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<title>Volume 20, Issue 9 (2024) | Journal of Computer Science</title>
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    <title><![CDATA[Personalized Recommendation System: Web of Things Using Modular Density-Based Community Discovery]]></title>
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        <![CDATA[<p>Journal of Computer Science, Published online: 21 June 2024; <a href="https://thescipub.com/jcs/jcssp.2024.918.930">doi:10.3844/jcssp.2024.918.930</a></p>Community discovery is the cornerstone and core of study in customized recommendation, assembling group features and social network analysis on the web of things. Conventional community discovery meth...]]></content:encoded>
    <dc:title><![CDATA[Personalized Recommendation System: Web of Things Using Modular Density-Based Community Discovery]]></dc:title><dc:creator>Vinod  Patidar</dc:creator><dc:creator>Jayashree A. Patil</dc:creator><dc:creator>Sonika  Thapak</dc:creator><dc:creator>Manmohan  Singh</dc:creator><dc:creator>Vikas  Prasad</dc:creator><dc:creator>Shaheen  Ayyub</dc:creator><dc:creator>Dharmendra  Sharma</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.918.930</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-06-21; | doi:10.3844/jcssp.2024.918.930</dc:source>
    <dc:date>2024-06-21</dc:date>
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    <prism:doi>10.3844/jcssp.2024.918.930</prism:doi>
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    <title><![CDATA[PM2.5 Prediction Using Homogenous and Heterogenous Ensemble Learning: A Comprehensive Evaluation]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.931.954</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 20 June 2024; <a href="https://thescipub.com/jcs/jcssp.2024.931.954">doi:10.3844/jcssp.2024.931.954</a></p>Air pollution is a global issue. PM2.5 is considered to be the most dangerous pollutant. Prediction of PM2.5 concentration is important so that effective measures can be taken beforehand. A multitude ...]]></content:encoded>
    <dc:title><![CDATA[PM2.5 Prediction Using Homogenous and Heterogenous Ensemble Learning: A Comprehensive Evaluation]]></dc:title><dc:creator>Shrabani  Medhi</dc:creator><dc:creator>Minakshi  Gogoi</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.931.954</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-06-20; | doi:10.3844/jcssp.2024.931.954</dc:source>
    <dc:date>2024-06-20</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.931.954</prism:doi>
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    <title><![CDATA[Global Supply Chain: Enhance Production Cost Efficiency Through Machine Learning]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.955.963</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 14 June 2024; <a href="https://thescipub.com/jcs/jcssp.2024.955.963">doi:10.3844/jcssp.2024.955.963</a></p>Machine learning has enabled the discovery of various disciplines and patterns in Supply Chain Management (SCM). The entire industrial sector is striving to harness the contextual intelligence provide...]]></content:encoded>
    <dc:title><![CDATA[Global Supply Chain: Enhance Production Cost Efficiency Through Machine Learning]]></dc:title><dc:creator>Loubna  Moumeni</dc:creator><dc:creator>Mohammed  Saber</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.955.963</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-06-14; | doi:10.3844/jcssp.2024.955.963</dc:source>
    <dc:date>2024-06-14</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.955.963</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.964.971">
    <title><![CDATA[Secure Fingerprint Identification for Unconscious Personal Health Record Users During an Emergency Situation]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.964.971</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 20 June 2024; <a href="https://thescipub.com/jcs/jcssp.2024.964.971">doi:10.3844/jcssp.2024.964.971</a></p>The Personal Health Record (PHR) system is a system that allows an individual to collect, store and share his/her health-related information. Such information about the victim during an emergency is c...]]></content:encoded>
    <dc:title><![CDATA[Secure Fingerprint Identification for Unconscious Personal Health Record Users During an Emergency Situation]]></dc:title><dc:creator>Pariwat  Choosang</dc:creator><dc:creator>Sangsuree  Vasupongayya</dc:creator><dc:creator>Kitsiri  Chochiang</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.964.971</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-06-20; | doi:10.3844/jcssp.2024.964.971</dc:source>
    <dc:date>2024-06-20</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.964.971</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.972.985">
