Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Abdi Insani International Journal of Artificial Intelligence in Medical Issues
Paramitha, Arimbi Tiara
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Dentistry Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Public Health

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Predictive Modelling of Chronic Kidney Disease Using Gaussian Naive Bayes Algorithm Azizah, Muthia Febriana; Paramitha, Arimbi Tiara
International Journal of Artificial Intelligence in Medical Issues Vol. 2 No. 2 (2024): International Journal of Artificial Intelligence in Medical Issues
Publisher : Yocto Brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijaimi.v2i2.160

Abstract

Chronic Kidney Disease (CKD) is a critical global health issue, characterized by significant morbidity and mortality. Early detection is vital for effective management and improved patient outcomes. This study explores the application of the Gaussian Naive Bayes algorithm to predict CKD using a comprehensive dataset from Kaggle, comprising health information from 1,659 patients. The research involves detailed data pre-processing, including feature selection, data scaling, and an 80/20 split for training and testing. The model's performance was evaluated using 5-fold cross-validation, resulting in an average accuracy of 89.93%, precision of 88.15%, recall of 89.93%, and F1-score of 88.42%. These metrics highlight the model's robustness and reliability in identifying CKD cases. Visualizations such as correlation heatmaps, 3D PCA, and t-SNE plots were used to understand feature relationships and data distribution. The results confirm the hypothesis that Gaussian Naive Bayes can effectively predict CKD, providing a reliable tool for early diagnosis. This study contributes to the medical field by demonstrating the utility of machine learning in improving diagnostic accuracy. However, limitations such as dataset biases and the need for comparison with other algorithms are acknowledged. Future research should focus on expanding the dataset, incorporating more features, and exploring additional machine learning models to enhance predictive performance and generalizability. Practical implications suggest that integrating such models into clinical practice could significantly improve patient management and outcomes.
MODEL PELATIHAN HYBRID BERBASIS WEBSITE UNTUK PENINGKATAN LITERASI INTERNET SEHAT DAN AMAN BAGI SISWA SMP NEGERI 12 MAKASSAR Yusri, Iin Karmila; Thamrin, Yahya; Prasetyo, Pulung Hendro; Agung, Ismi Batara; Paramitha, Arimbi Tiara; Pratama, Muh. Herlan
Jurnal Abdi Insani Vol 13 No 1 (2026): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v13i1.3450

Abstract

Perkembangan teknologi digital yang pesat membawa dampak positif sekaligus tantangan baru bagi remaja, terutama dalam menjaga kesehatan fisik, mental, dan keselamatan saat beraktivitas di dunia maya. Kurangnya kesadaran terhadap penggunaan internet yang sehat dan aman juga sering dipengaruhi oleh minimnya dukungan lingkungan sekolah dan keluarga. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan literasi digital sehat dan aman melalui model pelatihan hybrid berbasis website edukasi “sipakainga.com” yang melibatkan siswa, guru, dan orang tua siswa SMP Negeri 12 Makassar. Metode pelaksanaan terdiri atas pelatihan tatap muka dan pembelajaran daring melalui tiga jenis modul edukasi (modul siswa, modul guru, dan modul orang tua). Evaluasi dilakukan menggunakan pre-test dan post-test terhadap siswa, serta observasi dan wawancara terhadap guru dan orang tua. Sebanyak 32 siswa, 10 guru, dan 15 orang tua berpartisipasi aktif dalam kegiatan ini. Hasil analisis menunjukkan adanya peningkatan rata-rata nilai pengetahuan siswa dari 75,34 menjadi 76,43 dengan tingkat pertumbuhan (growth rate) sebesar 1,45%. Walaupun peningkatan ini belum signifikan secara statistik (p = 0,14), kegiatan ini mendorong perubahan perilaku positif pada siswa dalam penggunaan gawai, serta meningkatkan peran guru dan orang tua dalam pengawasan dan pembinaan digital anak. Program ini membuktikan bahwa model pelatihan hybrid berbasis website efektif dalam menumbuhkan kesadaran dan kolaborasi antara sekolah dan keluarga untuk menciptakan budaya digital yang sehat, aman, dan berkelanjutan.
Co-Authors Agung, Ismi Batara Azizah, Muthia Febriana Prasetyo, Pulung Hendro Pratama, Muh. Herlan Yahya Thamrin Yusri, Iin Karmila