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All Journal Dinamik Techno.Com: Jurnal Teknologi Informasi JSI: Jurnal Sistem Informasi (E-Journal) CESS (Journal of Computer Engineering, System and Science) Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Journal of Information System, Applied, Management, Accounting and Research International Journal of Informatics and Computation JATI (Jurnal Mahasiswa Teknik Informatika) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Sistem Informasi dan Sains Teknologi Jurnal Teknologi Informatika dan Komputer Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Bulletin of Information Technology (BIT) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Joong-Ki : Jurnal Pengabdian Masyarakat Joutica : Journal of Informatic Unisla Journal of Practical Computer Science (JPCS) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Malcom: Indonesian Journal of Machine Learning and Computer Science Riwayat: Educational Journal of History and Humanities VIDHEAS: Jurnal Nasional Abdimas Multidisiplin SAINTEK Joong-Ki JPMAS : Jurnal Pengabdian Masyarakat Dedikasi : Jurnal Pengabdian Lentera RECORD Journal of Loyality and Community Development Jurnal ilmiah teknologi informasi Asia Joong-Ki
Agung Nugroho
Universitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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Journal : Bulletin of Information Technology (BIT)

 1 
Analisa Data Mining Untuk Prediksi Penyakit Ginjal Kronik Dengan Algoritma Regresi Linier Angga Kurniadi Hermawan; Agung Nugroho; Edora
Bulletin of Information Technology (BIT) Vol 4 No 1: Maret 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i1.475

Abstract

In this study, we evaluate the ability of data mining to predict chronic kidney disease using a linear regression algorithm. We extract features from patient clinical data and apply a linear regression algorithm to build a predictive model. The results showed that our linear regression model was able to predict with high accuracy and could be used as an aid in diagnosing chronic kidney disease. In addition, we also analyze the factors that influence the risk of developing chronic kidney disease and suggest preventive measures that can be taken to reduce the risk of developing the disease. The results of this study can be used by doctors to improve efficiency in diagnosing and preventing chronic kidney disease. In addition, these results can also be used as a basis for further research in the field of data mining and chronic kidney disease. The process of testing the data in this study using a linear regression algorithm is able to provide good results with a Root Mean Squared Error: 0.285 +/- 0.000 and Squared Error: 0.081 +/- 0.234.
Prediksi Penyakit Kanker Paru-Paru Dengan Algoritma Regresi Linier Muhammad Abdul Rahman Wahid; Agung Nugroho; Abdul Halim Anshor
Bulletin of Information Technology (BIT) Vol 4 No 1: Maret 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i1.501

Abstract

Lung cancer is one of the deadliest types of cancer worldwide. Therefore, efforts to predict the likelihood of developing lung cancer are very important in its prevention and treatment. One way to predict the likelihood of getting lung cancer is to use a linear regression algorithm. This study aims to develop a predictive model that can identify a person's likelihood of developing lung cancer based on certain factors, such as age, passive smoker and level or severity. The data used in this study were collected from 100 patients diagnosed with lung cancer and their severity. The results of the analysis show that the linear regression algorithm can be used to predict the probability of getting lung cancer with an accuracy of about 90% and is able to give good results with a Root Mean Squared Error: 0.686 +/- 0.000 and Squared Error: 0.471 +/- 0.546
Co-Authors Abdul Halim Anshor Adi Kusuma Adi Kusuma Afrizal Ardiansyah Agus Suwarno, Agus Ahmad Rivaldi Ahmad Santoso Ahmad Turmudi Zy Ahmad Turmudi Zy Ahmad Turmudi Zy Al Abdilah, M. Akmal Alfatan Dzulatkha Alviyan, Eric Ananto Tri Sasongko Angga Kurniadi Hermawan Ansor, Abdul Halim Ari Maulana Arif Tri Widiyatmoko Aswan S Sunge Aswan Supriyadi Sunge Ayu Indriyanti Bima Randy Gumilang Butsianto, Sufajar Chandra, Ahmad Alfian Donny Maulana Edora Elkin Rilvani Endrik Fauzi Ahmad Muda Fitri, Retno Ike Yunia Pasa Ikhsan Romli Ilyas, Abdi Irfan Afriantoro Jamaludin Jamaludin Karsito Londong, Riko Reky Maulana, Donny Muhammad Abdul Rahman Wahid Muhammad Rizki Sani Nisa, Khilyatun Nur Hidayati Nur Hidayati Nurjeli Nurjeli Priatna , Wowon Rusdi, Adi Salman Alfaridzi Sasongko, Ananto Tri Septiawan Dwi Pramukti Supriadi, Asmadi Tiaraningsih Turmudi Zy, Ahmad Wahyono Wahyono Wahyu Hadikristanto Widiyatmoko, Arif Tri Wiyanto Wiyanto Wiyanto - Wiyanto Wiyanto Wiyanto, Wiyanto Yoga Religia