    <title><![CDATA[Performance Assessment of CPU Scheduling Algorithms: A Scenario-Based Approach with FCFS, RR, and SJF]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.972.985</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 16 June 2024; <a href="https://thescipub.com/jcs/jcssp.2024.972.985">doi:10.3844/jcssp.2024.972.985</a></p>This study presents an extensive examination of CPU scheduling algorithms, focusing on the First-Come, First-Served (FCFS), Round-Robin (RR), and Shortest-Job-First (SJF) strategies through a carefull...]]></content:encoded>
    <dc:title><![CDATA[Performance Assessment of CPU Scheduling Algorithms: A Scenario-Based Approach with FCFS, RR, and SJF]]></dc:title><dc:creator>Olaa  Hajjar</dc:creator><dc:creator>Escelle  Mekhallalati</dc:creator><dc:creator>Nada  Annwty</dc:creator><dc:creator>Faisal  Alghayadh</dc:creator><dc:creator>Ismail  Keshta</dc:creator><dc:creator>Mohammed  Algabri</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.972.985</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-06-16; | doi:10.3844/jcssp.2024.972.985</dc:source>
    <dc:date>2024-06-16</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.972.985</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.972.985</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.986.996">
    <title><![CDATA[Features of the Security System Development of a Computer Telecommunication Network]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.986.996</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 20 June 2024; <a href="https://thescipub.com/jcs/jcssp.2024.986.996">doi:10.3844/jcssp.2024.986.996</a></p>Global computer networks have enabled ordinary users, companies, organizations and medical institutions to gain virtually unlimited access to data arrays. Therefore, developing systems capable of ensu...]]></content:encoded>
    <dc:title><![CDATA[Features of the Security System Development of a Computer Telecommunication Network]]></dc:title><dc:creator>Leonid  Chervyakov</dc:creator><dc:creator>Tagirbek  Aslanov</dc:creator><dc:creator>Dmitry  Polezhaev</dc:creator><dc:creator>Viktor  Lysenko</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.986.996</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-06-20; | doi:10.3844/jcssp.2024.986.996</dc:source>
    <dc:date>2024-06-20</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.986.996</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.986.996</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.997.1008">
    <title><![CDATA[Efficient Detection of Palm and Hand Landmark for Speech Impaired People Using Mediapipe Model]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.997.1008</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 24 June 2024; <a href="https://thescipub.com/jcs/jcssp.2024.997.1008">doi:10.3844/jcssp.2024.997.1008</a></p>Human-machine interaction may be a basic figure in this age of touch-screen gadgets. Numerous gadgets are being created that can be worked without touching the system. So, in this consideration, how t...]]></content:encoded>
    <dc:title><![CDATA[Efficient Detection of Palm and Hand Landmark for Speech Impaired People Using Mediapipe Model]]></dc:title><dc:creator>Sharmila  Rathod</dc:creator><dc:creator>Nilesh  Rathod</dc:creator><dc:creator>Nilesh  Marathe</dc:creator><dc:creator>Aruna  Gawade</dc:creator><dc:creator>Jyoti  Kundale</dc:creator><dc:creator>Nikita  Kulkarni</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.997.1008</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-06-24; | doi:10.3844/jcssp.2024.997.1008</dc:source>
    <dc:date>2024-06-24</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.997.1008</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.997.1008</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1009.1019">
    <title><![CDATA[Explainable Evidence-Based Veracity Assessment of Textual Claim]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1009.1019</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 25 June 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1009.1019">doi:10.3844/jcssp.2024.1009.1019</a></p>The rise of social media and the internet has significantly increased the amount and speed of shared information, posing challenges for verifying content. Automated veracity checking has become essent...]]></content:encoded>
    <dc:title><![CDATA[Explainable Evidence-Based Veracity Assessment of Textual Claim]]></dc:title><dc:creator>Aruna  Shankar</dc:creator><dc:creator>Narayanan  Kulathuramaiyer</dc:creator><dc:creator>Johari Bin Abdullah</dc:creator><dc:creator>Muthukumaran  Pakkirisamy</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1009.1019</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-06-25; | doi:10.3844/jcssp.2024.1009.1019</dc:source>
    <dc:date>2024-06-25</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1009.1019</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1009.1019</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1020.1029">
