1 10 27 https://repository.horizon.ac.id/files/original/288c1fd4b6180106bd92a6638b6ea70e.pdf e36c2d3e35d43cff1a9561d22debb72b 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. 20, NO. 5 2022 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 TELKOMNIKA Telecommunication, Computing, Electronics and Control Multi-threaded approach in generating frequent itemset of Apriori algorithm based on trie data structure Subject The topic of the resource Apriori algorithm, Flynn’s taxonomy, Indexing, Multi-threaded, Trie data structure Description An account of the resource This research is about the application of multi-threaded and trie data structures to the support calculation problem in the Apriori algorithm. The support calculation results can search the association rule for market basket analysis problems. The support calculation process is a bottleneck process and can cause delays in the following process. This work observed five multi-threaded models based on Flynn’s taxonomy, which are single process, multiple data (SPMD), multiple process, single data (MPSD), multiple process, multiple data (MPMD), double SPMD first variant, and double SPMD second variant to shorten the processing time of the support calculation. In addition to the processing time, this works also consider the time difference between each multi-threaded model when the number of item variants increases. The time obtained from the experiment shows that the multi-threaded model that applies a double SPMD variant structure can perform almost three times faster than the multi-threaded model that applies the SPMD structure, MPMD structure, and combination of MPMD and SPMD based on the time difference of 5-itemsets and 10-itemsets experimental result. Creator An entity primarily responsible for making the resource Ade Hodijah, Urip Teguh Setijohatmo, Ghifari Munawar, Gita Suciana Ramadhanty Source A related resource from which the described resource is derived DOI: 10.12928/TELKOMNIKA.v20i5.24088 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource October 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 1693-6930 Relation A related resource http://journal.uad.ac.id/index.php/TELKOMNIKA 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 Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant TELKOMNIKA Telecommunication, Computing, Electronics and Control Apriori algorithm Flynn’s taxonomy Indexing Jurnal Nasional Informatika Multi-threaded Trie data structure https://repository.horizon.ac.id/files/original/bcc567ac1ded5da20da0464ba3f896e0.pdf ae1f44106721d49097dd19de4c199a57 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. 20, NO. 5 2022 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 TELKOMNIKA Telecommunication, Computing, Electronics and Control Identification of human resource analytics using machine learning algorithms Subject The topic of the resource Decision tree classifier, Logistic regression, Machine learning, Random forest Description An account of the resource Employee attrition is one of the most significant business issues in human resource (HR) analytics. This research aims to identify the most critical elements that contribute to employee attrition. Businesses operate heavily on employee training in order to maximize the returns they will offer to the company in the future. By utilizing the employee information value concept, it has been discovered that employee features such as overtime, the total number of projects and job level have a significant impact on attrition. To find the probability of new employee attrition, various classification algorithms such as decision trees (DT) classifier, logistic regression (LR), random forests (RF), and K-means clustering are used. A comparative analysis of the models with different rating scales is carried out for the highest accuracy. For prediction, four diverse machine learning (ML) algorithms such as LR, RF, DT classifier, and k-nearest neighbors (k-NN) are used. DT classifier outperforms with 97% of accuracy than other techniques. The effects of predictive ML techniques on the employee dataset show that RF evaluation outperforms other ML techniques followed by model of LR for the specific dataset if precision is the preferred metric. Identification of HR is forecasted using ML algorithms on employee data. Creator An entity primarily responsible for making the resource Elham Mohammed Thabit A. Alsaadi, Sameerah Faris Khlebus, Ashwak Alabaichi Source A related resource from which the described resource is derived DOI: 10.12928/TELKOMNIKA.v20i5.21818 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource October 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 1693-6930 Relation A related resource http://journal.uad.ac.id/index.php/TELKOMNIKA 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 Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant TELKOMNIKA Telecommunication, Computing, Electronics and Control Decision tree classifier Jurnal Nasional Informatika Logistic regression machine learning Random Forest https://repository.horizon.ac.id/files/original/8aee21367b4f6f8e5c0fd810227d0c72.pdf b9ae8d7a66fd7b5fdfb30fe44020b08e 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. 