1 10 15 https://repository.horizon.ac.id/files/original/994cceb938e5dc7aadbc612a0a0411b6.pdf 9d2d1749e9b90bb0ac4d3a00352b5403 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 8 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 Analyzing Reddit Data: HybridModel for Depression Sentiment using FastText Embedding Subject The topic of the resource depression; social media; reddit; biLSTM;fasttext Description An account of the resource Depression, a prevalent mental condition globally, exerts a substantial influence on various aspects of human cognition, emotions, and behaviour. The alarming increase in deaths attributable to depression over the past few years demonstrates the imperative need to address this problem through preventionand treatment interventions. In the era of thriving social media platforms, which have a significant impact on society and psychological aspects, these platforms have become a means for people to convey their emotions and experiences openly. Reddit standsout among these platforms as a significant place. The main aim of this study is to examine the feasibility of forecasting individuals' mental states by classifying Reddit articles ondepression and non-depression. This work aims to employ deep learning algorithms and word embeddings to analyze the textual and semantic settings of narratives todetect symptoms of depression. The study effectively employed a BiLSTM-BiGRU model that applied FastText word embeddings.The BiLSTM-BiGRU model analyzes informationbidirectionally, detecting correlations in sequential data. It's suitable for tasks dependent on input order or addressing data uncertainties. The Reddit dataset, featuring text concerning depression, achieved an accuracy score of 97.03% and an F1 scoreof 97.02%. Creator An entity primarily responsible for making the resource Amrul Faruq1, Merinda Lestandy2*, Adhi Nugraha3, Abdurrahim Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/article/view/5641/928 Publisher An entity responsible for making the resource available Departmentof Electrial Engineering, Facultyof Engineering, Universitas Muhammadiyah Malang, Malang, Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 28-04-2024 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/ca340f66ece562e7b5d3a622db4b6a13.pdf 7b21d2a0de206ba9b03b35996f27b22e 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 8 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 Mapping Residential Land Suitability Using a WEB-GIS-Based Multi-Criteria Spatial Analysis Approach: Integration of AHP and WPM Methods Subject The topic of the resource spatial analysis;MCDM;WPM method;AHP method; cohen's kappa Description An account of the resource Along with the increase in population and the acceleration of economic growth, the urgent need for additional property that can serve as a place for various community activities also increases. It is typicalfor big cities that are the epicenter of urbanization to experience a sharp spike in land demand. One area that has excellent accessibility is Sidarjo Regency, which is comparable to SurabayaCity in this regard. This research aims to use Web-GIS to conduct spatial data analysis to identify the most suitable land functions for use in residential areas. Analytic Hierarchy Process (AHP) and Weighted Product Model (WPM) are used in this research for spatial data modeling based on multi-criteria decision-making (MCDM). Parameters were based on distance to the city center, distance to the market, distance to the hospital, distance to public transport, slope, soil type, and rainfall intensity. The results of spatial data modeling categorize the suitability of new settlement land into the categories of uninhabitable and habitable land. The K value of 0.27 is the outcome of a comparison test between the two MCDM approaches using Cohen's Kappa coefficient. The test indicates that the K value falls into the category of having a fair strength of agreement between the two methods that came into play Creator An entity primarily responsible for making the resource Anik Vega Vitianingsih1, Choirul Ullum2, Anastasia Lidya Maukar3, Verdi Yasin4, Seftin Fitri Ana Wati5 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/article/view/4520/918 Publisher An entity responsible for making the resource available Informatics Department, Universitas Dr. Soetomo, Surabaya, Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 20-04-2024 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 https://repository.horizon.ac.id/files/original/69fc9107acfcd07eb5457ed1fc82235d.pdf 89eec11783240c6d0b686fe50c609942 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 8 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 YOLO-based Small-scaled Model for On-Shelf Availability in Retail Subject The topic of the resource YOLO; small-scaled model; on-shelf availability; retail; deep learning Description An account of the resource On-shelf availability(OSA) in the retail industry plays a very crucial role incontinuous sales. Product unavailability may lead to a bad impression on customers and reduce sales. The retailindustry may continue to develop through the rapidly advancing technology era to thrive in a market where competition is increasingly tough. Along with technological advancements in recentdecades, Artificial Intelligence has begun to be applied to support OSA, particularly using object detection technology. In this research, we develop a small-scaled object detection model based on four versions of You Only Look Once (YOLO) algorithm, namely YOLOv5-nano, YOLOv6-nano, YOLOv7-tiny, and YOLOv8-nano. The developed model can be used to support automatic detection of OSA. A small-scalemodel has developedin the sense of post-practicalimplementation through low-cost