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Kurniadi Wardana H, Indahwati E, Arifah Fitriyah L. Measurement of Non-Invasive Blood Glucose Level Based Sensor Color TCS3200 and Arduino. IOP Conf Ser Mater Sci Eng. 2018;336(1). doi:10.1088/1757-899X/336/1/012019Kurniadi WardanaHIndahwatiEArifah FitriyahLMeasurement of Non-Invasive Blood Glucose Level Based Sensor Color TCS3200 and Arduino2018336110.1088/1757-899X/336/1/012019Open DOISearch in Google Scholar
Putri WJ, Isa I. Studi Literatur Glucose Sensor for Human Blood Using Glassy Carbon Electrode (GCE) Based Electrochemical Sensor with Voltammetry Method. J Fis Unand. 2021;10(3):324–329.PutriWJIsaIStudi Literatur Glucose Sensor for Human Blood Using Glassy Carbon Electrode (GCE) Based Electrochemical Sensor with Voltammetry Method2021103324329Search in Google Scholar
Fridayanti N, Muldarisnur M. Design and Build a Blood Sugar Level Measuring Instrument in Urine with the Evanescent Method. Positron. 2018;8(2):1. doi:10.26418/positron.v8i2.26993FridayantiNMuldarisnurMDesign and Build a Blood Sugar Level Measuring Instrument in Urine with the Evanescent Method201882110.26418/positron.v8i2.26993Open DOISearch in Google Scholar
Lengkong TD, Wowor MF, Berhimpon SLE. Overview of Blood Glucose and Urine Glucose in Young Adults Overweight and Obesity. Med Scope J. 2020;1(2):56–60. doi:10.35790/msj.1.2.2020.27816LengkongTDWoworMFBerhimponSLEOverview of Blood Glucose and Urine Glucose in Young Adults Overweight and Obesity202012566010.35790/msj.1.2.2020.27816Open DOISearch in Google Scholar
Febryansah, M. Iqbal, Anton Yudhana, and Alfian Ma'arif. 2020. “Smart Urinal Analyzer Detecting Abnormalities in Kidney Function With Analysis Of Ph Levels And Color In Urine.” Mobile and Forensics 2(1):32–40.FebryansahM. IqbalYudhanaAntonMa'arifAlfian2020“Smart Urinal Analyzer Detecting Abnormalities in Kidney Function With Analysis Of Ph Levels And Color In Urine.”213240Search in Google Scholar
Putra G. Design and Build a Non-Invasive Blood Sugar Level Measuring Device Based on Atmega 328P Microcontroller by Measuring the Turbidity Level of Urine Specimens Using Photodiode and Light Emiting Diode Sensor Packages. 2015;4.PutraG20154Search in Google Scholar
Satria, Eko W. Design and Build a Non-Invasive Blood Sugar Level Measuring Instrument Based on the AT89S51 Microcontroller by Measuring the Turbidity Level of Urine Specimens Using Photodiode Sensors. J Fis Unand. 2013;2(1):40–47.SatriaEko WDesign and Build a Non-Invasive Blood Sugar Level Measuring Instrument Based on the AT89S51 Microcontroller by Measuring the Turbidity Level of Urine Specimens Using Photodiode Sensors2013214047Search in Google Scholar
Permanasari, A. R. et al. 2018. “The Effect of Substrate and Enzyme Concentration on the Glucose Syrup Production from Red Sorghum Starch by Enzymatic Hydrolysis.” IOP Conference Series: Earth and Environmental Science 160(1).[26]PermanasariA. R.2018“The Effect of Substrate and Enzyme Concentration on the Glucose Syrup Production from Red Sorghum Starch by Enzymatic Hydrolysis.”1601[26]Search in Google Scholar
Pratiwi, Z., & Hufri. (2020). Manufacture of Blood Sugar Level Measuring Device Based on Turbidity Level of Urine Specimen Using Tcs230 Color Sensor And Photodiode With LCD Display. Pillar of Physics, 13(April), 18–25.PratiwiZ.Hufri2020Manufacture of Blood Sugar Level Measuring Device Based on Turbidity Level of Urine Specimen Using Tcs230 Color Sensor And Photodiode With LCD Display13April1825Search in Google Scholar
Batta M. Machine Learning Algorithms A Review. Int J Sci Res (IJ. 2020;9(1):381-undefined. doi:10.21275/ART20203995BattaMMachine Learning Algorithms A Review202091381-undefined.10.21275/ART20203995Open DOISearch in Google Scholar
Leidiyana H. Application of the K-Nearest Neighbor Algorithm for Determining Credit Risk for Motor Vehicle Ownership. J Penelit Ilmu Komputer, Syst Embed Log. 2013;1(1):65–76.LeidiyanaHApplication of the K-Nearest Neighbor Algorithm for Determining Credit Risk for Motor Vehicle Ownership2013116576Search in Google Scholar
Anton Yudhana, et al. 2020. “Human Emotion Recognition Based on EEG Signal Using Fast Fourier Transform and K-Nearest Neighbor.” Advances in Science, Technology and Engineering Systems 5(6):1082–88.YudhanaAnton2020“Human Emotion Recognition Based on EEG Signal Using Fast Fourier Transform and K-Nearest Neighbor.”56108288Search in Google Scholar
