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All Journal TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Visualika
Frindo, Muhamad Meky
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Analisis Komparatif Metode MOORA dan MAUT untuk Rekomendasi Pengangkatan Tenaga Pendidik Oktavia, Petricia; Frindo, Muhamad Meky
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7337

Abstract

The objective and data-driven recruitment of educators is a strategic step toward improving the quality of education. This study aims to develop a recommendation system for selecting prospective educators by comparing two multi-criteria decision-making methods: MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) and MAUT (Multi-Attribute Utility Theory). Five key criteria were used in the evaluation: Grade Point Average (GPA), mastery of didactic and methodological knowledge, teaching experience, age, and distance from home to school. Primary data were collected directly from educational institutions and prospective educators, involving six alternatives that were analyzed through normalization, weighting, and final score calculation. The analysis showed that the MOORA method identified candidate A2 as the best with a score of 0.3143, while the MAUT method ranked candidate A6 highest with a score of 0.644. The difference in rankings stems from the distinct evaluation principles of the two methods: MOORA relies on normalized ratios relative to the maximum value, while MAUT applies an aggregated utility approach. Despite this variation, both methods consistently identified the top three candidates. The developed recommendation system not only enhances transparency and accountability but also outperforms conventional intuition-based approaches by providing a structured, measurable, and replicable framework. This system has the potential to be adopted by educational institutions to ensure a fairer and more objective educator recruitment process.
PEMODELAN REGRESI LINIER PADA KETIMPANGAN GENDER UNTUK MEMPREDIKSI POLA DISTRIBUSI TENAGA KERJA SEKTORAL Frindo, Muhamad Meky; Oktavia, Petricia
Jurnal Visualika Vol. 12 No. 1 (2026): Jurnal Visualika
Publisher : Prodi Sistem Informasi Universitas Saintek Muhammadiyah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56459/7p3zk432

Abstract

Ketimpangan gender dalam distribusi tenaga kerja lintas sektor merupakan tantangan signifikan bagi pembangunan ekonomi yang inklusif di wilayah perkotaan. Meskipun akses pendidikan bagi perempuan meningkat, segregasi okupasional yang memisahkan peran laki-laki dan perempuan pada sektor tertentu masih mendominasi struktur pasar kerja. Penelitian ini bertujuan untuk memodelkan dan memprediksi faktor-faktor yang memengaruhi ketimpangan gender tersebut di Kota Bogor dengan membandingkan tingkat signifikansi antara variabel kewilayahan (kecamatan) dan jenis pekerjaan terhadap proporsi gender tenaga kerja. Metode yang digunakan dalam penelitian ini adalah pendekatan data mining kuantitatif dengan menerapkan algoritma Regresi Linier Berganda (Multiple Linear Regression) dan Random Forest Regressor sebagai komparasi. Dataset yang dianalisis bersumber secara resmi dari portal open data pemerintah kota bogor untuk periode tahun 2022 dan tahun 2023. Tahapan analisis mencakup pra-pemrosesan data, pembersihan, imputasi nilai hilang, pemfilteran pembagian nol, pembersihan outlier berbasis Z-score (|Z| <= 3), one-hot encoding untuk fitur kategorikal, uji asumsi regresi, serta evaluasi model menggunakan metrik R-squared (R2), Root Mean Squared Error (RMSE), dan Mean Absolute Error (MAE). Hasil pemodelan menunjukkan bahwa jenis pekerjaan merupakan prediktor yang dominan dan berpengaruh sangat signifikan terhadap ketimpangan gender, sedangkan variabel kewilayahan secara statistik tidak menunjukkan pengaruh yang signifikan (p > 0,05). Model mencapai tingkat akurasi (R-squared) sebesar 0,7107 pada tahun 2022 dan 0,6223 pada tahun 2023. Temuan ini menyimpulkan bahwa kebijakan kesetaraan gender di masa depan harus lebih difokuskan pada intervensi spesifik sektoral (berdasarkan jenis pekerjaan) daripada kebijakan berbasis wilayah administratif.
Co-Authors Oktavia, Petricia