Influence of Logistic Regression Models For Prediction and Analysis of Diabetes Risk Factors

  • Yufri Isnaini Rochmat Maulana Politeknik Elektronika Negeri Surabaya
  • Tessy Badriyah Politeknik Elektronika Negeri Surabaya
  • Iwan Syarif Politeknik Elektronika Negeri Surabaya
Keywords: diabetes, logistic regression, mobile, framework


Diabetes is a very serious chronic. Diabetes can occurs when the pancreas doesn't produce enough insulin (a hormone used to regulate blood sugar), cause glucose in the blood to be high. The purpose of this study is to provide a different approach in dealing with cases of diabetes, that's with data mining techniques mengguanakan logistic regression algorithm to predict and analyze the risk of diabetes that is implemented in the mobile framework. The dataset used for data modeling using logistic regression algorithm was taken from Soewandhie Hospital on August 1 until September 30, 2017. Attributes obtained from the Hospital Laboratory have 11 attribute, with remove 1 attribute that is the medical record number so it becomes 10 attributes. In the data preparation dataset done preprocessing process using replace missing value, normalization, and feature extraction to produce a good accuracy. The result of this research is performance measure with ROC Curve, and also the attribute analysis that influence to diabetes using p-value. From these results it is known that by using modeling logistic regression algorithm and validation test using leave one out obtained accuracy of 94.77%. And for attributes that affect diabetes is 9 attributes, age, hemoglobin, sex, blood sugar pressure, creatin serum, white cell count, urea, total cholesterol, and bmi. And for attributes triglycerides have no effect on diabetes.


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Author Biographies

Yufri Isnaini Rochmat Maulana, Politeknik Elektronika Negeri Surabaya

Postgraduated Student at Electronic Engineering Polytechnic Institute of Surabaya

Department of Informatics Engineering

Tessy Badriyah, Politeknik Elektronika Negeri Surabaya

Postgraduated Lecturer at Electronic Engineering Polytechnic Institute of Surabaya

Department of Informatics Engineering

Iwan Syarif, Politeknik Elektronika Negeri Surabaya

Postgraduated Lecturer at Electronic Engineering Polytechnic Institute of Surabaya

Department of Informatics Engineering


Prayitno, Agus, Wibawa, Andi Dharma, Purnomo, Mauridhi, Hery. “Early Detection Study of Kidney Organ Complication Caused By Diabetes Mellitus using Iris Image Color Constancyâ€. International Conference of Information, Communication Technology and System (ICTS), 146 - 149, 2016

Basar, Md Abul, Alvi, Hassan Nomani, Bokul, Gazi Nowrin, Khan M, Shahriar, Anowar, Farzana, Huda, Mohammad Nurul, Al Mamun, Khondaker Abdullah. “A Review on Diabetes Patient Lifestyle Management Using Mobile Applicationâ€. 18th International Conference on Computer and Information Technology, 379 - 385, 2015

S. Goyal and J. a. Cafazzo. “Mobile phone health apps for diabetes management: Current evidence and future developmentsâ€. Qjm vol. 106, no. 12, pp. 1067–1069, 2013

George, Eleni I, Protopappas, Vasilios C, Mougiakakou, Stavroula G. “Short-term vs. Long-term Analysis of Diabetes Data: Application of Machine Learning and Data Mining Techniquesâ€. 2013

Ojugo, A A, Eboka, A O, Yoro, R E, Yerokun, M O, Efozia, F N. “Hybrid Model for Early Diabetes Diagnosisâ€. Second International Conference on Mathematics and Computers in Science and in Industry, 55 - 64, 2015

Srikanth, Panigrahi, Deverapalli, Dharmaiah. “A Critical Study of Classification Algorithms Using Diabetes Diagnosticsâ€. IEEE 6th International Conference on Advanced Computing, 245 - 249, 2016

Tulu, B et al. “Design Implications of User Experience Studies The Case of a Diabetes 9Wellness Appâ€. 49th Hawaii Internasional Conference on System Sciences, p. 3437 – 3482, 2016

Pagoto, S, Schneider K, Jojic M, DeBiasse M, and Mann D. “Evidence- based strategies in weight-loss mobile appsâ€. American journal of preventive medicine, 45, (5), p. 576-582 , 2013

