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Wasilah Wasilah
Institut Informatika Dan Bisnis Darmajaya
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Journal : Building of Informatics, Technology and Science

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Implementasi Data Mining Dalam Klasifikasi Tingkat Kesenjangan Kompetensi PNS Menggunakan Metode Naive Bayes Kurniawan, Putra; Wasilah, Wasilah; Sutedi, Sutedi; Nugroho, Handoyo Widi
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5641

Abstract

Civil Servants (Aparatur Sipil Negara or ASN) play crucial roles as implementers of public policy, community service providers, and national unifiers. The government's primary focus is on enhancing the quality and efficiency of public services. In the Provincial Government of Lampung, planning for the enhancement of the competencies of Civil Servants (Aparatur Sipil Negara or ASN) has become a current priority activity. This emphasis is due to the absence of reference data for determining competency development for each ASN. The Assessment Center is one method for determining the competency level of Civil Servants (ASN). However, its implementation faces several challenges such as budget constraints, time limitations, and a shortage of assessors. Based on the results of the 2023 Merit System Index assessment by the Civil Service Commission (KASN), it was recommended that mapping and evaluating employee competency gaps can be carried out through the Human Capital Development Plan (HCDP). In its implementation, a self-assessment method using a questionnaire based on the competency dictionary from the Regulation of the Minister of Administrative and Bureaucratic Reform No. 38 of 2017 is used to address the constraints of the assessment center. The questionnaire is specifically targeted at technical civil servants (PNS) in the Lampung Provincial Government. The analysis of this questionnaire data produces a classification of civil servants based on the level of competency gaps (none, low, medium, high). In this study, the classification results are tested using one of the data mining classification techniques, namely the Naïve Bayes method. The objective of this research is to evaluate the performance of the Naïve Bayes algorithm in classifying the levels of competency gaps among civil servants. Based on the research findings, it can be concluded that the classification system for competency gap levels among civil servants in the Lampung Province Government can be modeled. The testing of the model, which implemented the Naïve Bayes classification method using RapidMiner tools on the research dataset, achieved an accuracy rate of 98.02%. The conclusion is that the Naïve Bayes algorithm performs well in classifying the competency gap levels among civil servants. With the achieved accuracy level, the resulting classifications can be utilized by the Lampung Provincial Government in planning the development needs of civil servant competencies
Co-Authors Abdul Kadir, Seriyati Binti Aida Imtihana alfiah alfiah Alfirah, Nunung Dewi Amnah Amnah amnah amnah Andini Mugia Lestari Aniswita Assefi, Khaikal Fasya Azzaroh, Istofina Bambang Prasetyo Burhanuddin Burhanuddin Dalimunthe, Zuliani Darmawan Darmawan Diny Rahmadani Dona Yuliawati Eka Wulandari Enok Rohayati Fahrurrozi Ghalib Faisal Faisal Fitriana, Ani Qotuz Zuhro’ Hadiwandra, T Yudi Halimah Halimah Halimah Halimah Hamja, Ulfa Idin handoyo widi nugroho Haris Kusumajaya Hary Sabita Hendri Purnomo Herianto Herianto Herwanto, Riko Hidaya, Nur Iklimah, Iklimah Ikmal , Moh Iltavia Iltavia Irma Rahayu, Irma Jamanuddin Jamanuddin, Jamanuddin Jumhur Jumhur Khaidarmansyah Khaidarmansyah Kurniawan Kurniawan Kurniawan, Putra Lestari, Yulia M.I.Rizki M.Imamuddin, M.Imamuddin Mahfudzin, Abdul Halim Mardha Tilla Maria Sumaryati Marwati - Maryani Maryani Matroni, Matroni Mazid, Fakhrul Meli Amelia Mellania Miftahul Huda Minarni Minarni Moh Kholil Baitaputra Ms, Aswan Muhammad Akbar Muhammad Attar Muhammad Irsan Amrullah, Muhammad Irsan Muhammad Misbahuddin, Muhammad Muhammad Rifai Muhammad, Kemas Murtiani, Farida Muslimah, Nurul Mutmainnah Mutmainnah Nazarmanto, Nazarmanto Nirhamullah Nirhamullah, Nirhamullah Nisar Nisar Nisar Nisar Nisar Nisar Nuraidah Nuraidah, Nuraidah Nurfitria , Nurfitria Nursiyanto Nursyam Nursyam Nurul Fadhilah SM, Nurul Fadhilah Ochi Marshella Febriani Oktari, Safira Dwi OKTAVIA KRISTIANA Pramodiyo Wilantara, Rangga Pratama, Azwar Purnomo, Jeri Qoim Nurani Raden Arya Putra Martallata Raden Faridz Rahman, St Aisyah Rahmawati, Naely Rakhman, Agus Solehudin Ramasepti, Winki Rasyid, Fadilah Aliyah Razman, Muhammad Rendra Nasrul Rifai Retno Dwi Handayani Riko Herwanto Riko Herwanto Rini Nurlistiani Rizki Cahyadi Okasumaendy Rizky Amalia ROBIATUL ADAWIYAH, SITI Rosmiaty Rosmiaty Rusli, Akbar Sabana, Rendi Sam, Mukhlishah Sari, Anisa Fitria Satria Kusuma, Lutvianus Septiana, Eva septilia arfida Sriyanto Sriyanto St. Aisyah Rahman, St. Aisyah Suroso Suroso Sushanty Saleh Sutedi Sutedi Syukur, Idris Tasnim Rahmat, Tasnim Tia Almani Triloka, Joko Tutut Sholihah Ulmia, Nahda Ulya, Millatul Winda Rika Lestari Yan Aditiya Pratama Yaumil Maghfirah Asaf, Yaumil Maghfirah Yulistiawati, Yulistiawati Zulkarnain AS, Zulkarnain Zulkarnaini