Prototipe Sistem Pendukung Keputusan Terintegrasi Model Ner Untuk Validasi Dan Penetapan Pemuktahiran Data ASN

Penulis

  • Nur Muhamad Holik Institut Teknologi Sepuluh Nopember, Surabaya
  • Surya Sumpeno Institut Teknologi Sepuluh Nopember, Surabaya
  • Reza Fuad Rachmadi Institut Teknologi Sepuluh Nopember, Surabaya

DOI:

https://doi.org/10.25126/jtiik.2025129175

Kata Kunci:

State Civil Apparatus, Named Entity Recognition, Decision Support System, Optical Character Recognition

Abstrak

Untuk mendukung dan memperlancar penyelenggaraan manajemen aparatur sipil negara serta pengambilan keputusan yang efisien, efektif, dan akurat, diperlukan data pegawai ASN. Data tersebut harus dimutakhirkan dan divalidasi secara berkala sebelum disebarluaskan dan diakses oleh instansi pemerintah sesuai kewenangannya masing-masing serta dapat diakses oleh masyarakat melalui portal data sesuai dengan ketentuan peraturan perundang-undangan. Pada paper ini ditampilkan prototipe berbasis web untuk menunjukkan bahwa model NER yang dikembangkan dapat diintegrasikan sebagai subsistem dari sistem pendukung keputusan dalam melakukan validasi dan penetapan persetujuan pemutakhiran data ASN. Prototipe menunjukkan tingkat kemiripan hasil prediksi model dengan data yang diusulkan, tertinggi sebesar 100% dan terendah sebesar 41,34%. Pengukuran kinerja model menggunakan spacy menunjukkan bahwa model terbaik memperoleh nilai F1-score rata-rata sebesar 99,01 menggunakan dataset training, 98,20 menggunakan dataset testing, dan 94,26 menggunakan dataset other.

 

Abstract

To support and facilitate the implementation of state civil apparatus management and efficient, effective, and accurate decision-making, ASN employee data are required. The data must be updated and validated periodically before being disseminated and accessed by government agencies according to their respective authorities and can be accessed by the public through a data portal in accordance with the provisions of laws and regulations. This paper presents a web-based prototype to demonstrate that the proposed NER model can be integrated as a subsystem of a decision support system to validate and determine approval for ASN data updates. The prototype shows the level of similarity between the model's prediction results and the proposed data, with the highest value being 100% and the lowest being 41.34%. The measurement of model performance using spacy demonstrated that the best model obtained an average F1-score of 99.01 using the training dataset, 98.20 using the testing dataset, and 94.26 using the other dataset.

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Referensi

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Diterbitkan

30-06-2025

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Cara Mengutip

Prototipe Sistem Pendukung Keputusan Terintegrasi Model Ner Untuk Validasi Dan Penetapan Pemuktahiran Data ASN. (2025). Jurnal Teknologi Informasi Dan Ilmu Komputer, 12(3), 573-582. https://doi.org/10.25126/jtiik.2025129175