Gustiani, Yuyus Bahtiar (2018) Penerapan Algoritma K-Nearest Neighbor Dan Principal Component Analysis Pada Pengenalan Tulisan Tangan Dalam Kasus Penilaian Jawaban Esai. Other thesis, Universitas Komputer Indonesia.
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Abstract
SMK Negeri Rajapolah is one of the Vocational High Schools located in Tasikmalaya Regency, West Java. This vocational school has proper facilities of which one of them is a Koperasi. It is a kind of shop that sells any materials needed at school. The Koperasi is under Accountant study program and managed by their teachers. There is a problem which comes up in this Koperasi. The Koperasi Officer is difficult in serving the buyers (in this case are the students), which usually caused by the endless queuing of students. It happens because of payment process which takes long time. One of the solutions to overcome this problem is by developing a payment system on a Radio Frequency Identification basis, called RFID. This system is built to make the Koperasi Officer easier in giving service to the students, while the RFID system is used to minimize the long queuing. Based on the results of Black Box and Beta tests, it can be concluded that the implementation of RFID system in the Koperasi simplifies the service and makes less queuing.
Optical Character Recognition (OCR) is a tool that can be used for translating characters digital image into text format. This research are using principal component analysis and k-nearest neighbor methods. The purpose of PCA method is too reduce big dimension from observed variables intrigue dimension that smaller from independent variables, it is used to describe smaller data. K-NN is classification method that based on nearest neighbor class. The image that used for this research are training image and test image. Training image will be handwriting image that contains characters from a-z, A-Z and 0-9. Test image will be handwriting essay answers. Step by step of this research are preprocessing that include grayscaling, thresholding, dilation, segmented eruotion, and resizing. After that extraction process that using PCA method. For introduction step is by using extraction of feature from K-NN method result.. after getting the result from identification, next to do is assessing process essay by measuring similarity level with the answer sheet using rabin karp method. Based on the testing result that have been with five K values combination parameter. The accuracy of the method is 77,79 percent with K=5.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | Migrasi dari GDL. Identifier: jbptunikompp-gdl-yuyusbahti-38916. Folder: S1-Final_Project / Fakultas_Teknik_dan_Ilmu_Komputer / Teknik_Informatika / 2018 |
| Uncontrolled Keywords: | Pengenalan Tulisan Tangan, Principal Component Analysis, Ekstraksi Ciri, K-Nearest Neighbour, Pengolahan Citra Digital |
| Divisions: | S1 Skripsi > Teknik Informatika |
| Depositing User: | Robot Migration |
| Date Deposited: | 05 Nov 2026 13:03 |
| Last Modified: | 05 Nov 2026 13:03 |
| URI: | https://elibrary.unikom.ac.id/id/eprint/49785 |
