the resource Sri Winiarti1, Itsnaini Irvina Khoirunnisa2, Norhudah Seman3 Source A related resource from which the described resource is derived https://ijicom.respati.ac.id/index.php/ijicom/article/view/93/62 Date A point or period of time associated with an event in the lifecycle of the resource December 2024 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/d366c6b6c99918bf8457d901e56f9ff9.pdf 89c2559bfed8348fb52fe3775e5689cb Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 6 NO. 2 (2024) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Development of a Web-based Administration System for The Bantu Sodara Community Using the Waterfall Method Subject The topic of the resource System Development, Administrative System, Waterfall Description An account of the resource Bantu SodaraCommunity requires an efficient administration system to support structured data and operational management. This study aims to develop a web-based administration system using the Waterfall method. This approach involves five stages: needs analysis, system design, implementation, testing, and maintenance. The system developed includes features for managing member data, recording donations, and documenting community activities. The implementation results show that this system is able to improve efficiency and accuracy in administrative management, as well as provide easy access and transparency for users. System testing ensures that all features run according to community needs. Thus, the development of this web-based administration system is expected to support the sustainability of the Bantu Sodara Community's operations more effectively Creator An entity primarily responsible for making the resource Bima Randy Gumilang1, Agung Nugroho2, Ahmad Turmudi Zy Source A related resource from which the described resource is derived https://ijicom.respati.ac.id/index.php/ijicom/article/view/95/61 Date A point or period of time associated with an event in the lifecycle of the resource December 2024 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/108f6f6d401515adc6f91ac62fa4c858.pdf 3ae82adb4e9f629f8c2a252530836f11 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 6 NO. 2 (2024) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Virtual Reality and Augmented Reality in Sign Language Recognition: A Review of Current Approaches Subject The topic of the resource Virtual Reality, Augmented Reality,Sign Language Recognition, Gesture Recognition, Accessibility Description An account of the resource This paper delivers a critical and comprehensive review of the current approaches to Sign Language Recognition (SLR) using Virtual Reality (VR) and Augmented Reality (AR) technologies. The problem lies in traditional SLR methods, which often face limitations such as poor gesture recognition accuracy, lack of contextual understanding, and challenges in scalability. Recent advances in VR and AR technologies, characterized by their immersive and interactive environments, have shown promising potential to address these limitations, offering solutions that leverage state-of-the-art machine learning and computer vision techniques to enhance gesture recognition and contextual comprehension. These issues hinder effective communication and inclusivity for the deaf and hard-of-hearing community. This review critically examines how VR and AR, with their immersive and interactive environments, offer innovative solutions by enabling real-time feedback, dynamic learning experiences, and enhanced gesture recognition systems. Furthermore, the paper evaluates the integration of VR and AR with advanced technologies like machine learning and computer vision, which significantly improve the accuracy and efficiency of SLR. Despite notable progress, challenges such as hardware limitations, cultural diversity, and high costs remain. This study concludes with future directions for developing inclusive, scalable, and culturally sensitive SLR systems through advancements in AI, increased affordability, and interdisciplinary collaboration. The findings emphasize the transformative potential of VR and AR in creating accessible communication tools for lots worldwide Creator An entity primarily responsible for making the resource Aris Rakhmadi1, Anton Yudhana2, Sunardi3 Source A related resource from which the described resource is derived https://ijicom.respati.ac.id/index.php/ijicom/article/view/94/60 Date A point or period of time associated with an event in the lifecycle of the resource December 2024 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/5b9269555a53279e9828e22987d40002.pdf 0e98d19b6ad1a990840d668f1e34a284 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 6 NO. 2 (2024) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource FakeNewsDetectioninHealthDomainUsing Transformer Models Subject The topic of the resource FakeNewsDetection,TransformerModels,HealthInformation Description An account of the resource The rise of fake news in the health sector poses a serious threat to public well-being and accurate health communication.Thisstudyinvestigatestheeffectivenessof transformermodels, particularlyBERT(Bidirectional Encoder Representations from Transformers), in detecting fake news related to health. By leveraging the advanced contextual understanding of BERT, we aim to enhance the accuracy of fake news detection in this critical domain. Our approach involves training the BERT model on a curated dataset