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All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) OKTAL : Jurnal Ilmu Komputer dan Sains
Nurhasanah Nurhasanah
Universitas Pamulang
Astronomy Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Social Sciences

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Implementasi dan Optimalisasi Metode Naive Bayes Dalam Sistem Deteksi Dini Penyakit Tiroid Nurhasanah, Nurhasanah; Asyiah, Nilovar; Irawati, Okta
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7940

Abstract

This study aims to develop an early detection system for thyroid disease using the Naive Bayes algorithm. The dataset used is the Thyroid Disease Dataset from the UCI Machine Learning Repository, consisting of thousands of patient records. Prior to model training, the data undergoes preprocessing steps such as handling missing values, numerical normalization, and categorical encoding. The classification process involves calculating the prior probability, likelihood, and posterior probability for each class: normal, hypothyroid, and hyperthyroid. The system also presents the probability percentage for each class as an automated diagnosis result. Model accuracy is evaluated using a Confusion Matrix, achieving an accuracy score of 98.01% on the test data. These results indicate that the proposed approach can effectively and accurately classify thyroid conditions for early diagnosis purposes.
Perancangan Sistem Pendukung Keputusan Untuk Menilai Kesiapan Siswa TK Dalam Masuk Sekolah Dasar Menggunakan Metode SAW Di TK Nurul Jannah Agung Firmansyah; Nurhasanah
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 02 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The process of assessing kindergarten students' readiness for elementary school at Nurul Jannah Kindergarten is still done manually, resulting in subjective and inconsistent results. This study aims to develop a web-based Decision Support System (DSS) using the Simple Additive Weighting (SAW) method to help teachers assess student readiness objectively and measurably. The system was developed using Extreme Programming (XP). This system uses five assessment criteria, which are then calculated through a process of normalization, weighting, and ranking. Implementation results indicate that the developed DSS produces more accurate, faster, and easier-to-understand assessments than manual methods, and assists teachers in determining student eligibility recommendations for elementary school entry
Co-Authors Agung Firmansyah Asyiah, Nilovar Okta Irawati