20, NO. 5 2022 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 TELKOMNIKA Telecommunication, Computing, Electronics and Control Hybrid features selection method using random forest and meerkat clan algorithm Subject The topic of the resource Feature selection, Machine learning, Meerkat clan Random forest Description An account of the resource In the majority of gene expression investigations, selecting relevant genes for sample classification is considered a frequent challenge, with researchers attempting to discover the minimum feasible number of genes while yet achieving excellent predictive performance. Various gene selection methods employ univariate (gene-by-gene) gene relevance rankings as well as arbitrary thresholds for selecting the number of genes, are only applicable to 2-class problems and use gene selection ranking criteria unrelated to the algorithm of classification. A modified random forest (MRF) algorithm depending on the meerkat clan algorithm (MCA) is provided in this work. It is one of the swarm intelligence algorithms and one of the most significant machine learning approaches in the decision tree. MCA is used to choose characteristics for the RF algorithm. In information systems, databases, and other applications, feature selection imputation is critical. The proposed algorithm was applied to three different databases, where the experimental results for accuracy and time proved the superiority of the proposed algorithm over the original algorithm. Creator An entity primarily responsible for making the resource Hayder Adnan Saleh, Rana Amer Sattar, Enas Mohammed Hussein Saeed, Dalael Saad Abdul-Zahra Source A related resource from which the described resource is derived DOI: 10.12928/TELKOMNIKA.v20i5.23515 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource October 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 1693-6930 Relation A related resource http://journal.uad.ac.id/index.php/TELKOMNIKA 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 Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant TELKOMNIKA Telecommunication, Computing, Electronics and Control feature selection Jurnal Nasional Informatika machine learning Meerkat clan Random forest https://repository.horizon.ac.id/files/original/1408f32e9a2a5db88ca19bd3636896e2.pdf 7db305ef60cd4e03a5525ae92c6cc12d 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. 20, NO. 5 2022 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 TELKOMNIKA Telecommunication, Computing, Electronics and Control A stochastic algorithm for solving the posterior inference problem in topic models Subject The topic of the resource Latent Dirichlet allocation, Posterior inference, Stochastic optimization, Topic models Description An account of the resource Latent Dirichlet allocation (LDA) is an important probabilistic generative model and has usually used in many domains such as text mining, retrieving information, or natural language processing domains. The posterior inference is the important problem in deciding the quality of the LDA model, but it is usually non-deterministic polynomial (NP)-hard and often intractable, especially in the worst case. For individual texts, some proposed methods such as variational Bayesian (VB), collapsed variational Bayesian (CVB), collapsed Gibb’s sampling (CGS), and online maximum a posteriori estimation (OPE) to avoid solving this problem directly, but they usually do not have any guarantee of convergence rate or quality of learned models excepting variants of OPE. Based on OPE and using the Bernoulli distribution combined, we design an algorithm namely general online maximum a posteriori estimation using two stochastic bounds (GOPE2) for solving the posterior inference problem in LDA model. It also is the NP-hard non-convex optimization problem. Via proof of theory and experimental results on the large datasets, we realize that GOPE2 is performed to develop the efficient method for learning topic models from big text collections especially massive/streaming texts, and more efficient than previous methods. Creator An entity primarily responsible for making the resource Hoang Quang Trung, Xuan Bui Source A related resource from which the described resource is derived DOI: 10.12928/TELKOMNIKA.v20i5.23764 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource October 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 1693-6930 Relation A related resource http://journal.uad.ac.id/index.php/TELKOMNIKA 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 Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant TELKOMNIKA Telecommunication, Computing, Electronics and Control Jurnal Nasional Informatika Latent Dirichlet allocation Posterior inference Stochastic optimization Topic models https://repository.horizon.ac.id/files/original/c5a76253c45cf8cd59faec7c1b8d81b1.pdf 5bfc9b0133d35fdd7225e0d0422e9e25 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. 20, NO. 5 2022 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 TELKOMNIKA Telecommunication, Computing, Electronics and Control A proton-exchange membrane fuel cell and ultra-capacitor system model for stand-alone residential applications Subject The topic of the resource Energy demands, Energy efficiency, PEM fuel cell, PEMFC, Stationary applications, Ultra-capacitor Description An account of the resource Energy consumption by sector in Malaysia is rising significantly, especially for residential and commercial sectors, and is expected to continue to increase in the upcoming years. The existing power generated from a proton-exchange membrane fuel cell (PEMFC) system may be insufficient to sustain peak load demands during peak periods in stationary residential applications. The presence of an ultra-capacitor (UC) bank would be beneficial as a support as it can supply a large burst of power. The integration of PEMFC and UC has the potential to provide an effective way to supply power demands, has better energy efficiency, and is also economically friendly. In this research, we demonstrate a proposed combined PEMFC and UC bank that operates in parallel. A novel design methodology and dynamic model for both PEMFC and UC systems as energy sources have been developed for stand-alone residential applications. The simulation results are shown in Matlab Simulink. These results are based on mathematical and dynamic models of the system being shown. Creator An entity primarily responsible for making the resource Ibrahim Alhamrouni, Mohamed Salem, Awang Jusoh, Tole Sutikno Source A related resource from which the described resource is derived DOI: 10.12928/TELKOMNIKA.v20i5.24292 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource October 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 1693-6930 Relation A related resource http://journal.uad.ac.id/index.php/TELKOMNIKA 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 Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant TELKOMNIKA Telecommunication, Computing, Electronics and Control Energy demands Energy Efficiency Jurnal Nasional Informatika PEM fuel cell PEMFC Stationary applications Ultra-capacitor https://repository.horizon.ac.id/files/original/a51c6edf31ad645bb77c3593f84afde9.pdf 5d01910a612a65e58499e75f54a0fd51 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. 