Ramadhan RS., Junta Z., Ardytha L. 2016. “Application of K-Nearest Neighbor Algorithm in Information Retrieval in Determining Final Project Reference Topics.” 1(2):123–33.RamadhanRS.JuntaZ.ArdythaL.20161212333Search in Google Scholar
Musliman, Anwar Siswanto, Abdul Fadlil, and Anton Yudhana. 2021. “Identification of White Blood Cells Using Machine Learning Classification Based on Feature Extraction.” Jurnal Online Informatika 6(1):63.MuslimanAnwar SiswantoFadlilAbdulYudhanaAnton2021“Identification of White Blood Cells Using Machine Learning Classification Based on Feature Extraction.”6163Search in Google Scholar
Anton Yudhana, et al. 2022. “Fish Freshness Identification Using Digital Image-Based KNN Algorithm.” 10(1):1–9.YudhanaAnton202210119Search in Google Scholar
Neighbor AK nearest, Chazar C, Nursyamsi I, Herwanto P. Breast Cancer Diagnosis Using Machine Learning With Introduction. 2021;(September):182–191.NeighborAKnearest,ChazarCNursyamsiIHerwantoP2021September182191Search in Google Scholar
Zhang S, Li X, Zong M, Zhu X, Cheng D. Learning k for kNN Classification. ACM Trans Intell Syst Technol. 2017;8(3). doi:10.1145/2990508ZhangSLiXZongMZhuXChengDLearning k for kNN Classification20178310.1145/2990508Open DOISearch in Google Scholar
Angreni IA, Adisasmita SA, Ramli MI, Hamid S. The Effect of K Value on the K-Nearest Neighbor (Knn) Method on the Accuracy Level of Road Damage Identification. Rekayasa Sipil. 2019;7(2):63. doi:10.22441/jrs.2018.v07.i2.01AngreniIAAdisasmitaSARamliMIHamidSThe Effect of K Value on the K-Nearest Neighbor (Knn) Method on the Accuracy Level of Road Damage Identification2019726310.22441/jrs.2018.v07.i2.01Open DOISearch in Google Scholar
Anton Yudhana, Sunardi S, Hartanta AJS. K-Nn Algorithm With Euclidean Distance For Prediction Of Sengon Sawmill Results. Transmisi. 2020;22(4):123–129. doi:10.14710/transmisi.22.4.123-129YudhanaAntonSunardiSHartantaAJSK-Nn Algorithm With Euclidean Distance For Prediction Of Sengon Sawmill Results202022412312910.14710/transmisi.22.4.123-129Open DOISearch in Google Scholar
Nikmatun IA, Waspada I. Implementation of Data Mining for Classification of Student Study Periods Using the K-Nearest Neighbor Algorithm. J SIMETRIS. 2019;10(2):421–432.NikmatunIAWaspadaIImplementation of Data Mining for Classification of Student Study Periods Using the K-Nearest Neighbor Algorithm2019102421432Search in Google Scholar
Halim AAD, Anraeni S. Classification Analysis of Pneumonia Image Datasets using the K-Nearest Neighbor (KNN) Method. Indones J Data Sci. 2021;2(1):01–12. doi:10.33096/ijodas.v2i1.23HalimAADAnraeniSClassification Analysis of Pneumonia Image Datasets using the K-Nearest Neighbor (KNN) Method202121011210.33096/ijodas.v2i1.23Open DOISearch in Google Scholar
Ente, Dewi Rahma et al. 2020. “Classification of Factors Causing Diabetes Mellitus in Unhas Hospital Using the C4.5. Algorithm.” Indonesian Journal of Statistics and Its Applications 4(1):80–88.EnteDewi Rahma2020“Classification of Factors Causing Diabetes Mellitus in Unhas Hospital Using the C4.5. Algorithm.”418088Search in Google Scholar
Nikam SS. A Comparative Study of Classification Techniques in Data Mining Algorithms. Int J Mod Trends Eng Res. 2017;4(7):58–63. doi:10.21884/ijmter.2017.4211.vxaykNikamSSA Comparative Study of Classification Techniques in Data Mining Algorithms201747586310.21884/ijmter.2017.4211.vxaykOpen DOISearch in Google Scholar
Hutapea, Tanzil & Indriati. 2018. “Application of Modified K-Nearest Neighbor Algorithm in Classification of Schizophrenic Mental Illness.” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer 2(10):3957–61.HutapeaTanzilIndriati2018“Application of Modified K-Nearest Neighbor Algorithm in Classification of Schizophrenic Mental Illness.”210395761Search in Google Scholar
Tangkelayuk, Aldi. 2022. “The Water Quality Classification Using KNN, Naïve Bayes, And Decision Tree Methods.” JATISI (Jurnal Teknik Informatika dan Sistem Informasi) 9(2):1109–19.TangkelayukAldi2022“The Water Quality Classification Using KNN, Naïve Bayes, And Decision Tree Methods.”92110919Search in Google Scholar
Singh, Satyanand. 2020. “Minimal Redundancy Linear Array and Uniform Linear Arrays Beamforming Applications in 5G Smart Devices.” Emerging Science Journal 4(Special Issue):70–84.SinghSatyanand2020“Minimal Redundancy Linear Array and Uniform Linear Arrays Beamforming Applications in 5G Smart Devices.”4Special Issue7084Search in Google Scholar