1 10 29 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/48dec08535922b71e1ed73d4ff8eddef.pdf f00a13de7453cc924c3ae565760f46fd 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 Folk Games Image Captioning using Object Attention Subject The topic of the resource image captioning; folk games; object attention; object detection Description An account of the resource The result of deep-learning based image captioning system with encoder-decoder framework relies heavily on image feature extraction technique and caption-based model. The model accuracy is heavily influenced by the proposed attention mechanism. Unsuitability between the output of the attention model and the input expectation of the decoder can cause the decoder to give incorrect results. In this paper, we proposed an object attention mechanism using object detection. Object detection outputs a bounding box and object category label, which is then used as an image input into VGG16 for feature extraction and into a caption-based LSTM model. Experiment results showed that the system with object attention gave better performances than the system without object attention. BLEU-1, BLEU-2, BLEU-3, BLEU-4, and CIDER scores for image captioning system with object attention improved 12.48%, 17.39%, 24.06%, 36.37%, and 43.50% respectively compared to the system without object attention. Creator An entity primarily responsible for making the resource Saiful Akbar, Benhard Sitohang, Jasman Pardede, Irfan I. Amal, Kurniandha S. Yunastrian, Marsa T. Ahmada, Anindya Prameswari 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 folk games image captioning object attention Object detection https://repository.horizon.ac.id/files/original/cfea17d6790188a7258cf592cc6afdc9.pdf 533cf8244497d3cf6511b296488d0498 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 Transforming LMS into KMS in Indonesia Educational Institution Case Study in Telkom University Open Library Subject The topic of the resource library management system; library paradigm; knowledge management system; workflow management; workforce management Description An account of the resource Library is an institution that collects printed and recorded knowledge, manages it in a particular way to meet the intellectual needs of its users through various ways of knowledge interaction. In 2021, Indonesia provided 4605 active educational institutions, ranging from universities to community academies. All these institutions are obliged to provide library to create a better learning environment, by providing source of references for each course delivered by the institution. This obligation is encouraged by the government by considering library support within the accreditation system. In this accreditation system, a library should allocate books as a source of reference to each course. This establishes a paradigm that library is where we store books and where a member of the institution may borrow, learn, and return those aforementioned books. Today, educational institution deals with not only books but also thesis, dissertation, technical report, training/workshop report, research paper, etc. Authors believe it will be prudent to leave all these documents of knowledge to librarians, by changing the library's paradigm from managing books to managing knowledge. This study proposes a model of Knowledge Management System as a transformation from Library Management System. This study also explains about expected opportunities and benefits after the transformation. Creator An entity primarily responsible for making the resource Nyoman Karna, Gede Agung Ary Wisudiawan, Ni Putu Nurwita Pratami Wijaya,I Kadek Andrean Pramana Putra, Dewa Ayu Putu Rahyuni 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 knowledge management system library management system library paradigm workflow management workforce management https://repository.horizon.ac.id/files/original/5e27985edde94e4e8c246b2c02ad5ad2.pdf 654d527cc32c2b1bb08b79483e4e30a7 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 The Application of Game Mechanics and Technological Trend in Game-Based Learning: A Review of the Research Subject The topic of the resource game-based learning; systematic literature review; engagement model; technology; study subjects Description An account of the resource The rapid development of information technology affects numerous aspects of human life, including education. An example of IT application in education is game-based learning. Game-based learning has been implemented in various fields or subjects on various platforms. This is due to the potential of game-based learning to enhance the student engagement in the learning process. Nevertheless, the effectiveness of this method is still needs to be studied further. This systematic literature review aimed to explore about game mechanics that applied on current game-based learning researches, accompanied by the trend of technological utilization in research paper published in this domain. This study covered 30 journal and conference proceeding papers published from 2012-2022. The review was conducted using the Kitchenham method. Selected papers were then analyzed to determine the engagement model used in each paper (Feedback Model, Incentive and Achievement Model and Progression Model). Findings included the trend of research in this field (technology applied to each research, online feature, study majors/subject) are displayed based on the time paper were published. The result of the study indicated that all previous research used at least one of the engagement models, with 12 papers using all three models. In terms of technology, it was found that the adoption of web-based technology has been increasing in recent years, including online features which have also increased, along with the study subjects that implemented game-based learning. In summary, game-based learning can be applied in a wide range of subjects and platforms with the support of its feature, making learning more flexible Creator An entity primarily responsible for making the resource Mhd. Adhitiya Okta Riyandi, Harry Budi Santoso, Panca Oktavia Hadi Putra 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 engagement model; technology; game-based learning study subjects Systematic literature review https://repository.horizon.ac.id/files/original/3a1d4d6ed166378d4edc28f7f5436142.pdf 