20, NO. 5 2022 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 TELKOMNIKA Telecommunication, Computing, Electronics and Control A secure telemedicine electronic platform based on lightweight cryptographic approachcommunication, Computing, Electronics and Control Subject The topic of the resource Diffie Hellman encryption, IoT chaotic cryptographic, IoT system, Lightweight crypto, Telemedicine platform Description An account of the resource Telemedicine platforms have emerged as one of the most harnessed studies in recent years, especially after the spread of pandemics. Due to the epidemic, telemedicine distribution to rural or isolated areas has become an urgent need. However, there are several obstacles to providing remote medical care, the most significant of which is protecting patient data while sustaining the speed of communication between the patient and the medical staff. The significant of this study is to provides a lightweight encryption/decryption technique that uses on the internet of medical things in stance of bio-sensors and bio-actuators. This study is one of the cybersecurity approaches, such type of encryption has little effect on the speed of data transmission. The Diffie Hellman technique is used as a lightweight encryption method because it includes four encryption-keys. The efficiency of the proposed encryption method has been compared with several equivalent methods. According to experimental results, the proposed encryption method represents a lightweight and secure method which can accomplish the level of protection that required to secure medical information despite the data’s disarray. Creator An entity primarily responsible for making the resource Israa Ezzat Salem, Haider Rasheed Abdulshaheed, Hassan Muwafaq Gheni Source A related resource from which the described resource is derived DOI: 10.12928/TELKOMNIKA.v20i5.22662 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource October 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 1693-6930 Relation A related resource http://journal.uad.ac.id/index.php/TELKOMNIKA 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 Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant TELKOMNIKA Telecommunication, Computing, Electronics and Control Diffie Hellman encryption IoT chaotic cryptographic IoT system Jurnal Nasional Informatika Lightweight crypto Telemedicine platform https://repository.horizon.ac.id/files/original/9ec182fb1cf6abc8928009c7612345ed.pdf 3037a546491e3ac893411fd1667572bc 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. 20, NO. 5 2022 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 TELKOMNIKA Telecommunication, Computing, Electronics and Control Model design to develop online web based questionnaire Subject The topic of the resource Design, Features, Online, Questionnaire, Web Based Description An account of the resource This research aims to create a web-based application for sharing questionnaires. The developed features are creating questionnaires, sharing questionnaire in the dashboard, filter the questionnaire as the requested criterias, exchange the rewarded coins for gifts, export questionnaire data to a document, set a limit for the questionnaire for each device. The development will be using data collecting using questionnaire and literature study. Then, software development life cycle (SDLC) waterfall research methodology will be used for the website system development. Result of this research will be a website application that will be used for questionnaire maker so that they can reach the respondent count target, have a suitable respondent (minimize respondent who does not meet the criteria), and also can collect more validated data. Creator An entity primarily responsible for making the resource Julian Wesley, Fifilia, Cynthia Catrine, Dennis Antony, Ferdian Rizky Estefan Source A related resource from which the described resource is derived DOI: 10.12928/TELKOMNIKA.v20i5.23768 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource October 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 1693-6930 Relation A related resource http://journal.uad.ac.id/index.php/TELKOMNIKA 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 Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant TELKOMNIKA Telecommunication, Computing, Electronics and Control Design Features, Online Jurnal Nasional Informatika questionnaire Web Based https://repository.horizon.ac.id/files/original/76afddfb8f0a38762a0bd5286c365cd1.pdf 429b903bd50cb258340968723d1cf55d 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. 20, NO. 5 2022 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 TELKOMNIKA Telecommunication, Computing, Electronics and Control Static-gesture word recognition in Bangla sign language using convolutional neural network Subject The topic of the resource BSL, BSL word dataset, Convolutional neural network, Static-gesture signs Description An account of the resource Sign language is the communication process of people with hearing impairments. For hearing-impaired communication in Bangladesh and parts of India, Bangla sign language (BSL) is the standard. While Bangla is one of the most widely spoken languages in the world, there is a scarcity of research in the field of BSL recognition. The few research works done so far focused on detecting BSL alphabets. To the best of our knowledge, no work on detecting BSL words has been conducted till now for the unavailability of BSL word dataset. In this research, a small static-gesture word dataset has been developed, and a deep learning-based method has been introduced that can detect BSL static-gesture words from images. The dataset, “BSLword contains 30 static-gesture BSL words