1 10 29 https://repository.horizon.ac.id/files/original/12e9954d859f1b56edea897f5e269961.pdf 130ac261838f61b49471684d7376380e 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 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni 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 A Security Architecture for Mobile Computing-Based IoT Subject The topic of the resource mobile computing; mobile computing – based IoT; internet of things (IoT); security architecture. Description An account of the resource The Internet of Things (IoT) is a complex technology with various applications that have become a vital part of our everyday life. The amount of Internet of Things and linked devices continues to rise. In terms of bandwidth, service availability, security controls, cyber-attacks and privacy problems, transporting the huge data created by these IoT devices to the cloud offers concern and challenges comprising of intermittent connection, service unavailability, data loss at rest, in use and in motion, unhardened device and server, unpatched device and server and exploitation vulnerabilities. Mobile computing (MC) is a strategic solution to tackle these difficulties by offering flexible data processing and storage to end users, increase security controls and with customized IoT devices for varied geographic locations. This paper is providing a complete description of the IoT architecture's components. After that, it elaborates on similar security threats and potential cyber-attacks in the context of mobile computing-based IoT and suggested solutions. In conclusion, we provide a secure mobile-computing-based architecture design for IoT applications. Creator An entity primarily responsible for making the resource Farina Mutia, Eugene Ario Suradilaga, Raymond Giovadius Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 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 Internet of things (IoT) mobile computing mobile computing – based IoT security architecture https://repository.horizon.ac.id/files/original/9deefe5fa28ccbad0d15734da0108104.pdf 41ad0f62073de77a3f7b0388eea3f947 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 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni 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 and Mitigation of Religion Bias in Indonesian Natural Language Processing Datasets Subject The topic of the resource natural language processing; Indonesian NLP; social bias; debiasing Description An account of the resource Previous studies have shown the existence of misrepresentation regarding various religious identities in Indonesian media. Misrepresentations of other marginalized identities in natural language processing (NLP) datasets have been recorded to inflict harm against such marginalized identities, in cases such as automated content moderation, and as such must be mitigated. In this paper, we analyze, for the first time, several Indonesian NLP datasets to see whether they contain unwanted bias and the effects of debiasing on them. We find that two, out of three, datasets analyzed in this study contain unwanted bias, whose effects trickle down to downstream performance under the form of allocation and representation harm. The results of debiasing at the dataset level, as a response to the biases previously discovered, are consistently positive for the respective dataset. Nevertheless, depending on the dataset and embedding used to train the model, they vary highly at the downstream performance level. In particular, the same debiasing technique can decrease bias on a combination of datasets and embedding, yet increase bias on another, particularly in the case of representation harm. Creator An entity primarily responsible for making the resource Muhammad Arief Fauzan, Ari Saptawijaya Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 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 debiasing Indonesian NLP natural language processing social bias https://repository.horizon.ac.id/files/original/092501d5627ab57618c6373877838e2e.pdf 9b61ecbf48d47a26fd929439e33b4190 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 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni 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 Antlion Optimizer Algorithm Modification for Initial Centroid Determination in K-means Algorithm Subject The topic of the resource clustering; initial center; centroid; antlion optimizer; sum of intra-distance clusters; k-means Description An account of the resource Clustering is a grouping of data used in data mining processing. K-means is one of the popular clustering algorithms, easy to use and fast in clustering data. The K-means method groups data based on k distances and determines the initial centroid randomly as a reference for processing. Careless selection of centroids can result in poor clustering processes and local optima. One of the improvements in determining the initial centroid on the k-means method is to use the optimization method for determining the initial centroid. The modified Antlion Optimizer (ALO) method is used to improve poor clustering in the initial centroid determination and as an alternative to determining the initial centroid in the k-means method for better clustering results. The results of the research on the use of the proposed method for determining the initial centroid provide an increase in clustering compared to the usual k-means and k-means++ methods. This is evidenced by the evaluation of the Sum of Intra-Cluster distance (SICD) with UCI datasets, namely iris, wine, glass, ecoli and cancer in each method, the best SICD value was obtained in the proposed method. Then measuring the best SICD value for each method and datasets is measured by providing a ranking proving that the proposed method on the iris, wine, cancer datasets gets the first rank and on the ecoli and glass datasets the proposed method and the k-means++ method both get the first rank. From the average ranking value, the proposed method is ranked first which provides evidence that the proposed method can improve clustering results and can be an alternative method for determining the initial center of a cluster using the k-means method. Creator An entity primarily responsible for making the resource Nanang Lestio Wibowo, Moch Arief Soeleman, Ahmad Zainul Fanani Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 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 antlion optimizer centroid Clustering initial center K-means sum of intra-distance cluster https://repository.horizon.ac.id/files/original/d8f2b754b5b818b6f3c446344aef68b4.pdf a5c4fb35caf3957da1da77d224a4a3ce 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 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni 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 Application of Object Mask Detection Using the Convolution Neural Network (CNN) Subject The topic of the resource covid-19; object detection; image processing; convolution neural network (CNN); public services Description An account of the resource The spread of Coronavirus Disease (Covid-19) is still a serious problem we are currently facing. The spread occurred very quickly through the process of face-to-face interaction. The process of face-to-face interaction that occurs both in public spaces and closed spaces has a great risk of transmitting the Covid-19 virus. One of the efforts to deal with the spread of the Covid- 19 virus is by increasing the use of masks both in public and closed spaces. Based on this, this study aims to develop an Object Detection process in image processing techniques. Object Detection development using the Convolution Neural Network (CNN) method to provide optimal output. The CNN can process the input image which is converted into a pixel matrix and then forwarded to the convolution layer. The research dataset consists of 2000 images of face masks and not masks. The images were obtained from the open sources github.com and kaggle.com. The results of the study present a system capable of detecting masks in real time. CNN provides very good performance with an accuracy rate of 99.05%. With these results, the contribution of this research can be used for the process of monitoring public services for the community to increase the use of masks. Creator An entity primarily responsible for making the resource Yuhandri, Musli Yanto, Eka Naufaldi Novri Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 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 convolution neural network (CNN) COVID-19 image processing Object detection public services https://repository.horizon.ac.id/files/original/79a0933ad24019b66df303920a378922.pdf 5a8b861fbb0fddd80c5ee7db6e1a7a3d 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 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni 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 Assessing User Experience and Usability in the OVO Application: Utilizing the User Experience Questionnaire and System Usability Scale for Evaluation Subject The topic of the resource digital wallet; user experience; usability; user experience questionnaire; system usability scale Description An account of the resource The OVO application, despite having a large user base in Indonesia, has received low ratings compared to other digital wallet apps on the Google Play Store and App Store. Users frequently complain about the user experience, which greatly affects their overall satisfaction. This study evaluates the user experience and usability of the OVO application using the User Experience Questionnaire (UEQ) and System Usability Scale (SUS). The UEQ results show that efficiency is excellent (1.55), while attractiveness, perspicuity, dependability, and stimulation are above average (1.56, 1.67, 1.33, and 1.16, respectively). However, the novelty aspect falls below average (0.64), indicating a need for improvement. The SUS score is 77.53, classifying the app as "Acceptable" with a "C" grade and an overall "Good" rating. Addressing the identified shortcomings can enhance the user experience and usability, ultimately improving user satisfaction. This study contributes valuable empirical data to the field, offering insights for researchers and practitioners in assessing the user experience and usability of mobile applications. Creator An entity primarily responsible for making the resource Ali Ibrahim, Onkky Alexander, Ken Ditha Tania, Pacu Putra, Allsela Meiriza Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 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 digital wallet system usability scale usability user experience user experience questionnaire https://repository.horizon.ac.id/files/original/d8f5fe8a03009ce9203320c76743c7ec.pdf 3ded903ef0f07e57c8a3a479001bc46a 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 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni 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 Brent Crude Oil Price Forecasting using the Cascade Forward Neural Network Subject The topic of the resource artificial neural networks; cascade forwards; brent; crude oil; MAPE Description An account of the resource Crude oil is one of the most traded non-food products or commodities in the world. In Indonesia, crude oil will still be a contributor to the Gross Domestic Product in 2021. Excessive consumption of fuel oil (BBM) in Indonesia has resulted in a scarcity of crude oil, especially diesel. Forecasting the price of Brent crude oil is an important effort to anticipate fluctuations in the price of fuel oil. The Cascade Forward Neural Network (CFNN) method is proposed to forecast fuel prices because of its superiority in fluctuating data types. The data used in this research is the price of Brent crude oil in the period January 2008 to December 2022. The CFNN method will be evaluated using the Mean Absolute Percentage Error (MAPE) to choose the best architectural model. The best Architectural Model is used to predict the next 12 months. After 10 architectural model trials, 2-6-1 became the best model with a MAPE data training value of 6.3473% and MAPE data testing of 9.4689%. Forecasting results for Brent crude oil for the next 12 months tend to experience a downward trend until December 2023. Creator An entity primarily responsible for making the resource Fatkhurokhman Fauzi, Dewi Ratnasari Wijaya, Tiani Wahyu Utami Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 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 Artificial neural networks brent cascade forwards crude oil MAPE https://repository.horizon.ac.id/files/original/71fa622c6288b9d83fe8fbc78e751cdd.pdf de14e35e6e967cd0602d949d5ef23c75 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 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni 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 Classification of Acute Lymphoblastic Leukemia based on White Blood Cell Images using InceptionV3 Model Subject The topic of the resource ALL; CNN; deep learning; inceptionV3; leukemia Description An account of the resource Acute Lymphoblastic Leukemia (ALL) is the most prevalent form of leukemia that occurs in children. Detection of ALL through white blood cell image analysis can assist in prognosis and appropriate treatment. In this study, the author proposes an approach for classifying ALL based on white blood cell images using a Convolutional Neural Network (CNN) model called InceptionV3. The dataset used in this research consists of white blood cell images collected from patients with