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All Journal Pendidikan Administrasi Perkantoran FENOMEN IJOG : Indonesian Journal on Geoscience JUPE Journal of Contemporary Indonesian Art Habitat Jurnal Varidika Benefit: Jurnal Manajemen dan Bisnis Jurnal Teknik Industri : Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri EXTRAPOLASI: Jurnal Teknik Sipil Indonesian Treasury Review: Jurnal Perbendaharaan, Keuangan Negara dan Kebijakan Publik Jurnal Pariwisata Terapan Al-Ard: Jurnal Teknik Lingkungan Jurnal Ilmiah Hijau Cendekia Ge-STRAM: Jurnal Perencanaan dan Rekayasa Sipil Journal of Robotics and Control (JRC) Jurnal Ilmiah Profesi Pendidikan International Journal of Industrial Optimization (IJIO) Infotech: Journal of Technology Information Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) International Journal of Business, Law, and Education Abdi Masya Nusantara Hasana Journal Extrapolasi GANESHA: Jurnal Pengabdian Masyarakat Premium: Insurance Business Journal Jurnal Ilmu-Ilmu Kehutanan NEAR: Jurnal Pengabdian kepada Masyarakat Journal of Artificial Intelligence and Digital Business eProceedings of Engineering VISA: Journal of Vision and Ideas Indonesian Journal of Forestry Research Sunan Kalijaga Journal of Physics INTECH (Informatika dan Teknologi) Journal of Production, Enterprise, and Industrial Applications
Wiyono wiyono
Jurusan Teknik Elektro Universitas Brawijaya
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Journal : Infotech: Journal of Technology Information

 1 
OPTIMALISASI KLASIFIKASI UJI EMISI SEPEDA MOTOR MENGGUNAKAN ALGORITMA NAÏVE BAYES Irwansyah, Irwansyah; Dittyata, Rizki; Rizal, Rizal; Wiyono, Wiyono
Infotech: Journal of Technology Information Vol 10, No 2 (2024): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v10i2.327

Abstract

Dense urban areas with high levels of industrial and transportation activity result in increased air pollutant emissions that threaten air quality and the health of their residents. The issue is the lack of utilization and optimization of motorcycle emission test classification through a machine learning approach. This research aims to utilize motorcycle emission test data and to determine the accuracy, precision, and recall results of the naive Bayes algorithm. The number of datasets used by the researchers is 2409 data points. Based on this data, it is divided into two parts: training data consisting of 1927 data points (80%) and testing data consisting of 482 data points (20%). The results of the motorcycle emission test data can be utilized for classification optimization, and the naive Bayes algorithm can be applied to classify and analyze the accuracy, precision, and recall results of the motorcycle emission test data. The accuracy result is 91.49%, the precision result for the pass classification is 93.72%, and the precision result for the fail classification is 83%, while the recall result for the pass classification is 95.47% and the recall result for the fail classification is 77.57%.      ABSTRAK Daerah perkotaan yang padat penduduk dengan tingkat aktivitas industri dan transportasi yang tinggi mengakibatkan peningkatan emisi polutan udara yang mengancam kualitas udara dan kesehatan warganya. Permasalahan belum  adanya pemanfaatan dan optimalisasi klasifikasi uji emisi sepeda motor melalui pendekatan machine learning. Penelitian ini bertujuan untuk memanfaatkan data uji emisi sepeda motor dan untuk mengetahui  hasil akurasi, presisi, dan recall dari algoritma naïve bayes. Adapun jumlah dataset yang peneliti gunakan sebanyak 2409 data. Berdasarkan data tersebut dibagi menjadi dua yaitu data training sebanyak 1927 data (80%) dan data testing sebanyak 482 data (20%). Hasil penelitian data uji emisi sepeda motor dapat dimanfaatkan untuk optimalisasi klasifikasi dan algoritma naïve bayes dapat diterapkan dalam mengklasifikasi dan menganalisis hasil akurasi, presisi, dan recall dari data uji emisi sepeda motor. Adapun hasil akurasinya sebesar sebesar 91,49%, hasil precision klasifikasi lulus sebesar 93,72% dan hasil precision klasifikasi tidak lulus sebesar 83%, dan hasil recall klasifikasi lulus sebesar 95,47% dan hasil recall klasifikasi tidak lulus sebesar 77,57%.
Co-Authors Abdul Hafidz Achmad Fatchul Aziez Achmad Nurmandi Ade Jubaedi Agus Budiyono Akin, Özgenç Akin, Özgenç Al Mahfuz, Al Mahfuz Alfatih, Zhilan Zhalilla Puti Alhafi, Azwar Najib Alifah, Maulida Amalia, Atika Amir Hamzah Andika, Putu Pradnya Andriyani, Diana Arensi, Niken Arif Cahyanto Arif Hidayatullah, Arif BAMBANG SUJATMIKO Bangsa, Vanessa Bunga Barnes, Ahmad Bela Pitria Hakim Budiarta Cantikasari, Yuliana DARYANTI DARYANTI Denni Susanto Denny Sukma Eka Atmaja Dewi, Amina Sukma Dittyata, Rizki Dwi Susilo Utami Endang Budiasih Endang Sulastri Endang Suprapti Epan Chaidir Fatihah, Syalaysa Imani Febrianita, Maya Fitihatussiriyah, Fitihatussiriyah Hadi Susanto Handoyo Handoyo Haq, Mellanie Nadya Azmi Haris Rachmat Harmani, Evy Harmani, Evy Heri Kustanto Hidayat, Rochmad Hidayati , Diyah Nur HIDAYATI, MIFTAKHUL Ilis, N Imam Setyo Nugroho Indah Nofitasari Irwansyah Irwansyah Juwita, Mega Maduratna Karsono Karsono Koesmantoro, Hery Kunanti, Rahmi Anugrah Leo, Andi Lilipaly, Maria Ruthy Hillary Listariyanto, Adwityam Padma Putra Lujeng Widodo, Lujeng Maharani, Annissa Tiara Majlani, Majlani Moh. Erkamim Muhammad Ridho Muhammad Rivai Murman Dwi Prasetio Nariyanti, Lucianna Putri Nugraha, Aditya Prawira Nugrahaini, Yunita Oktalina, Silvi Nur OKTI PURWANINGSIH Paiman Paiman Pataropura, Amesanggeng Puspita, Mayang Bunga Rahmat Hermawan Ramadhani, Argia Putri Ramdani, Aziz Ramdhani, Muhammad Rizki Rizal Rizal Roedy Kristiyono, Roedy Rohmatulloh, Hafizhudin Romadhona, Maya Rosa Ruchimat, Acep Rudiana, Sarah Aulia Ruhimat, Acep Rumengan, Riko Febrian Santoso, Probo Sari, Sri Mardhika Setie Harieni Sheila Amalia Salma Sigalingging, Asido Saputra Sihaloho, Miranda Cahaya Rembulan Br Sihombing, Rusman Efendi Siti Mardhika Sari SKD, Tyas Soelistijono , R Soemarah KD , Tyas Sony Meidiansyah Sopian sopian Sri Herwiningsih Subejo Sulistiyawati, Anggun SUMARAH KD, TYAS Sunaryo Sunaryo Suswara, Naufal Lathief Suwandi, Jessen Laorenza Suyanto, Beny Syahna A, Fayza Teguh Supriyadi Usman Adam Wardani, Qurrotul Ain Putri Kusuma Wijaya, Ardie Halim Witjaksono, Bambang Xavier, Rais Yufli Yusuf Kurnia, Yusuf