    <title><![CDATA[A New Hybrid Model to Predict the Performance of Trainee Teachers Based on Clustering and Classification]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1020.1029</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 26 June 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1020.1029">doi:10.3844/jcssp.2024.1020.1029</a></p>This article explores how artificial intelligence, particularly machine learning, can be used to assess and predict the performance of trainee teachers in Morocco. Considering the country's focus on i...]]></content:encoded>
    <dc:title><![CDATA[A New Hybrid Model to Predict the Performance of Trainee Teachers Based on Clustering and Classification]]></dc:title><dc:creator>Yissam  Lakhdar</dc:creator><dc:creator>Khawla  EL-Bendadi</dc:creator><dc:creator>Brahim  Bakkas</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1020.1029</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-06-26; | doi:10.3844/jcssp.2024.1020.1029</dc:source>
    <dc:date>2024-06-26</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1020.1029</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1020.1029</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1030.1039">
    <title><![CDATA[Deep Learning Approach to Mitigate DDoS Attacks in SDN]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1030.1039</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 5 July 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1030.1039">doi:10.3844/jcssp.2024.1030.1039</a></p>The rise of Distributed Denial of Service (DDoS) attacks remains a significant obstacle to network security and availability. This abstract presents a new hybrid model for DDoS mitigation in Software-...]]></content:encoded>
    <dc:title><![CDATA[Deep Learning Approach to Mitigate DDoS Attacks in SDN]]></dc:title><dc:creator>Hema Surendrakumar Dhadhal</dc:creator><dc:creator>Paresh  Kotak</dc:creator><dc:creator>Parvez  Faruki</dc:creator><dc:creator>Atul  Gonsai</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1030.1039</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-07-05; | doi:10.3844/jcssp.2024.1030.1039</dc:source>
    <dc:date>2024-07-05</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1030.1039</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1030.1039</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1040.1050">
    <title><![CDATA[Autism Spectrum Disorder Prediction Using Hybrid Deep Learning Model and a Recommendation System Application for Autistic Patient]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1040.1050</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 6 July 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1040.1050">doi:10.3844/jcssp.2024.1040.1050</a></p>The goal of this study is to create machine learning models that use a big dataset to predict Autism Spectrum Disorder (ASD). To achieve optimal performance, a number of algorithms were employed and r...]]></content:encoded>
    <dc:title><![CDATA[Autism Spectrum Disorder Prediction Using Hybrid Deep Learning Model and a Recommendation System Application for Autistic Patient]]></dc:title><dc:creator>Biplov  Paneru</dc:creator><dc:creator>Bishwash  Paneru</dc:creator><dc:creator>Krishna Bikram Shah</dc:creator><dc:creator>Awan  Shrestha</dc:creator><dc:creator>Ramhari  Poudyal</dc:creator><dc:creator>Khem Narayan Poudyal</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1040.1050</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-07-06; | doi:10.3844/jcssp.2024.1040.1050</dc:source>
    <dc:date>2024-07-06</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1040.1050</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1040.1050</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1051.1058">
    <title><![CDATA[Logistic Regression with Multi-Connected Weights]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1051.1058</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 4 July 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1051.1058">doi:10.3844/jcssp.2024.1051.1058</a></p>Results of current research in biological and cognitive science reveal that neuronal interactions predominantly depend on neurotransmitters for signaling and sending information between neurons. Furth...]]></content:encoded>
    <dc:title><![CDATA[Logistic Regression with Multi-Connected Weights]]></dc:title><dc:creator>Avazjon Marakhimov Rakhimovich</dc:creator><dc:creator>Kabul Khudaybergenov Kadirbergenovich</dc:creator><dc:creator>Zahriddin Muminov Ishkobilovich</dc:creator><dc:creator>Kudaybergenov Jabbarbergen Kadirbergenovich</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1051.1058</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-07-04; | doi:10.3844/jcssp.2024.1051.1058</dc:source>
    <dc:date>2024-07-04</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1051.1058</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1051.1058</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1059.1068">
