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Identification of glucose levels in urine based on classification using k-nearest neighbor algorithm method Cover

Identification of glucose levels in urine based on classification using k-nearest neighbor algorithm method

Open Access
|Aug 2023

Figures & Tables

Figure 1:

Block diagram. PLN, State Electricity Company; I2C, Inter Integrated Circuit System.

Figure 2:

Wiring diagram.

Figure 3:

Flowchart.

Figure 4:

Machine learning flowchart.

Figure 5:

K-nearest neighbor visualization.

Table 1.

Glucose characterization

No.Urine sampleGlucose level (%)Glucose rate (g)Color resultUrine positive rate (mg/dL)
1.Sample 10–0.50Slightly greenish blue and a bit cloudyNormal
2.Sample 20.5–10.2Yellowish greenPositive 1
3.Sample 31–1.50.3Greenish yellowPositive 2
4.Sample 42–3.50.4Slightly brownish orangePositive 3
5.Sample 5>3.51Slightly brownish brick redPositive 4
Table 2.

Results of the data from the sensor

Result of specimen colorSensor color indicatorClass category
VioletBlueGreenYellowOrangeRed
graphic/j_ijssis-2023-0006_ingr_001.png21.3423.3618.6819.6414.026.66Normal
graphic/j_ijssis-2023-0006_ingr_002.png14.9313.5324.2721.4819.236.53Positive 1
graphic/j_ijssis-2023-0006_ingr_003.png12.1910.0722.6324.1421.879.05Positive 2
graphic/j_ijssis-2023-0006_ingr_004.png11.128.2116.9721.9126.0215.74Positive 3
graphic/j_ijssis-2023-0006_ingr_005.png13.689.9322.5820.7722.5810.43Positive 4
Figure 6:

Prototype: (a) front view, (b) inside view, and (c) upper view.

Figure 7:

Graphs of the data results: (a) Normal, (b) Positive 1, (c) Positive 2, (d) Positive 3, and (e) Positive 4.

Figure 8:

K-value graph.

Figure 9:

KNN classification results. KNN, K-nearest neighbor.

Figure 10:

Confusion matrix.

Language: English
Submitted on: Aug 15, 2022
Published on: Aug 3, 2023
Published by: International Journal on Smart Sensing and Intelligent Systems
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2023 Anton Yudhana, Fathiyyah Warsino, Son Ali Akbar, Fatma Nuraisyah, Ilham Mufandi, published by International Journal on Smart Sensing and Intelligent Systems
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.