ALL and healthy individuals. These images were obtained from The Cancer Imaging Archive (TCIA), which is a service for storing large-scale cancer medical images available to the public. During the evaluation phase, the author used training data evaluation metrics such as accuracy and loss to measure the model's performance. The research results show that the InceptionV3 model is capable of classifying white blood cell images with a high level of accuracy. This model achieves an average ALL recognition accuracy of 0.9896 with a loss of 0.031. The use of CNN models like InceptionV3 in medical image analysis has the potential to enhance the efficiency and accuracy of image-based disease diagnosis Creator An entity primarily responsible for making the resource Rizki Firdaus Mulya, Ema Utami, Dhani Ariatmanto Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 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 ALL CNN deep learning InceptionV3 Leukemia https://repository.horizon.ac.id/files/original/2f0f563f220dedb2a99b4956ce2725c9.pdf 3ccf1ae932a7210d8a9359351835901c 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 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni 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 Classification of Hearing Loss Degrees with Naive Bayes Algorithm Subject The topic of the resource classification; hearing loss degrees; naive bayes Description An account of the resource According to the World Health Organization (WHO), hearing loss is one of the fourth highest causes of disability. The number of people with hearing loss continues to increase yearly. This increase occurred due to delays in recognizing the hearing loss, leading to delays in providing treatment. To solve this problem one solution to deal with this is early identification to detect the degree of hearing loss. This research will use machine learning to classify the degree of hearing loss. The algorithm implemented in this study is naive Bayes. This study uses a dataset from the open-access repository Zenodo with 3105 raw data and 19 features. This study evaluates the performance of overall accuracy, precision, recall, and f1-score and classified four classes: mild, moderate, moderately severe, and severe. The methodology classification stages in this study include data pre�processing, data training, data testing to evaluation. From evaluating the performance of the Naive Bayes algorithm, the classification results obtained the highest impacts in the form of 94% overall accuracy, 100% precision, 100% recall, and 97% f1-score in classifying the degree of hearing loss Creator An entity primarily responsible for making the resource Okky Putra Barus, Romindo, Jefri Junifer Pangaribuan Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Elektronik: 2580-0760 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 classification hearing loss degrees Naïve Bayes https://repository.horizon.ac.id/files/original/5ea4ac2d098f9776c9baa659dcf2d481.pdf 48280de598ea7559f48b50c0b61be467 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 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni 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 Comparing the Performance of Data Mining Algorithms in Predicting Sentiments on Twitter Subject The topic of the resource sentiment analysis; twitter; SVM; K-NN Description An account of the resource On the social networking site Twitter, users can post tweets, videos, and images. It can, however, also be disruptive and difficult. In order to categorize material and improve searchability, hashtags are crucial. This study focuses on examining the opinions of Twitter users who participate in trending topics. The algorithms K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) are employed for sentiment analysis. The dataset comprises of tweet information on popular subjects that was collected using the Twitter API and saved in Excel format. SVM and K-NN are used for data preparation, weighting, and sentiment analysis. With 105 data points, the study provides insights into user sentiment. SVM identified 99% of positive and 1% of negative replies with accuracy of 80%. KNN successfully identified 90% of positive and 10% of negative responses, with an accuracy rate of 71.4%. According to the results, SVM performs better when analyzing the sentiment of hashtag users on Twitter Creator An entity primarily responsible for making the resource Rusydi Umar, Sunardi, Muhammad Nur Ardhiansyah Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 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 K-NN sentiment analysis SVM Twitter https://repository.horizon.ac.id/files/original/8725a544985c6e9156b821baf35a43c3.pdf 4b75cc41a5b85bd44e3bd333c2b08fde 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 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni 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 Comparison of Naive Bayes and PSO-Based Naive Bayes Algorithms for Prediction of Covid-19 Patient Recovery Data in Indonesia Subject The topic of the resource naive bayes algorithm; particle swarm optimization; covid-19 patients; data mining; classification Description An account of the resource A brand-new illness known as COVID 19 was identified in 2019 but has yet to infect humans (World Health Organization, 2019). This group of viruses can infect mammals including humans as well as birds and cause sickness. People commonly contract coronaviruses from the flu and other minor respiratory ailments, but they can also spread serious diseases like SARS, MERS, and the deadly COVID-19. So that there are no more casualties, this number must be decreased. It is crucial to understand the variables that can truly reduce the danger of death and gauge the propensity for recovery in Covid-19 patients. Several techniques in data mining can be used to forecast patient recovery rates depending on various characteristics. This study's criteria included gender, age, province, and status. The Naive Bayes (NB) and Pso-based Naive Bayes algorithms are compared in this study using patient datasets to determine whether strategy is more accurate. The findings of this study reveal that using the NB method has a 94.07% accuracy rate, a precision value of 14%, a recall value of 1%, and an AUC value of 0.613, according to the study's data. The accuracy rate of PSO-based Naive Bayes is 95.56%, the precision is 25%, the recall is 1%, and the AUC is 0.540. Creator An entity primarily responsible for making the resource Alvina Felicia Watratan, Ema Utami, Anggit Dwi Hartanto Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 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 classification covid-19 patients data mining naive bayes algorithm Particle Swarm Optimization