mobile applications. We also use the quantization method to reduce the model size, INT8 and FP16. This small-scaled model implementation also offers implementation flexibility. With a total of 7697 milk-based retail product images and 125 different product classes, the experiment results show that the developed YOLOv8-nano model, with a mAP50 score of 0.933 and an inference time of 13.4 ms, achieved the best performance Creator An entity primarily responsible for making the resource Arrie Kurniawardhani1, Dhomas Hatta Fudholi2*, Gabriel Imam Andaru3, Ahmad Azzam Alhanafi4, Nabil Najmudin Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/article/view/5600/925 Publisher An entity responsible for making the resource available Departmentof Informatics, Universitas Islam Indonesia, Yogyakarta, Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 25-04-2024 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/d43a143c47e0c9386ac5605a8384c936.pdf 7b21d2a0de206ba9b03b35996f27b22e 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 8 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 Evaluating the Bibit App: The HEART Framework Approach in UX Design Subject The topic of the resource bibit;HEART framework;investment application;user experience Description An account of the resource With the rise of investment applications like Bibit in Indonesia, evaluating user experience is crucial to improveuser engagement and satisfaction. This study aims to assess the Bibit appuser experience using the HEART framework to identify areas for improvement. A descriptive survey was conducted usingthe Slovin method to determine a sample size of approximately 100 people. The study useda questionnaire distributed throughGoogle Forms that measuresthe five aspects of the HEART frameworkon a Likert scale. Data were analyzed for validity and reliability using IBM SPSS and stored in Google Spreadsheets. Overall, the Bibit app demonstrated high satisfaction, engagement, adoption, retention, and task success among its users, with most categories scoring above the 80% target. However, specific areas, particularlyHappiness 2, Adoption 1, Retention 1, and Task Success 3, requirefurther development attention.The Bibit app provides a generally satisfying user experience, with significant potential for improvement in navigation tooltips, investment product development, and app speed and efficiency. Creator An entity primarily responsible for making the resource Dandi Setya Perdana1, Lintang YuniarBanowosari Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/article/view/5714/923 Publisher An entity responsible for making the resource available Postgraduate Program, Gunadarma University, Jakarta, Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 24-04-2024 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/91141e3ef6b6030260a30066d631fd72.pdf d68d7f496a6245d27a0ca1d00b9b26d4 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 8 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 Enhanced Yolov8 with OpenCV for Blind-Friendly Object Detection and Distance Estimation Subject The topic of the resource computer vision; blindpeople; YOLOv8; OpenCV Description An account of the resource The development of computer technology and computer vision has had a significant positive impact on the daily lives of blind people, especially in efforts to improve their navigation abilities. This research has the main aim of introducing a superiorobject detection method, especially in supporting the sustainability and effectiveness of navigation for the blind. The main focus of the research is the use of YOLOv8, the latest version of YOLO, as an object detection method, and distance measurement technology from OpenCV. The main challenge to be addressed involves improving the accuracy and performance of object detection, which is an important key to ensuring safe and effective navigation for blind people. In this context, blind people often face obstacles in their mobility, especially when walking around environments that may be full of obstacles or obstacles. Therefore, better object detection methods become essential to ensure the identification of nearby objects, which may involveobstacles or potential threats, thereby preventing possible accidents or difficulties in daily commuting. Involving YOLOv8 as an object detection method provides the advantage of a high level of accuracy, although with a slight increase in detection duration and GPU power consumption compared to previous versions. The research results show that YOLOv8 provides a low error rate, with an average error percentage of 3.15%, indicating very optimal results. Using a combined performance evaluation approach of YOLOv8 and OpenCV distance measurement metrics, this research not only seeks to improve accuracy but also efficiency in detection time and power consumption. This research makes an important contribution in presenting technological solutions that can help improve mobility and safety for blind people, bringing a real positive impact in facilitating their daily lives Creator An entity primarily responsible for making the resource Erwin Syahrudin1, Ema Utami2, Anggit Dwi Hartanto Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/article/view/5529/917 Publisher An entity responsible for making the resource available Magister of Informatics Engineering, Universitas AMIKOM Yogyakarta, Yogyakarta, Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 29-03-2024 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/76f1db88ce68af9a5042eb4b57533b4e.pdf 9951e8be719aa4224633e19e6e8125e7 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 8 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 Digital Image Object Detectionwith GLCM Multi-Degrees and Ensemble Learning