Penerapan Metode Learning Vector Quantization (LVQ) Untuk Mengenali Jenis Teks Kaligrafi

Addilah, Ziqra (2021) Penerapan Metode Learning Vector Quantization (LVQ) Untuk Mengenali Jenis Teks Kaligrafi. Skripsi thesis, Universitas Islam Negeri Sumatera Utara.

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Abstract

Calligraphy is the art of beautiful writing. The term calligraphy comes from simplified English (calligraphy) taken from the Latin word "kalios" which means beautiful, and "graph" which means writing or script. The art of writing Arabic letters is called science of khat, known as Arabic calligraphy or Islamic calligraphy. There are many types and varieties of Islamic calligraphy. Each has a different letterform and function. There are seven types of calligraphy writing that are known and recognized by calligraphy art lovers in Indonesia, such as, Khat Naskhi, Tsuluts, Farisi, Riq'ah, Diwani, Diwani Jali, and Kufi. The method commonly used to identify what type of calligraphy is made is to see directly through the form and characteristics of the calligraphy itself (calligraphy experts). Here the author tries to create a computerized calligraphy type recognition system using the Learning Vector Quantization method. Where this method is a method that works with each output unit presenting a class. In other words, this method is a method of grouping where the target / class of each group / number of groups has been determined. This classification method has the advantage of faster computation time and better recognition. So with this system, we can type computerized calligraphy texts. From the results of applying the LVQ algorithm to calligraphy image recognition, some are successful and some are failures. With a sample of 60 data on each type of calligraphy image. The accuracy value obtained in the calligraphy image recognition results is 75%.

Jenis Item:	Skripsi (Skripsi)
Uncontrolled Keywords:	Learning Vector Quantization, LVQ, Kaligrafi.
Subjects:	000 Generalities > 005 Computer programming, programs, data
Divisions:	Fakultas Sains dan Teknologi > Ilmu Komputer > Skripsi
Pengguna yang mendeposit:	Ms Nurul Hidayah Siregar
Date Deposited:	07 Jul 2023 04:54
Last Modified:	07 Jul 2023 04:54
URI:	http://repository.uinsu.ac.id/id/eprint/19832

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