{"id":107206,"date":"2026-02-19T03:44:00","date_gmt":"2026-02-18T20:44:00","guid":{"rendered":"https:\/\/www.its.ac.id\/news\/?p=107206"},"modified":"2026-02-20T05:16:42","modified_gmt":"2026-02-19T22:16:42","slug":"doktor-its-kembangkan-sistem-pendeteksi-depresi-berdasarkan-riwayat-medsos","status":"publish","type":"post","link":"https:\/\/www.its.ac.id\/news\/doktor-its-kembangkan-sistem-pendeteksi-depresi-berdasarkan-riwayat-medsos\/","title":{"rendered":"Doktor ITS Kembangkan Sistem Pendeteksi Depresi Berdasarkan Riwayat Medsos"},"content":{"rendered":"
\"Dr
Dr Gede Aditra Pradnyana SKom MKom saat presentasi disertasinya dalam sidang promosi doktor di Departemen Teknik Elektro ITS<\/figcaption><\/figure>\n

Kampus ITS, ITS News \u2013 <\/strong>Maraknya pemakaian smartphone dan media sosial (medsos) di era globalisasi ini menyebabkan kondisi mental masyarakat menjadi lebih dinamis. Menjawab tantangan tersebut, lulusan program doktoral Departemen Teknik Elektro Institut Teknologi Sepuluh Nopember (ITS)<\/a> Dr Gede Aditra Pradnyana SKom MKom merancang model sistem deteksi depresi berbasis sumber data dari penggunaan medsos menggunakan Artificial Intelligence (AI) multimodal.<\/p><\/blockquote>\n

Lelaki yang akrab disapa Adit ini menjelaskan bahwa kasus bunuh diri yang disebabkan oleh depresi menjadi salah satu permasalahan genting dalam hal kemanusiaan. Ketakutan untuk mengungkapkan masalah kehidupan secara langsung, baik kepada psikolog, psikiater, maupun kerabat terdekat masih menjadi hambatan bagi mayoritas orang. Bahkan, sebagian orang lebih sering meluapkan perasaan gelisah dan persoalan yang rumit ke medsos.<\/p>\n

Berangkat dari masalah tersebut, dosen Universitas Pendidikan Ganesha ini mengusulkan pendekatan deteksi depresi secara non-intrusif berbasis jejak digital. Melalui pendekatan ini, sistem yang dibangun mampu memberikan informasi awal secara cepat, mendukung intervensi diri, dan berfungsi sebagai pelengkap asesmen klinis konvensional. \u201cPendekatan ini bukan hanya memerlukan sensor fisiologis, melainkan juga memanfaatkan pola ekspresi multimodal sebagai indikator awal,\u201d paparnya.<\/p>\n

Model yang dikembangkan bernama DeXMAG, yakni gabungan antara Cross-Modal Attention and Adaptive Gated Fusion dengan fitur Myers Briggs Type Indicator (MBTI). Lebih jelasnya, kombinasi dari kerangka kerja multimodal deep learning<\/em> yang dipersonalisasi oleh tipe kepribadian pengguna. Oleh karena itu, sistem yang dimiliki dapat meningkatkan performa deteksi depresi dari data media sosial.<\/p>\n

\"Dr
Dr Gede Aditra Pradnyana SKom MKom saat menyampaikan tahapan awal penelitian pada Konferensi Internasional FUZZ-IEEE di Korea Selatan tahun 2023<\/figcaption><\/figure>\n

Secara arsitektural, rancangan model tersebut dimulai dari tahap paling awal dan utama, yakni mengidentifikasi modalitas teks dan gambar yang diunggah oleh pengguna. Setelah proses identifikasi, muatan modalitas diproses oleh RoBERTa dan VGG-16 model terlatih serta keputusan kepribadian oleh GloVe-BiLSTM. Penyelesaian proses dilakukan dengan Weighted Fused Representation, sehingga diperoleh hasil deteksi berupa depresi atau tidak depresi.<\/p>\n

Lebih lanjut, hasil yang didapatkan menunjukkan delapan sifat kepribadian yang berhubungan dengan indikasi depresi. Sifat kepribadian tersebut terdiri atas perceiving, judging, intuition, dan thinking. \u201cBukan hanya itu, sifat kepribadian tentang perasaan, seperti feeling<\/em>, introversion<\/em>, sensing<\/em>, dan extroversion<\/em> turut ditampilkan dengan bentuk diagram radar,\u201d imbuh alumnus Universitas Udayana tersebut.<\/p>\n

Secara keseluruhan, hasil deteksi terbukti dari studi ablasi yang menunjukkan bahwa setiap modalitas memberikan kontribusi terhadap kinerja prediktif. Setiap sinyal linguistik dan visual akan memberikan peningkatan kinerja yang signifikan dibandingkan pendekatan unimodal. \u201cHarapannya, pendekatan ini bisa dimanfaatkan banyak orang dan mampu membantu memutuskan kerentanan depresi hanya melalui fitur aplikasi,\u201d tuturnya optimistis.<\/p>\n

Penelitian ini juga selaras dengan agenda Sustainable Development Goals (SDGs)<\/a>. Khususnya pada poin ke-3 mengenai Kehidupan Sehat dan Sejahtera serta poin ke-9 mengenai Industri, Inovasi, dan Infrastruktur. Melalui integrasi kecerdasan buatan dan kesehatan mental digital, inovasi ini berkontribusi terhadap pengembangan solusi teknologi yang mendukung kesejahteraan psikologis masyarakat secara berkelanjutan. (HUMAS ITS)<\/strong><\/p>\n

 <\/p>\n

Reporter: Mohammad Fariz Irwansyah<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

Kampus ITS, ITS News \u2013 Maraknya pemakaian smartphone dan media sosial (medsos) di era globalisasi ini menyebabkan kondisi mental masyarakat menjadi lebih dinamis. Menjawab tantangan tersebut, lulusan program doktoral Departemen Teknik Elektro Institut Teknologi Sepuluh Nopember (ITS) Dr Gede Aditra Pradnyana SKom MKom merancang model sistem deteksi depresi berbasis sumber data dari penggunaan medsos menggunakan […]<\/p>\n","protected":false},"author":767,"featured_media":107207,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[4007,14,3661,4093,3755,3689],"tags":[1951,1746,3557],"class_list":["post-107206","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-berita-terkini","category-berita-utama","category-good-health-well-being","category-industri1","category-industry","category-innovation-infrastructure","tag-ann","tag-humas-its","tag-riz"],"yoast_head":"\nDoktor ITS Kembangkan Sistem Pendeteksi Depresi Berdasarkan Riwayat Medsos - ITS News<\/title>\n<meta name=\"description\" content=\"Lulusan 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