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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) International Journal of Engineering, Science and Information Technology
Muhammad Eka Suryana
Universitas Negeri Jakarta
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Membandingkan Pengaruh Feature Selection Terhadap Algoritma Naïve Bayes dan Support Vector Machine Aldi Rahmansyah; Ovitasari Dewi; Puti Andini; Trisna Hastuti Puspita Ningrum; Muhammad Eka Suryana
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2018
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Abstract

Feature selection menjadi perhatian di banyak bidang penelitian yang menggunakan machine learning, karena menyediakan pengklasifikasi untuk mempercepat proses, menghemat biaya dan meningkatkan akurasi. Pada penelitian ini kami menggunakan beberapa algoritma dengan menerapkan Algoritma Machine learning. Algoritma yang kami gunakan yaitu Support Vector Machine dan Naïve Bayes dengan sebelas features. Dan untuk mempermudah penerapannya di dunia nyata kami juga melakukan feature selection dengan harapan mengurangi features yang digunakan. Hasil yang kami dapatkan adalah pengaruh feature selection terbaik ada pada algoritma Naive Bayes yang mendapat nilai presisi dan recall 0.5 dan 0.52 yang sebelumnya adalah 0.455 dan 0.434. Sebaliknya pada Support Vector Machine, hasil terbaiknya adalah ketika semua feature digunakan tanpa ada yang dikurangi.
Web-Based Math Braille Translator Using Indonesian Braille Symbols Ari Hendarno; Andira Azzahra; Muhammad Eka Suryana
International Journal of Engineering, Science and Information Technology Vol 4, No 2 (2024)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i2.506

Abstract

According to estimates from the Indonesian Ministry of Health in 2017, at least 3,750,000 people in Indonesia have visual impairments. This significant number highlights the need for special attention to their educational needs, especially in mathematics. Educational media is essential to facilitate learning for visually impaired students and educators, as they often struggle with understanding math due to limited access to visual content. One solution is to use Mathematical Braille symbols, yet technology that translates these symbols into mathematical text is still limited. To address this, the author has developed a web-based Math Braille Translator application aimed at assisting visually impaired individuals and educators. This website translates mathematical Braille into notation by inputting Braille using the keys s, d, f, j, k, and l on the keyboard. The application is developed using the waterfall methodology and is based on the Indonesian Mathematical Braille Symbol Reference NOMOR 056/U/2000.
Co-Authors Aldi Rahmansyah Andira Azzahra Ari Hendarno Ovitasari Dewi Puti Andini Trisna Hastuti Puspita Ningrum