Subject The topic of the resource Object detection; object rotation; Gray-level Co-occurrence Matrix Multi-Degrees; Ensemble Voting Description An account of the resource Object detection in digital images has been implemented in various fields. Object detection faces challenges, one of which is rotation problems, causing objects to become unknown. We need a method that can extract features that do not affect rotation and reliable ensemble-based classification. The proposal uses the GLCM-MD (Gray-Level Co-occurrence Matrix Multi-Degrees) extraction method with classification using K-Nearest Neighbours(K-NN) and Random Forest (RF) learning as well as Voting Ensemble (VE) from two single classifications. The main goal is to overcome the difficulty of detecting objects when the object experiences rotation which results in significant visualization variations. In this research, the GLCM method is used to produce features that are stable against rotation. Furthermore, classification methods such as K-Nearest Neighbours(KNN), Random Forest (RF), and KNN-RF fusion using the Voting ensemble method are evaluated to improve detection accuracy. The experimental results show that the use of multi-degreesand the use of ensemble voting at all degrees can increase the accuracy value, and the highest accuracy for extraction using multi-degreesis 95.95%. Based on test results which show that the use of features of various degrees and the ensemble voting method can increase accuracyfor detecting objects experiencing rotation. Creator An entity primarily responsible for making the resource Florentina TatrinKurniati1, Hindriyanto Dwi Purnomo2, Irwan Sembiring3, Ade Iriani4 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/article/view/5597/931 Publisher An entity responsible for making the resource available Facultyof Information Technology, Universitas Kristen Satya Wacana Date A point or period of time associated with an event in the lifecycle of the resource Facultyof Information Technology, Universitas Kristen Satya Wacana 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/327a26bee4e32b1549c771fe54f0db5e.pdf 19601635cac88d4a1c69cf1ff8a622f2 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 8 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 LR-GLASSO Method for Solving Multiple Explanatory Variables of the Village Development Index Subject The topic of the resource logistic regression (LR);LR-GLASSO, LR-LASSO;multiple explanatory variables;village development index. Description An account of the resource Sustainable Development Goals (SDGs) are developments that maintain sustainable improvement in society’s economic, social, and environmental welfare. Kemendes PDTT RI has issued the Village Development Index (VDI) to provide information and the status of village progress to support village development to improve the National SDGS.Modellingwith multiple explanatory variables causes a high correlation between explanatory variables, multicollinearity, and coefficient estimation results, which have major variance and overfitting in prediction results. The modeling solution uses LASSO and GLASSO. Binary categorical response data uses binary logistic regression (LR), so LR-LASSO and LR-GLASSO are used. North Maluku Province has a VDI ranking that tends to fall in 2018-2022. Based on the mean and variance of the coefficient estimation results and misclassification errors, LR-GLASSO is better than LR-LASSO and LR. LR-GLASSO is recommended for analyzing VDI data because it has many explanatory variables, and the correlation between them is relatively high. The recommendation given by the Indonesian government, if it is to increase the status of VDI in Indonesia, especially in North Maluku province, is to increase the number of electricity users, food and beverage stalls, and other cooperatives. The Indonesian government alsoneeds to pay attention to villages relatively far from the regent's office, between food and beverage stalls, and supporting health centres,because they still need to be developed compared to other villages,and morethan 50% of villages are underdeveloped. If the Village SDGs are formulated through increasing VDI status, it will support the achievement of SDGs goals nationally Creator An entity primarily responsible for making the resource https://jurnal.iaii.or.id/index.php/RESTI/article/view/5656/929 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/article/view/5656/929 Publisher An entity responsible for making the resource available Department of Statistics, Faculty of Mathematics and Natural Sciences, IPB University, Bogor, Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 28-04-2024 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/ee1362bd553d5c0744722ee499414ad2.pdf 8a6d6d153a80921e4b15e36ad909899c 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 8 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 IoT-Based Irrigation System Using Machine Learning for Precision Shallot Farming Subject The topic of the resource smart farming;WSN sensors; IoT; shallot farming; enrekang Description An account of the resource Despite the massive production of shallots in EnrekangRegency, South Sulawesi Province, Indonesia, the cultivation method is still very conventional. Shallot cultivation is very challenging because it requires precision irrigation and pest prevention. In this research, we proposed a smart irrigation system to help farmers manage irrigation with more efficient water usage without hampering their pest prevention. The system outcomes were three options: 1) no water needed, 2) water is required and is efficient for watering and 3) water is required but it is not efficient for watering. We used Wireless Sensor Networks and IoT to collect yield