with 1200 images for training.The training is done using a multi-layered convolutional neural network with the Adam optimizer. OpenCV is used for image processing and TensorFlow is used to build the deep learning models. This system can recognize BSL static-gesture words with 92.50% accuracy on the word dataset. Creator An entity primarily responsible for making the resource Kulsum Ara Lipi, Sumaita Faria Karim Adrita, Zannatul Ferdous Tunny, Abir Hasan Munna, Ahmedul Kabir Source A related resource from which the described resource is derived DOI: 10.12928/TELKOMNIKA.v20i5.24096 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource October 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 1693-6930 Relation A related resource http://journal.uad.ac.id/index.php/TELKOMNIKA 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 Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant TELKOMNIKA Telecommunication, Computing, Electronics and Control BSL BSL word dataset Convolutional neural network Jurnal Nasional Informatika Static-gesture signs https://repository.horizon.ac.id/files/original/e128726ae7ace9496050a6292d77d73b.pdf 2ad537ca4a2ad129f56a79739666ece6 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. 20, NO. 5 2022 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 TELKOMNIKA Telecommunication, Computing, Electronics and Control Knowing group motivation using Bolzano method on PageRank computation Subject The topic of the resource Bolzano method, Eigenvalues, PageRank, Plagiarism network, Trend analysis Description An account of the resource On the e-learning system, student assignments are collected, but problems arise that based on observations from two classes of database courses, 73% of students make plagiarism so lecturers need to give motivation to students. Self motivate is needed by with a group of students. For this reason, using a bolzano method or bisection method will provide an overview of the development of the plagiarism trend between groups of students based on scores on similarity score that compute by PageRank algorithm used by Google. Research method is carried out by conducting preliminary observations of plagiarism scores and creating markov matrix. PageRank compute this ranking and Bolzano method find the intersection of two eigenvalues. Bolzano results the maximum and minimum values on range of intervals where each group consists of 5 students. Experiments were conducted in 3 classes of database courses. Trend analysis found that the plagiarism score averaged 54% with a gradient of 3°, this is relatively small but when spread in different groups it becomes larger and student group have a higher plagiarism score. Results implies a way of looking student motivation based on the plagiarism score by a small groupto motivate each other. Creator An entity primarily responsible for making the resource M. Zainal Arifin, Ahmad Naim Che Pee, Sarni Suhaila Rahim Source A related resource from which the described resource is derived DOI: 10.12928/TELKOMNIKA.v20i5.19650 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource October 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 1693-6930 Relation A related resource http://journal.uad.ac.id/index.php/TELKOMNIKA 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 Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant TELKOMNIKA Telecommunication, Computing, Electronics and Control Bolzano method Eigenvalues Jurnal Nasional Informatika PageRank Plagiarism network Trend analysis https://repository.horizon.ac.id/files/original/670a6ec3c280db38cce80692eb209b23.pdf 4494b7e7a2d8e361973347594efc5a0a 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. 20, NO. 5 2022 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 TELKOMNIKA Telecommunication, Computing, Electronics and Control Cervical cancer diagnosis based on cytology pap smear image classification using fractional coefficient and machine learning classifiers Subject The topic of the resource Cytology image, DCT transform, Haar transform, Machine learning, Pap smear Description An account of the resource Doctors and pathologists have long been concerned about determining the malignancy from cell images. This task is laborious, time-consuming and needs expertise. Due to this reason, automated systems assist pathologists in providing a second opinion to arrive at accurate decision based on cytology images. The classification of cytology images has always been a difficult challenge among the various image analysis approaches due to its extreme intricacy. The thrust for early diagnosis of cervical cancer has always fuelled the research in medical image analysis for cancer detection. In this paper, an investigative study for the classification of cytology images is proposed. The proposed study uses the discrete coefficient transform (DCT) coefficient and Haar transform coefficients as features. These features are given as a input to seven different machine learning algorithms for normal and abnormal pap smear images classification. In order to optimize the feature size, fractional coefficients are used to form the five different sizes of feature vectors. In the proposed work, DCT transform has given the highest classification accuracy of 81.11%. Comparing the different machine learning algorithms the overall best performance is given by the random forest classifier. Creator An entity primarily responsible for making the resource Madhura Kalbhor, Swati Vijay Shinde, Hemanth Jude Source A related resource from which the described resource is derived DOI: 10.12928/TELKOMNIKA.v20i5.22440 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource October 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 1693-6930 Relation A related resource http://journal.uad.ac.id/index.php/TELKOMNIKA 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 Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant TELKOMNIKA Telecommunication, Computing, Electronics and Control Cytology image DCT transform Haar transform Jurnal Nasional Informatika machine learning Pap smear