    <title><![CDATA[Design of Enterprise Architecture Using Zachman Framework at Private School in Center Jakarta]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1059.1068</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 8 July 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1059.1068">doi:10.3844/jcssp.2024.1059.1068</a></p>Technology is currently fundamental and necessary, including in the education sector, where information technology, such as enterprise architecture, can be applied to support and facilitate school bus...]]></content:encoded>
    <dc:title><![CDATA[Design of Enterprise Architecture Using Zachman Framework at Private School in Center Jakarta]]></dc:title><dc:creator>Keysia  Aprilia</dc:creator><dc:creator>Francka Sakti Lee</dc:creator><dc:creator>Yemima Monica Geasela</dc:creator><dc:creator>Shierly  Everlin</dc:creator><dc:creator>Felliks Feiters Tampinongkol</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1059.1068</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-07-08; | doi:10.3844/jcssp.2024.1059.1068</dc:source>
    <dc:date>2024-07-08</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1059.1068</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1069.1079">
    <title><![CDATA[Phishing Website Detection Using Improved Multilayered Convolutional Neural Networks]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1069.1079</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 6 July 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1069.1079">doi:10.3844/jcssp.2024.1069.1079</a></p>The internet has become an essential part of many fields: Communication, entertainment, commerce, industrial production, agriculture, etc. Unfortunately, online users are vulnerable to various attacks...]]></content:encoded>
    <dc:title><![CDATA[Phishing Website Detection Using Improved Multilayered Convolutional Neural Networks]]></dc:title><dc:creator>Hadia  Bibi</dc:creator><dc:creator>Syed Rehan Shah</dc:creator><dc:creator>Mirza Murad Baig</dc:creator><dc:creator>Muhammad Imran Sharif</dc:creator><dc:creator>Mehwish  Mehmood</dc:creator><dc:creator>Zahid  Akhtar</dc:creator><dc:creator>Kamran  Siddique</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1069.1079</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-07-06; | doi:10.3844/jcssp.2024.1069.1079</dc:source>
    <dc:date>2024-07-06</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1069.1079</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1069.1079</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1080.1090">
    <title><![CDATA[E-Participation Success Factors: A Systematic Literature Review]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1080.1090</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 10 July 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1080.1090">doi:10.3844/jcssp.2024.1080.1090</a></p>E-participation which has emerged from the development of electronic government, is a very interesting phenomenon to study today. However, when e-participation was first introduced, various problems a...]]></content:encoded>
    <dc:title><![CDATA[E-Participation Success Factors: A Systematic Literature Review]]></dc:title><dc:creator>Elgamar  Syam</dc:creator><dc:creator>Elgamar  Syam</dc:creator><dc:creator>Alawiyah Abd Wahab</dc:creator><dc:creator>Abdullah  Husin</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1080.1090</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-07-10; | doi:10.3844/jcssp.2024.1080.1090</dc:source>
    <dc:date>2024-07-10</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1080.1090</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1080.1090</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1091.1098">
    <title><![CDATA[The Stanford Dependency Relations for Commonsense Knowledge Representation of Winograd Schema Challenge (WSC)]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1091.1098</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 10 July 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1091.1098">doi:10.3844/jcssp.2024.1091.1098</a></p>An alternative to the Turing Test that could offer a more accurate measurement of artificial intelligence is the Winograd Schema Challenge (WSC). It presents a number of coreference resolution issues ...]]></content:encoded>
    <dc:title><![CDATA[The Stanford Dependency Relations for Commonsense Knowledge Representation of Winograd Schema Challenge (WSC)]]></dc:title><dc:creator>Nesreen  Alsharman</dc:creator><dc:creator>Raja  Masadeh</dc:creator><dc:creator>Ibrahim Ali Jawarneh</dc:creator><dc:creator>Ahmad  Al-Rababa’a</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1091.1098</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-07-10; | doi:10.3844/jcssp.2024.1091.1098</dc:source>
    <dc:date>2024-07-10</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1091.1098</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1091.1098</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1099.1109">
