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All Journal KOMPUTA : Jurnal Ilmiah Komputer dan Informatika Adabiyah: Jurnal Pendidikan Islam
Janah, Roikhatul
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Computer Science & IT Education Other

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Analysis of Maharah Qira'ah Learning Based on E-Learning for Fourth Siemester Students of the PBA Study Program in the Era of the Covid-19 Pandemc: Analisis Pembelajaran Maharah Qira'ah Berbasis E-Learning Mahasiswa Semester IV Prodi PBA di Era Pandemi Covid-19 Janah, Roikhatul; Anwar, Najih
Adabiyah: Jurnal Pendidikan Islam Vol. 5 (2023): September
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1643.695 KB) | DOI: 10.21070/adabiyah.v5i0.1682

Abstract

The purpose of this research to describe the learning process of maharah qira'ah based on e-learning for fourth semester students of PBA UMSIDA study program in the era of the covid-19 pandemic. This study uses a qualitative research approach. Data collection techniques used are interviews, observation and documentation. The data analysis technique is data reduction, data display and verification. The results of this study indicate that: planning for e-learning-based maharah qira'ah includes: socialization activities, providing training and guidelines, preparing learning materials, Semester Learning Plans (RPS), and filling in e-learning. The implementation of learning uses the reading method. The learning evaluation includes: assignment, UTS, UAS and individual evaluation. Supporting factors: the use of supporting applications, flexible e-learning characters, UMSIDA wifi facilities, quotas from UMSIDA and the government and the presence of electronic devices. Inhibiting factors: lack of lecturer supervision, less stable internet network, lack of internet quota, lack of interaction between lecturers and students, unclear and detailed explanations, lack of student understanding, limited time and student laziness.
Klasifikasi Jenis Burung Berdasarkan Suara Kicau Menggunakan Ekstraksi MFCC dan BiLSTM Janah, Roikhatul; Susanto, Eko Budi; Setiawan, Tri Agus
Komputa : Jurnal Ilmiah Komputer dan Informatika Vol 14 No 2 (2025): Komputa : Jurnal Ilmiah Komputer dan Informatika
Publisher : Program Studi Teknik Informatika - Universitas Komputer Indonesia (UNIKOM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputa.v14i2.17694

Abstract

Automatic bird species classification based on chirping sounds has become an important solution to support conservation efforts for Indonesia's biodiversity, which comprises 1.835 bird species. This study proposes a classification system that combines Mel-Frequency Cepstral Coefficients (MFCC) feature extraction with Bidirectional Long Short-Term Memory (BiLSTM) architecture to identify 10 commonly found Indonesian bird species. The research dataset utilized 750 bird sound recordings from the xeno-canto.org platform, segmented into 4-second duration clips and augmented to 3,750 samples through pitch shift and time stretch techniques. MFCC feature extraction with 40 coefficients was employed to represent the spectral characteristics of bird sounds, while the BiLSTM model was selected to capture complex bi-directional temporal dependencies in bird vocal signals. In the testing process, an 80:20 data split was performed for training and testing. Confusion matrix analysis confirms the model's capability to distinguish unique characteristics of each species with minimal error rates. Research results demonstrate that the system achieved a classification accuracy of 98%. The combination of MFCC and BiLSTM proves effective for automated and sustainable biodiversity monitoring and bird conservation applications in Indonesia.
Co-Authors Anwar, Najih Ihtiari, Dhiya Ayu Tsamrotul Susanto, Eko Budi Tri Agus Setiawan