of health news articles, followedbyrigorousevaluationofitsabilitytodifferentiatebetweengenuineandmisleadingcontent.Theresults reveal that the transformer-based model significantly outperforms traditional methods, achieving high accuracy and robust performance metrics. This research underscores the potential of transformer models in combating health misinformation and provides a foundation for future improvements in automated fake news detection systems Creator An entity primarily responsible for making the resource Suwarto1,SriHastaMulyani2,Hamzah3, R.NurhadiWijayaS4,Rodiyah5,WitaAdelia Source A related resource from which the described resource is derived https://ijicom.respati.ac.id/index.php/ijicom/article/view/89/59 Date A point or period of time associated with an event in the lifecycle of the resource December 2024 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/8bc6767f62789a291a091b64832b2f0a.pdf c22b579abd5059fe24982bd1862140ed Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 6 NO. 2 (2024) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Prediction of Peak Ground Acceleration (PGA) in Java Using Artificial Neural Network Method Subject The topic of the resource Earthquake, Prediction, Peak Ground Acceleration (PGA), Artificial Neural Network Description An account of the resource Java is one of the islands in Indonesia that frequently experiences earthquakes. Earthquakes can cause significant ground motion that can damage buildings and threaten human life. Peak Ground Acceleration (PGA) is a measure of the maximum ground acceleration that occurs during an earthquake and is an important factor that must be considered at every construction site to assess the potential damage that can be caused by an earthquake. The parameters considered in determining PGA predictions are earthquake parameters, such as magnitude and hypocenter distance. In addition, the PGA value is also influenced by local site conditions. With advances in information technology and artificial intelligence, especially in the development of Artificial Neural Networks (ANN), research on PGA prediction needs to be conducted as one of the efforts to reducethe risk of earthquakes. The purpose of this research is to obtain the best network architecture forpredicting PGA values. The criteria for selecting the best network architecture is done by comparing the error value of each possible architecture formed. The best prediction results are obtained in the model with 3-15-1 architecture with a correlation value of 0.67. Creator An entity primarily responsible for making the resource Sofyan Hadi Rahmawan1, Cahyo Crysdian2, Sri Harini3 Source A related resource from which the described resource is derived https://ijicom.respati.ac.id/index.php/ijicom/article/view/90/58 Date A point or period of time associated with an event in the lifecycle of the resource December 2024 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/c6e06d60f6bf583788603fbcef94fca2.pdf 9c77b1ed0dfb656408359882c2135d06 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 6 NO. 2 (2024) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Analysis of the Application of Linear Interpolation and Quadratic Interpolation in Electrical Distribution Performance Subject The topic of the resource Linear Interpolation, Distribution Networks, Matlab Description An account of the resource The electricity distribution network is an important component that distributes electricity from substations to end consumers. Monitoring voltage across the network is critical, but direct measurement at all points is often impractical due to resource limitations. This research uses linear interpolation and quadratic interpolation to estimate stress at unmeasured points. Voltage measurement data at several points is used as a basis for interpolation. With the help of MATLAB, the voltage at unmeasured points can be estimated quickly and accurately. The results of the interpolation of distance on electricity consumption show that electricity consumption decreases as distance increases. At a distance of 5 km (Ds. Galih), electricity consumption was recorded at 1,237.5 kWh, while at a distance of 15 km (Ds. Triharjo) electricity consumption was reduced to 1,232.5 kWh. Furthermore, at a distance of 25 Km (Wungurejo District), electricity consumption was recorded at 1,227.5 kWh, and at a distance of 35 Km (Tejorejo District) electricity consumption decreased again to 1,222.5 kWh. This method enables more comprehensive monitoring of network performance, helps identify areas that require special attention, and supports decisions in network maintenance and repair. In conclusion, linear interpolation is an effective method for estimating voltages in electrical distribution networks, making an important contribution to improving the reliability and efficiency of electrical power distribution. Assists in monitoring and analyzing the performance of the electricity distribution network, thereby enabling more targeted maintenance and repair actions Creator An entity primarily responsible for making the resource Siswandari Noertjahjani1, Syafiq Abdul Zaki2, ArisKiswanto Source A related resource from which the described resource is derived https://ijicom.respati.ac.id/index.php/ijicom/article/view/84/71 Date A point or period of time associated with an event in the lifecycle of the resource December 2024 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text