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Journal : Jurnal Sains Teknologi dan Sistem Informasi

 1 
Klasifikasi Rambut Rontok Menggunakan Metode Naive Bayes Arif Hidayat; Sutedi, Sutedi
SATESI: Jurnal Sains Teknologi dan Sistem Informasi Vol. 5 No. 2 (2025): Oktober 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian ALGERO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/satesi.v5i2.5612

Abstract

Hair loss is a common problem experienced by various groups, both men and women. In 2023, a survey found that 64.7% of hair problems were hair loss, followed by dandruff, dry hair, dull hair, limp hair, and oily hair. The causes of hair loss are diverse, ranging from genetic and hormonal factors to lifestyle. To accurately identify and classify the types of hair loss, a method is needed that can handle data efficiently and accurately. This study aims to classify types of hair loss using the Naive Bayes method, a classification algorithm in data mining based on probability and Bayes' theorem. The data used consists of various attributes such as staying up late, brain activity duration, stress levels, dandruff, and hormones. The Naive Bayes method was chosen because of its ability to handle data with a large number of attributes and produce fairly accurate predictions even with the assumption of independence between features. The results of the study show that the Naive Bayes method is capable of classifying types of hair loss with an accuracy rate of 76.67%. These findings indicate that this method can be used as a tool to aid in the rapid and efficient initial diagnosis of hair loss problems.
Co-Authors - Nurfiana Absor, M Ulil Adam Japal Adela, Cindy Nada Agariana, Melda Agarina , Melda Agung Nugroho Menggala Putra AGUS PURWANTO Anton Catur Atmoko Ardiansyah, Ari ARIF HIDAYAT Arman Suryadi Karim, Arman Suryadi DANU WIJAYA Diba Madya Margerefti Dona Yuliawati Edi Edi Pranyoto Fauzi Maulana, Muh Royan Fauzi, M.Royan Firdhayanti, Ayu Firmansyah Firmansyah Firmansyah Yunialfi Alfian Guntur Guntur Halimah Halimah handoyo widi nugroho Hartono Hartono Hasibuan, Said Hendra Kurniawan Hendri Purnomo Hendri Purnomo Ilhamiharja, Arbi Irianti , Artia Kaesar Azra Putra Zeva Kesuma, Martika Kurniawan, Putra Lestari, Mentari Puji Luh Putu Ratna Sundari M Said Hasibuan M Ulil Absor M. Royan Fauzi M.Ariza M.Royan Fauzi M.Royan Fauzi Maulana Maarif, Syaiful Mahfudzin, Abdul Halim Maulana, Muh Royan Fauzi Melda Agarina MS Hasibuan MUBAAROK, ABDURRAHMAN Muhamad Ariza Eka Yusendra Muhammad Ariza Eka Yusendra Nirma Nirma Nirmala Handayani Nirmala Handayani Ochi Marshella Febriani rinaldi rinaldi Rinaldo, Reyhandoni Rini Nurlistiani Risa Ayuna Sari, Erlinda Ratna Sri Karnila Sriyanto . Sriyanto Sriyanto Sriyanto Sriyanto Stefanus Rumangkit Suryadi , Arman Susanti Susanti Susanti Susanti Susanti Tria Devi Miranti Triloka, Joko Ubaidilah, Romdan Muhamad Wasilah Wasilah Yusminar Yusminar