    <title><![CDATA[The User Experience Analysis of Digital Health Tracking Application in Indonesia]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1099.1109</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 9 July 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1099.1109">doi:10.3844/jcssp.2024.1099.1109</a></p>Indonesia has an application for health tracking called SATUSEHAT. This application is used to search for hospitals, record vaccine data, and all functions related to public health. This application w...]]></content:encoded>
    <dc:title><![CDATA[The User Experience Analysis of Digital Health Tracking Application in Indonesia]]></dc:title><dc:creator>Sugiarto  Hartono</dc:creator><dc:creator>Henricus Bambang Triantono</dc:creator><dc:creator>Hendri  Hartono</dc:creator><dc:creator>Muhammad Henry Sulistyo</dc:creator><dc:creator>Faizah  Shahudin</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1099.1109</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-07-09; | doi:10.3844/jcssp.2024.1099.1109</dc:source>
    <dc:date>2024-07-09</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1099.1109</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1099.1109</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1110.1120">
    <title><![CDATA[Mapping Learning Algorithms on Data, a Useful Step for Optimizing Performances and Their Comparison]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1110.1120</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 10 July 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1110.1120">doi:10.3844/jcssp.2024.1110.1120</a></p>In this paper, we propose a novel methodology to map learning algorithms on data (performance map) in order to gain more insights into the distribution of their performances across their parameter spa...]]></content:encoded>
    <dc:title><![CDATA[Mapping Learning Algorithms on Data, a Useful Step for Optimizing Performances and Their Comparison]]></dc:title><dc:creator>Filippo  Neri</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1110.1120</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-07-10; | doi:10.3844/jcssp.2024.1110.1120</dc:source>
    <dc:date>2024-07-10</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1110.1120</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1110.1120</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1121.1145">
    <title><![CDATA[Mitigating Privacy and Security Risks in the Era of Big Data: A Comprehensive Framework of Best Practices and Protocols]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1121.1145</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 13 July 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1121.1145">doi:10.3844/jcssp.2024.1121.1145</a></p>Addressing the intricate challenges of security and privacy in big data necessitates a focused research approach toward the development of innovative frameworks, protocols and algorithms. This study a...]]></content:encoded>
    <dc:title><![CDATA[Mitigating Privacy and Security Risks in the Era of Big Data: A Comprehensive Framework of Best Practices and Protocols]]></dc:title><dc:creator>Uma  Narayanan</dc:creator><dc:creator>Nithin Puthiya Veettil</dc:creator><dc:creator>Ratheesh Thottungal Krishnankutty</dc:creator><dc:creator>Leya Elizabeth Sunny</dc:creator><dc:creator>Varghese  Paul</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1121.1145</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-07-13; | doi:10.3844/jcssp.2024.1121.1145</dc:source>
    <dc:date>2024-07-13</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1121.1145</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1121.1145</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2024.1146.1165">
    <title><![CDATA[A Comparative Analysis of Smote and CSSF Techniques for Diabetes Classification Using Imbalanced Data]]></title>
    <link>https://thescipub.com/jcs/jcssp.2024.1146.1165</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 22 July 2024; <a href="https://thescipub.com/jcs/jcssp.2024.1146.1165">doi:10.3844/jcssp.2024.1146.1165</a></p>Diabetes, a prevalent chronic metabolic disorder, poses a significant burden on healthcare systems worldwide. Accurate and timely diagnosis is crucial for effective management and complication prevent...]]></content:encoded>
    <dc:title><![CDATA[A Comparative Analysis of Smote and CSSF Techniques for Diabetes Classification Using Imbalanced Data]]></dc:title><dc:creator>Bashar Hamad Aubaidan</dc:creator><dc:creator>Rabiah Abdul Kadir</dc:creator><dc:creator>Mohamad Taha Ijab</dc:creator><dc:identifier>doi:10.3844/jcssp.2024.1146.1165</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2024-07-22; | doi:10.3844/jcssp.2024.1146.1165</dc:source>
    <dc:date>2024-07-22</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2024.1146.1165</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2024.1146.1165</prism:url>
    </item></rdf:RDF>