DOI: https://doi.org/10.14710/jmasif.14.2.59513

Implementasi Metode Support Vector Machine (SVM) dan t-Distributed Stochastic Neighbor Embedding (t-SNE) untuk Klasifikasi Depresi

Departemen Informatika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia

Received: 8 Nov 2023; Revised: 29 Nov 2023; Accepted: 30 Nov 2023; Available online: 30 Nov 2023; Published: 30 Nov 2023.
Editor(s): Prajanto Adi
Open Access Copyright (c) 2023 The authors. Published by Department of Informatics, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract

Depresi merupakan salah satu gangguan kesehatan mental. Sekitar 300 juta jiwa atau 3,76% populasi di dunia dari segala usia dan komunitas menderita depresi. WHO memprediksi bahwa depresi akan menjadi penyebab kematian paling berdampak dalam 15 tahun ke depan. Penelitian terdahulu yang melakukan klasifikasi terhadap depresi untuk instrumen Depression Anxiety Stress Scales (DASS-42) masih sangat sedikit. Penelitian ini mengidentifikasi seseorang memiliki kemungkinan depresi, melalui proses pelatihan model klasifikasi menggunakan metode Support Vector Machine dan t-Distributed Stochastic Neighbor Embedding pada set data DASS-42. Set data DASS-42 terdiri dari 39.776 data dan dapat digunakan untuk mengklasifikasi 3 fenomena yang berbeda yaitu, depresi, stress dan kecemasan. Model Support Vector Machine dilatih menggunakan data DASS-42 yang telah dibersihkan, normalisasi dan balancing serta menggunakan atribut yang telah direduksi melalui proses reduksi dimensi t-Distributed Stochastic Neighbor Embedding. Data latih dan data uji dibagi dengan rasio 80:20. Berdasarkan hasil pengujian, implementasi metode Support Vector Machine (SVM) dan t-Distributed Stochastic Neighbor Embedding (t-SNE) untuk klasifikasi depresi pada data DASS-42 menunjukkan performa yang lebih baik dengan akurasi terbaik sebesar 100% pada data sebelum balancing dan 91,71% pada data setelah balancing.

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Keywords: Support Vector Machine; t-Distributed Stochastic Neighbor Embedding; Klasifikasi; Depresi

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