parameters, designed a firebase database, and developed a mobile application and a web service embedded with a machine learning application. All applications interacted by using the Representational State Transfer Application Programming Interface. The proposed system architecture successfully gathered cropland data and distributed them to all applications within the system. Furthermore, we analyzed four supervised learning algorithms (decision trees, random forest, gradient boosting, and K-Nearest neighbor), and the random forest was deployed in the web service because it outperformed other algorithms with an accuracy of 94% and AUC Score of 0.90 Creator An entity primarily responsible for making the resource Mardhiyyah Rafrin1, Muh. Agus2, Putri Ayu Maharani Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/article/view/5579/919 Publisher An entity responsible for making the resource available Computer Science,TeknologiProduksiand Industri, Institut Teknologi Bacharuddin Jusuf Habibie, Parepare, Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 20-04-2024 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/f0fc32892060b627a083aec9e6ff2dbe.pdf 815a7cb7938121d5e7a08653f536d18a 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 8 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 Integration Waterfall and ScrumMethodology in The Development of SIMARGA Web Application Subject The topic of the resource waterfall; scrum; web application; methodologies integration; software development Description An account of the resource This research explores the integration of Waterfall and Scrum methodologies in the development of the SIMARGA web application. The integration aims to maximize the strengths of each methodology, with Waterfall contributing to planning, analysis, and initial system structure, while Scrum supports the creation of Product Backlog and implementation of Scrum events. The combination results in a structured and methodical product management process, simplifying task lists and enhancing efficiency. The achievement of good efficiency and effectiveness in task execution is facilitated by leveraging both methodologies, reducing wastage. Progress in product development and team productivity is measured through daily meetings, evaluations, and sprint reviews. Emphasis is placed on fostering strong relationships among the Scrum team, customers, and stakeholders, promoting effective communication and collaboration. However, challenges are identified in team commitment to daily meetings, potentially influenced by their involvement in additional business activities. Future efforts should focuson technological resource enhancement and software maintenance to achieve the initially outlined product goals. The effectiveness of this product development initiative can be measured using metrics such as views and user data, particularly in Kabupaten Pegunungan Bintang Creator An entity primarily responsible for making the resource Nikson Theys Muay1, Eko Sediyono2, Johan Tambotoh Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/article/view/5652/920 Publisher An entity responsible for making the resource available Magister Sistem Informasi, Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana, Salatiga, Jawa Tengah Date A point or period of time associated with an event in the lifecycle of the resource 20-04-2024 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/24c1b04eb68eca7402905f915e64ed8a.pdf a41997475b6aeac981db42898106cbb5 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 8 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 Enhancing Weighted Averaging for CNN Model Ensemble in Plant Diseases Image Classification Subject The topic of the resource ensemblelearning;weighted averagingvoting;convolutional neural network;image classification;plant disease Description An account of the resource Deeplearning, especially convolutional neural networks (CNN), has gained traction in the field of image classification. In the specific case of plant diseaseclassification, improving the accuracy and reliability of image classification is paramount. This paper delves into the ensemble predictiontechnique using a weighted soft-voting method. Instead of assigning a generalized weight to each CNN model, our approach emphasizes giving weights to each label's prediction within every individual model. We employed three esteemed CNN architectures for our experiments: DenseNet201, InceptionV3, and Xceptionfocusing on classifying various diseases affecting grapes. By harnessing transfer learning coupled with end-to-end fine-tuning, we achieved a streamlined and efficient training process. Notably, the f1-score for each grape disease class was used as a parameter for weight determination and as a metric for the final evaluation. In our study, the newly proposed method was tested across various datasets and ensemble scenarios, demonstrating its effectiveness by not only outperforming the conventional soft-voting and prevalent weighted soft-voting methods, which achieved best scores of 95.68% and 95.81% respectively, but also by achieving a remarkable accuracy of 96.56%.This method's efficacy is heightened when ensemble models exhibit distinct characteristics; the more varied the model characteristics, the more enhanced the ensemble results Creator An entity primarily responsible for making the resource Octavian1, Ahmad Badruzzaman2, Muhammand Yusuf Ridho3, Bayu Distiawan Trisedya4 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/article/view/5669/926 Publisher An entity responsible for making the resource available Faculity of Computer Sciences, University ofIndonesia, Depok, Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 25-04-2024 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