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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Infotech Journal
Dewi Mufadilah
Bina Insani University
Computer Science & IT Decision Sciences, Operations Research & Management

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Enhancing Transformer Performance through Contextual Labeling: A Case Study on Student Mental Health Prediction Mardi Yudhi Putra; Dwi Ismiyana Putri; Rika Apriani; Renaldi Triharsono; Dewi Mufadilah
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 14 No. 1 (2026): March 2026
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v14i1.11800

Abstract

 Early identification of stress and depression among university students is essential to support timely psychological intervention, yet traditional counseling methods often rely on manual, self-initiated reporting that may overlook students experiencing emotional distress. This study aimed to develop a text-based mental-health detection framework using transformer models supported by contextual labeling to analyze student-generated social-media content. The research was conducted through three stages: problem exploration with the Student Affairs Division, data collection from questionnaires and 993 social-media text entries, and comprehensive data preprocessing involving cleaning, normalization, deduplication, and lexicon-based weak labeling. The cleaned dataset was used to fine-tune two transformer architectures—RoBERTa for sequence classification and T5 for text-to-text classification—and to construct a majority-vote ensemble. Model performance was evaluated using accuracy, precision, recall, F1-score, and confusion matrices. The results showed that the T5 model achieved the most balanced performance across all categories, particularly in distinguishing neutral and stress expressions, while RoBERTa and the ensemble exhibited strong prediction bias toward a single class. The findings demonstrated that contextual preprocessing combined with transformer-based modeling effectively supported automated detection of student emotional states. This study concluded that transformer models, especially T5 with contextual labeling, offered a promising foundation for developing early-warning systems that can be integrated into university counseling services and further enhanced through expanded datasets, expert-validated annotations, and explainable-AI components.
PENERAPAN SOFTWARE TESTING LIFE CYCLE (STLC) BERBASIS ISO/IEC 25010 PADA SIBASWEB Najwa Nur Aulya; Amira Dinar Malika Isnadi; Kaela Alifiya Putri Salsabila; Dewi Mufadilah; Anastasya Putri Syahzuar
INFOTECH journal Vol. 12 No. 2 (2026)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/infotech.v12i2.19374

Abstract

Pengelolaan sampah pada bank sampah masih banyak dilakukan secara manual, sehingga rawan terjadi kesalahan pencatatan dan pelayanan kepada nasabah menjadi lambat. Penelitian ini bertujuan mengevaluasi kualitas SIBASWEB (Sistem Informasi Bank Sampah Berbasis Web) yang dikembangkan untuk Bank Sampah Villa 1 Asri, Bekasi. Pengujian dilakukan dengan menerapkan tahapan Software Testing Life Cycle (STLC) yang dievaluasi menggunakan standar kualitas perangkat lunak ISO/IEC 25010, yang berfokus pada Functional Suitability dan Usability. Evaluasi fungsional dilakukan melalui Alpha testing dengan metode Black box testing (teknik equivalence partitioning) pada 34 test case. Sedangkan pengujian usability dilakukan lewat Beta testing menggunakan kuesioner skala Likert kepada 35 responden. Hasil Alpha testing menunjukkan tingkat keberhasilan sebesar 85,29%, dengan 29 dari 34 test case berstatus valid dan 5 test case tidak valid karena belum adanya validasi input pada beberapa kondisi. Hasil Beta testing menunjukkan indeks penerimaan pengguna sebesar 86,91% dengan rata-rata skor 4,35 dari skala 5,00 yang termasuk kategori Sangat Baik. Hasil ini menunjukkan bahwa SIBASWEB dinilai sudah memenuhi kelayakan standar mutu perangkat lunak pada aspek fungsional maupun penerimaan pengguna. Namun, penguatan validasi input pada beberapa fitur masih diperlukan sebelum sistem digunakan sepenuhnya.
Co-Authors Amira Dinar Malika Isnadi Anastasya Putri Syahzuar Dwi Ismiyana Putri Kaela Alifiya Putri Salsabila Mardi Yudhi Putra Najwa Nur Aulya Renaldi Triharsono Rika Apriani