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

Yufri Isnaini Rochmat Maulana, Tessy Badriyah, Iwan Syarif


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.


diabetes; logistic regression; mobile; framework


(1) Prayitno, Agus, Wibawa, Andi Dharma, Purnomo, Mauridhi, Hery.

“Early Detection Study of Kidney Organ Complication Caused By Diabetes Mellitus using Iris Image Color Constancy”. International Conference of Information, Communication Technology and System (ICTS), 146 - 149, 2016

(2) 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 Application”. 18th International Conference on Computer and Information Technology, 379 - 385, 2015

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

(4) 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 Techniques”. 2013

(5) Ojugo, A A, Eboka, A O, Yoro, R E, Yerokun, M O, Efozia, F N. “Hybrid Model for Early Diabetes Diagnosis”. Second International Conference on Mathematics and Computers in Science and in

Industry, 55 - 64, 2015

(6) Srikanth, Panigrahi, Deverapalli, Dharmaiah. “A Critical Study of

Classification Algorithms Using Diabetes Diagnostics”. IEEE 6th

International Conference on Advanced Computing, 245 - 249, 2016

(7) Tulu, B et al. “Design Implications of User Experience Studies The Case of a Diabetes 9Wellness App”. 49th Hawaii Internasional

Conference on System Sciences, p. 3437 – 3482, 2016

(8) Pagoto, S, Schneider K, Jojic M, DeBiasse M, and Mann D. “Evidence- based strategies in weight-loss mobile apps”. American journal of

preventive medicine, 45, (5), p. 576-582 , 2013

(9) Siahaan, Elisa Julie Irianti, Cholissodin, Imam, Fauzi, M. Ali. “Sistem

Rekomendasi Bahan Makanan Bagi Penderita Penyakit Jantung Menggunakan Algoritma Genetika”. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol. 1 No. 11, 1406 - 1415, 2017

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

(11) M. Cable. “Mobile Diabetes Management Tools”. no. November, pp. 24–26, 2011.

(12) Douali, Nassim, Dollon, Julien, Jaulent, Marie-Christine.

“Personalised Prediction of Gestational Diabetes Using a Clinical

Decision Support System”. IEEE, 2015

(13) Sevani, Nina. “Personal Health Care Framework for Children”.

International Conference on Data and Software Engineering, 166 -

, 2015

(14) Salman, Galih Afan, Prasetio, Yen Lina, Kanigoro, Bayu, Anggi.

“Aplikasi Rekomendasi Pola Makan Berbasis iOS”. ComTech Vol. 3

No. 2, 796 – 807, 2012

(15) Al-Nazer,Ahmed,Helmy,Tarek,andAl-Mulhem,Mohammed.“User’s

Profile Ontology-Based Semantic Framework for Personalized Food and Nutrition Recommendation”. Procedia Computer Science 32, 101 – 108, 2014

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

(17) Al-Taee,MajidA,Al-Nuaimy,Waleed.,Al-Ataby,Ali,Muhsin,andZahra J. “Mobile Health Platform for Diabetes Management Based on the

Internet-of-Things”. IEEE Jordan Conference on Applied Electrical

Engineesing and Computing Technologies (AEECT), 2015

(18) Perez,JavierAndreu.,Leff,DanielR,IpHMD,andYang,Guang-Zhong. “From Wearable Sensors to Smart Implants – Towards Pervasive

and Personalised Healthcare”. IEEE, 2015

(19) Blount, M. et al. “Remote Healthcare Monitoring Using Personal

Care Connect”. IBM Systems Journal Vol. 46, No. 1, 2017

(20) Rahman,RuhaniAb,Aziz,NurShimaAbdul,Yusof,MatIkanetal.“IoT- based Personal Health Care Monitoring Device for Diabetics

Patiens”. IEEE, 2017

(21) Kotimah, Muinah Kusnul, dan Wulandari, Sri Pingit. “Model Regresi

Logistik Biner Stratifikasi Pada Partisipasi Ekonomi Perempuan Di Provinsi Jawa Timur”. Jurnal Sains dan Seni Pomits, Vol. 3, No. 1, 2014

(22) 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 Kediri”. Jurnal Sains dan Seni Pomits, Vol. 3, No. 2, 2014

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

(24) Maharani,IndahIrma,Hardinsyah,danSumantri,Bambang.“Aplikasi Regresi Logistik Dalam Analisis Faktor Risiko Anemia Gizi Pada Mahasiswa Baru IPB”. Jurnal Gizi dan Pangan, 36 - 43, 2007

(25) D, Hosmer, & S, Lemeshow. “Aplied Logistic Regression”. USA: John Wliey & Sons, 2000

DOI: 10.24003/emitter.v6i1.258


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