35d9556b57416a2aa5806eac012c5b1f 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 Development Steps of Avionics and Flight Control System of Flight Vehicle Subject The topic of the resource software in the loop simulation (SILS); hardware in the loop simulation (HILS); ready to fly system (RTFS) Description An account of the resource The success of a research is highly dependent on the method adopted, especially research related to dangerous and expensive matters which will certainly require special handling in the development or maintenance steps. One of them is research related to space technology such as aviation and rocketry technology which is very dependent on the design model of the flying vehicle and in general will always use simulation to ensure that the entire system being built is carried out safely and can be implemented properly according to plan. In the development of the flying vehicle prototype, especially the development of the avionics and flight control system, the vehicle will go through sequential simulation steps from Software in the Loop Simulation (SILS), Hardware in the Loop Simulation (HILS), and Ready to Fly System (RTFS). In this paper, the simulation steps will be described with the intention of facilitating integration and testing of each sub-system being developed, testing the control strategy applied or eliminating bugs if something goes wrong. And in the end, with a series of flying vehicle simulations, it can be developed quickly, cost-effectively, including saving human resources Creator An entity primarily responsible for making the resource Herma Yudhi Irwanto, Purnomo Yusgiantoro, Zainal Abidin S., Romie O. Bura, Aris Sarjito , Oka Sudiana, Faisa Lailiyul M 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 hardware in the loop simulation (HILS) ready to fly system (RTFS) software in the loop simulation (SILS) 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 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/3dd7fa741908a7abc6d13dfe1855b270.pdf 87e4b7264b4c7360996191d9db30dde9 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 Diabetes Risk Prediction using Feature Importance Extreme Gradient Boosting (XGBoost) Subject The topic of the resource diabetes; prediction; machine learning; xgboost Description An account of the resource Diabetes results from impaired pancreas function as a producer of insulin and glucagon hormones, which regulate glucose levels in the blood. People with diabetes today are not only experienced adults, but pre-diabetes has been identified since the age of children and adolescents. Early prediction of diabetes can make it easier for doctors and patients to intervene as soon as possible so that the risk of complications can be reduced. One of the uses of medical data from diabetes patients is used to produce a model that can be used by medical staff to predict and identify diabetes in patients. Various techniques are used to provide the earliest possible prediction of diabetes based on the symptoms experienced by diabetic patients, including using machine learning. People can use Machine Learning to generate models based on historical data of diabetic patients, and predictions are made with the model. In this study, extreme gradient boosting is the machine learning technique to predict diabetes (xgboost) using Feature Importance XGBoost. The diabetes dataset used in this study comes from the Early stage diabetes risk prediction dataset published by UCI Machine Learning, which has 520 records and 16 attributes. The diabetes prediction model using xgboost is displayed as a tree. The model accuracy result in this study was 98.71%, for the F1 score was 98.18%. While the accuracy obtained based on the best 10 attributes using the XGBoost feature importance are 98.72% Creator An entity primarily responsible for making the resource Kartina Diah Kusuma W, Memen Akbar 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 Diabetes machine learning Prediction XGBoost https://repository.horizon.ac.id/files/original/f5ef5359a8a31e6d2a37198506dd7f0a.pdf 709423fa16281a81b9a5e9f09ce7ff05 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 Evaluating Player Experience for Fear Modeling of 2D East Java Horror Game Alas Tilas Subject The topic of the resource UEQ; 2D horror game; user experience Description An account of the resource Developing a 2D horror game and evaluating the reliability of the player experience are two things that are interrelated and equally important. Developers must ensure that the game can provide a satisfying and reliable gaming experience for its players. This study aims to evaluate the reliability of the player's experience in the game entitled Alas Tilas, East Java. This study used User Experience Questionnaire (UEQ) in Indonesian as survey approach method which was given to 30 teenager respondents who at least played horror games once. UEQ may provide feedback to developers on the Attractiveness, Clarity, Efficiency, Accuracy, Stimulation, and Novelty aspects of the game. From the results of the UEQ, a reliability test will be carried out using the Cronbach Alpha Technique. The results of the descriptive analysis show that these variables are Attractiveness (mean, 0.933), Clarity (mean, 1.808), Efficiency (mean, 1.508), Accuracy (mean, 0.217), Stimulation (mean, 0.667) and Novelty (mean, 0.242). Attractiveness, Clarity and Efficiency averaged positive results. While the average aspects of accuracy, stimulation and novelty of the game get neutral results. The results of the reliability test conducted on UEQ data obtained a Cronbach alpha value > 0.6 which indicates that the research data used in testing player experience is considered reliable so that it can be used to provide input for future Alas Tilas game development. To increase the average score, the researcher provides recommendations for improvement, namely adjusting the Accuracy and Novelty aspects of the horror scenario game entitled Alas Tilas East Java. So that it is expected to improve the quality of the game Creator An entity primarily responsible for making the resource Herman Thuan To Saurik, Harits Ar Rosyid, Aji Prasetya Wibawa, Esther Irawati Setiawan 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 2D horror game UEQ user experience 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