Siahaan, Elisa Julie Irianti, Cholissodin, Imam, Fauzi, M. Ali. “Sistem Rekomendasi Bahan Makanan Bagi Penderita Penyakit Jantung Menggunakan Algoritma Genetikaâ€. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol. 1 No. 11, 1406 - 1415, 2017

Wicaksono, Andri Permana, Badriyah, Tessy, Basuki, Ahmad. “Comparison of The Data-Mining Methods in Predicting The Risk Level of Diabetesâ€. EMITTER International Journal of Engineering Technology, Vol. 4 No. 1, 2016

M. Cable. “Mobile Diabetes Management Toolsâ€. no. November, pp. 24–26, 2011.

Douali, Nassim, Dollon, Julien, Jaulent, Marie-Christine. “Personalised Prediction of Gestational Diabetes Using a Clinical Decision Support Systemâ€. IEEE, 2015

Sevani, Nina. “Personal Health Care Framework for Childrenâ€. International Conference on Data and Software Engineering, 166 - 170, 2015

(14) Salman, Galih Afan, Prasetio, Yen Lina, Kanigoro, Bayu, Anggi. “Aplikasi Rekomendasi Pola Makan Berbasis iOSâ€. ComTech Vol. 3 No. 2, 796 – 807, 2012

Al-Nazer,Ahmed,Helmy,Tarek,andAl-Mulhem,Mohammed.“User’s Profile Ontology-Based Semantic Framework for Personalized Food and Nutrition Recommendationâ€. Procedia Computer Science 32, 101 – 108, 2014

Tang, Y Y, Zhang, Bob, Shu, Ting. “Using k-NN With Weights To Detect Diabetes Mellitus Based On Genetic Algorithm Feature Selectionâ€. Proceding of the 2016 Internasional Conference on Wavelet Analysis and Pattern Recognition, 2016

Al-Taee,MajidA,Al-Nuaimy,Waleed.,Al-Ataby,Ali,Muhsin,andZahra J. “Mobile Health Platform for Diabetes Management Based on the Internet-of Thingsâ€. IEEE Jordan Conference on Applied Electrical Engineesing and Computing Technologies (AEECT), 2015

Perez,JavierAndreu.,Leff,DanielR,IpHMD,andYang,Guang-Zhong. “From Wearable Sensors to Smart Implants – Towards Pervasive and Personalised Healthcareâ€. IEEE, 2015

Blount, M. et al. “Remote Healthcare Monitoring Using Personal Care Connectâ€. IBM Systems Journal Vol. 46, No. 1, 2017

Rahman,RuhaniAb,Aziz,NurShimaAbdul,Yusof,MatIkanetal.“IoT- based Personal Health Care Monitoring Device for Diabetics Patiensâ€. IEEE, 2017

Kotimah, Muinah Kusnul, dan Wulandari, Sri Pingit. “Model Regresi Logistik Biner Stratifikasi Pada Partisipasi Ekonomi Perempuan Di Provinsi Jawa Timurâ€. Jurnal Sains dan Seni Pomits, Vol. 3, No. 1, 2014

Al-Nazer, Ahmed, Helmy, Tarek, and Al-Mulhem, Mohammed. “Analisis Klasifikasi Kredit Menggunakan Regresi Logistik Biner Dan Radial Basis Function Network di Bank “X†Cabang Kediriâ€. Jurnal Sains dan Seni Pomits, Vol. 3, No. 2, 2014

Aditya, Ahmad Reza, Suparti, Sudarno. “Ketepatan Klasifikasi Pemilihan Metode Kontrasepsi Di Kota Semarang Menggunakan Bootstrap Aggregating Regresi Logistik Multinomialâ€. Jurnal Gaussian, Volume 3, Nomor 1, 2015

Maharani,IndahIrma,Hardinsyah,danSumantri,Bambang.“Aplikasi Regresi Logistik Dalam Analisis Faktor Risiko Anemia Gizi Pada Mahasiswa Baru IPBâ€. Jurnal Gizi dan Pangan, 36 - 43, 2007

D, Hosmer, & S, Lemeshow. “Aplied Logistic Regressionâ€. USA: John Wliey & Sons, 2000

How to Cite
Maulana, Y. I. R., Badriyah, T., & Syarif, I. (2018). Influence of Logistic Regression Models For Prediction and Analysis of Diabetes Risk Factors. EMITTER International Journal of Engineering Technology, 6(1), 151-167.