Mulyo W, Petra Andriyani and Jatnika, Hendra and Rifai, M. Farid (2022) Penerapan Metode Multiple Linear Regression (MLR) pada Training dan Pelatihan di Information Technology Certification Center (ITCC). Diploma thesis, IT PLN.
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Abstract
Multiple Linear Regression (MLR) is one of the algorithms in Machine Learning. Machine Learning predicts linear coefficient equations involved in one or more independent variables that can predict the value of the intended variable. That algorithm predicts the value of a variable based on the value of other variables. In 2021, data showed that the quality and quantity of Microsoft Office Specialist (MOS) and Microsoft Technology Associate (MTA) graduates is decreasing. In the "MOS 2018" passing percentage was seventy-two percent (72%) which held before pandemic, then it dropped to fifty-two percent (52%) in "MOS 2019 batch 1", which held in the pandemic. Based on the results of the MLR trial test to the dataset of the MOS Word 2019 and MCF AI certification test participants, a calculation formula was obtained as a guideline to calculate the assessment of MOS Word 2019 and MCF AI scores. The results of this formula could be used for the preparation of self-assessment in accordance with the competency test grid. The MLR method can provides calculation for competency test score criteria, with an accuracy of 98% for MOS Word 2019 and 94% for MCF AI. It can be used to help training participants to measure their own abilities against the competency test that will be tested.
Multiple Linear Regression (MLR) merupakan salah satu algoritma dalam Machine Learning. Machine Learning yang memperkirakan persamaan koefisien linear yang terlibat dalam satu atau lebih variabel bebas yang bisa memprediksi nilai variabel yang dituju. Algoritma yang digunakan untuk memprediksi nilai suatu variabel berdasarkan nilai variabel lainnya. Berdasarkan data tahun 2021, terlihat kualitas dan kuantitas lulusan Microsoft Office Specialist (MOS) dan Microsoft Technology Associate (MTA) kian menurun. Pada sertifikasi MOS 2018 gelombang 1 (pra pandemi), persentase kelulusan sebesar tujuh puluh dua persen (72%), sedangkan pada MOS 2019 gelombang 1 (masa pandemi) persentase kelulusan turun menjadi lima puluh dua pesen (52%). Berdasarkan hasil tes uji coba MLR ke dataset peserta uji sertifikasi MOS Word 2019 dan MCF AI didapatkan rumus perhitungan sebagai patokan dalam penilaian skor MOS Word 2019 dan MCF AI. Hasil Rumusan ini dapat dipergunakan untuk penyusunan self-assessment sesuai dengan kisi-kisi uji kompetensi. Aplikasi dengan metode MLR dapat membetrikan perhitungan kriteria skor uji kompetensi, dengan keakuratan diatas 98% untuk MOS Word 2019 dan 94% untuk MCF AI, yang dapat digunakan guna membantu peserta training dan pelatihan untuk mengukur kemampuan diri terhadap uji kompetensi yag akan diujikan
| Item Type: | Thesis (Diploma) |
|---|---|
| Uncontrolled Keywords: | self-assessment, Multiple Linear Regression, (Information Technology Certification Center) ITCC, MOS 2019, dan MCF AI. |
| Subjects: | Skripsi Bidang Keilmuan > Teknik Informatika |
| Divisions: | Fakultas Telematika Energi > S1 Teknik Informatika |
| Depositing User: | Sutrisno |
| Date Deposited: | 10 Oct 2025 01:39 |
| Last Modified: | 10 Oct 2025 01:39 |
| URI: | https://repository.itpln.ac.id/id/eprint/2030 |
