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All Journal International Journal of Artificial Intelligence Research JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Vocatech : Vocational Education and Technology Journal JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Engineering, Science and Information Technology TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Bangun Abdimas Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Jurnal Solusi Masyarakat Dikara
Fadlisyah Fadlisyah
Universitas Malikussaleh
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Journal : Journal of Advanced Computer Knowledge and Algorithms

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Independent Campus Student Exchange Sentiment Analysis Using SVM Irhami, Putri; Darnila, Eva; Fadlisyah, Fadlisyah
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 2 (2024): Journal of Advanced Computer Knowledge and Algorithms - April 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i2.14902

Abstract

Support Vector Machine (SVM) is a machine learning method that is widely used for regression and classification problems, especially application review classification. Student exchange is one of the programs that universities must prepare. The student exchange program is intended to reduce the problem of disparities in educational facilities and infrastructure in Indonesia. The advantage of student exchange is that they can manage their time, have high awareness in communicating, are able to admit when they experience problems and need help, independent student exchange offers study options of up to 20 credits, both covering Higher Education Recipients courses and activities in the form of the Nusantara Module. Additionally, students are offered the option to register for a maximum of 6 credits of higher education online. The method used in this research is the SVM algorithm, the dataset used consists of 1000 comment reviews with a ratio of 70;30. This research was implemented in a web system using the Python programming language. Of the 300 test data implemented with 700 training data. The Support Vector Machine (SVM) algorithm in classifying review data obtained the highest accuracy in dividing training data & test data 70:30 at 85.00% then precision 28.33%, recall 33.33%
Classification of Asthma Diseases Using Machine Learning Models at Arun Hospital Muqarrabin, Khalis Al; Fadlisyah, Fadlisyah; Safari, T Mirzal
Journal of Advanced Computer Knowledge and Algorithms Vol. 2 No. 2 (2025): Journal of Advanced Computer Knowledge and Algorithms - April 2025
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v2i2.21229

Abstract

Asthma is one of the chronic diseases that significantly affects the quality of life of patients. This study aims to classify asthma disease based on patient data from Arun Hospital using the K-Nearest Neighbor (KNN) algorithm. The dataset consists of 330 patient data with attributes such as allergy, itchy throat, and shortness of breath. The data went through preprocessing, transformation, and normalization stages. The KNN model was tested with a value of k = 3, resulting in three main classifications: Mild Asthma, Moderate Asthma, and Severe Asthma. The evaluation results showed a high accuracy rate, with an average of more than 90%. In addition, the model was implemented in the form of a system that visualizes the dataset, KNN analysis, and model evaluation. These findings demonstrate the potential of the KNN algorithm to provide accurate predictions and support the diagnosis of asthma disease effectively.
Co-Authors Adani, Safira Alfi Fauzi Alfyansyah, Gusti Altharizka, Muhammad Aldonny Alzaky, Muammar Aris Munandar Aris Munandar Arnawan Hasibuan Aryandi Aryandi Aryandi, Aryandi Asmi, Nurul Annisa Asmirayani Asmirayani Asmirayani, Asmirayani Aulia Barus, M Farhan Azzahra, Dea Bustami Bustami Bustami Bustami Cindenia Puspasari Cut Ita Erliana Cut Lika Mestika Sandy Dahlan Abdullah Dea Azzahra Dessayani Putri Eva Darnila Fahrozi, Mahlil Fajriana Fajriana Fajriana, Fajriana Fasdarsyah Fasdarsyah Fauzi, Alfi Fuadi, Wahyu Gusti Alfyansyah Gusti Alfyansyah Hamdhana, Defry Hamdhana, Defry Intan Nuriani Ira Safira Irhami, Putri Irma Mauliza Irwansyah, Defi Jalaluddin Jalaluddin Jalaluddin Jalaluddin Kamarullah Kamarullah Kamilaini Kamilaini Kamilaini, Kamilaini Lidya Rosnita Mara Wahyu Alamsyah Pane Maryana Maryana Maryana Maryana Maryana Maryana, Maryana Mauliza, Irma Muammar Alzaky Muhammad Aldonny Altharizka Muhammad Fikry Muhammad Rivai Muhathir Muhathir Muhathir, Muhathir Muhathir, Muhathir Muhathir, Muhathir Mukti Qamal Mukti Qamal Muqarrabin, Khalis Al Mutammimul Ula Nasriah Nasriah Nasriah Nasriah Nisak, Rahmatin Noor, Fredy Nurdin Nurdin Nurdin Nurdin Nurdin Nurdin Nuriani, Intan Nuriani, Intan Pradita, Cindy Cika Putri, Dessayani Putri, Husna Moetia Reyhan Achmad Rizal Riansyah, Muhammad Risawandi, Risawandi Rizal Rizal Rizal Rizal Rizal S.Si., M.IT, Rizal Rofiq Harun Rozzi Kesuma Dinata Safari, T Mirzal Safira Adani Safwandi Safwandi Safwandi Safwandi, Safwandi Said Fadlan Anshari Sari, Putri Amelia Sayed Fachrurrazi Siregar, M. Ali Akbar Sujacka Retno Syahputra, Dinur Syahrial Syahrial SYAHRIAL SYAHRIAL Taufik Ismail Simanjuntak Taufiq Taufiq Uliana, Lisa Wahyu Fuadi Widari, Liz Ayu Yasir Amani Yesy Afrillia Zara Yunizar Zarkasyi, Zarkasyi Zuhra, Elviza