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All Journal Jurnal Ilmiah Informatika Komputer Journal of Artificial Intelligence and Technology Information
Adlan Nugroho
Politeknik Negeri Cilacap
Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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TESTING APLIKASI SIAKAD DI PERGURUAN TINGGI XYZ DENGAN PENDEKATAN EXPLORATORY TESTING DAN BLACK BOX TESTING Joko Purwanto; Adlan Nugroho; Muhammad Abdul Muin
Jurnal Ilmiah Informatika Komputer Vol 30, No 1 (2025)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2025.v30i1.12971

Abstract

Sistem Informasi Akademik (SIAKAD) di Perguruan Tinggi XYZ mempunyai peran penting dalam mendukung kegiatan akademik. Namun, sistem ini belum memiliki dokumentasi pelaporan pengujian yang memadai, yang dapat mempengaruhi kualitas dan keandalan layanan. Penelitian ini bertujuan untuk mengevaluasi kualitas SIAKAD menggunakan pendekatan exploratory testing dan black box testing serta menghasilkan laporan hasil yang terstruktur. Laporan yang disusun mencakup hasil pengujian tiap modul, skenario pengujian, tingkat keberhasilan dan kegagalan, serta rekomendasi perbaikan sistem. Exploratory testing diterapkan untuk mengidentifikasi skenario pengujian tanpa memerlukan dokumentasi rinci, sementara black box testing digunakan untuk menguji fungsionalitas berdasarkan spesifikasi tanpa melihat source code. Hasil pengujian melibatkan 318 kasus uji pada 11 modul, dengan tingkat keberhasilan 77,36% dan kegagalan 22,64%. Fitur inti seperti Login , tahun ajaran, paralel, dan absensi diuji secara komprehensif. Studi ini memberikan rekomendasi untuk memperbaiki validasi Input dan penguatan proses bisnis guna meningkatkan keandalan sistem.
Automatic Dewey Decimal Classification of Indonesian Book Metadata Using IndoBERT with Weighted Loss and Context Enhancement Joko Purwanto; Fajar Mahardika; Adlan Nugroho
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 4 No. 2 (2026): Volume 4 Number 2 June 2026
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v4i2.258

Abstract

This study proposes an automatic Dewey Decimal Classification (DDC) classification framework for Indonesian book metadata by integrating the IndoBERT model strengthened through weighted loss and context enhancement mechanisms. The current escalation of digital book collections poses significant challenges in classification efficiency and information retrieval, while the manual DDC classification process still relies on librarian expertise and is relatively time-consuming. The dataset used includes 2,516 book metadata obtained through the Google Books API and mapped into 14 DDC categories. The context enhancement strategy is implemented by integrating book titles and descriptions into a single text representation, while weighted cross-entropy loss, random oversampling, and simple data augmentation techniques are applied to address class imbalance issues. Model performance is evaluated based on accuracy, precision, recall, and F1-score metrics. Experimental results show that the proposed approach achieves an accuracy of 90.14% and a weighted F1-score of 90.15%, outperforming the baseline IndoBERT model, which only achieved an accuracy of 47.82% and a weighted F1-score of 47.06%. These findings indicate that the combination of weighted loss and contextual text representation can improve the semantic understanding of book metadata while reducing bias towards the majority class in Transformer-based DDC classification.
Co-Authors Joko Purwanto Mahardika, Fajar Muhammad Abdul Muin