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All Journal Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Edukasi Islami: Jurnal Pendidikan Islam Mobile and Forensics Khazanah Pendidikan Islam Eduprof
Hanif, Abdullah
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Religion Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Library & Information Science Mathematics Neuroscience Other

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Ekstraksi Fitur Pengenalan Emosi Berdasarkan Ucapan Menggunakan Linear Predictor Ceptral Coeffecient Dan Mel Frequency Cepstrum Coefficients Helmiyah, Siti; Riadi, Imam; Umar, Rusydi; Hanif, Abdullah
Mobile and Forensics Vol 1, No 2 (2019)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v1i2.1259

Abstract

Ucapan suara memiliki informasi penting yang dapat diterima oleh otak melalui gelombang suara. Otak menerima gelombang suara melalui alat pendengaran dan menghasilkan suatu informasi berupa pesan, bahasa, dan emosi. Pengenalan emosi wicara merupakan teknologi yang dirancang untuk mengidentifikasi keadaan emosi seseorang dari sinyal ucapannya. Hal tersebut menarik untuk diteliti, karena berkaitan dengan teknologi zaman sekarang yaitu pada penggunaan smartphone di berbagai macam aktivitas sehari-hari. Penelitian ini membandingkan ekstraksi fitur Metode LPC dan Metode MFCC. Kedua metode ekstraksi tersebut diklasifikasi menggunakan Metode Jaringan Syaraf Tiruan (MLP) untuk pengenalan emosi. Masing-masing metode menggunakan data emosi marah, bosan, bahagia, netral, dan sedih. Data dibagi menjadi dua, yaitu data testing dan data data training dengan perbandingan 80:20. Arsitektur jaringan yang digunakan adalah tiga lapisan yaitu lapisan input, lapisan tersembunyi, dan lapisan output. Parameter MLP yang digunakan learning rate = 0.0001, epsilon = 1e-08, epoch = 500, dan Cross Validation = 5. Hasil akurasi pengenalan emosi dengan ekstraksi fitur LPC sebesar adalah 28%. Sedangkan hasil akurasi dengan ekstraksi fitur MFCC sebesar 61,33%. Hasil akurasi ini bisa ditingkatkan dengan menambahkan data yang lebih banyak lagi, terutama untuk data testing. Perlunya pengujian pada nilai parameter jaringan MLP, yaitu dengan mengubah nilai-nilai parameter, karena dapat mempengaruhi tingkat akurasi pengenalan. Selain itu penentuan ekstraksi fitur dan klasifikasi metode yang lain juga dapat digunakan untuk mencari nilai akurasi pengenalan emosi yang lebih baik lagi.
Speech Classification to Recognize Emotion Using Artificial Neural Network Helmiyah, Siti; Riadi, Imam; Umar, Rusydi; Hanif, Abdullah
Khazanah Informatika Vol. 7 No. 1 April 2021
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v7i1.11913

Abstract

This study seeks to identify human emotions using artificial neural networks. Emotions are difficult to understand and hard to measure quantitatively. Emotions may be reflected in facial expressions and voice tone. Voice contains unique physical properties for every speaker. Everyone has different timbres, pitch, tempo, and rhythm. The geographical living area may affect how someone pronounces words and reveals certain emotions. The identification of human emotions is useful in the field of human-computer interaction. It helps develop the interface of software that is applicable in community service centers, banks, education, and others. This research proceeds in three stages, namely data collection, feature extraction, and classification. We obtain data in the form of audio files from the Berlin Emo-DB database. The files contain human voices that express five sets of emotions: angry, bored, happy, neutral, and sad. Feature extraction applies to all audio files using the method of Mel Frequency Cepstrum Coefficient (MFCC). The classification uses Multi-Layer Perceptron (MLP), which is one of the artificial neural network methods. The MLP classification proceeds in two stages, namely the training and the testing phase. MLP classification results in good emotion recognition. Classification using 100 hidden layer nodes gives an average accuracy of 72.80%, an average precision of 68.64%, an average recall of 69.40%, and an average F1-score of 67.44%.This study seeks to identify human emotions using artificial neural networks. Emotions are difficult to understand and hard to measure quantitatively. Emotions may be reflected in facial expressions and voice tone. Voice contains unique physical properties for every speaker. Everyone has different timbres, pitch, tempo, and rhythm. The geographical living area may affect how someone pronounces words and reveals certain emotions. The identification of human emotions is useful in the field of human-computer interaction. It helps develop the interface of software that is applicable in community service centres, banks, and education and others. This research proceeds in three stages, namely data collection, feature extraction, and classification. We obtain data in the form of audio files from the Berlin Emo-DB database. The files contain human voices that express five sets of emotions: angry, bored, happy, neutral and sad. Feature extraction applies to all audio files using the method of Mel Frequency Cepstrum Coefficient (MFCC). The classification uses Multi-Layer Perceptron (MLP), which is one of the artificial neural network methods. The MLP classification proceeds in two stages, namely the training and the testing phase. MLP classification results in good emotion recognition. Classification using 100 hidden layer nodes gives an average accuracy of 72.80%, an average precision of 68.64%, an average recall of 69.40%, and an average F1-score of 67.44%.
Ekstraksi Fitur Pengenalan Emosi Berdasarkan Ucapan Menggunakan Linear Predictor Ceptral Coeffecient Dan Mel Frequency Cepstrum Coefficients Helmiyah, Siti; Riadi, Imam; Umar, Rusydi; Hanif, Abdullah
Mobile and Forensics Vol. 1 No. 2 (2019)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v1i2.1259

Abstract

Ucapan suara memiliki informasi penting yang dapat diterima oleh otak melalui gelombang suara. Otak menerima gelombang suara melalui alat pendengaran dan menghasilkan suatu informasi berupa pesan, bahasa, dan emosi. Pengenalan emosi wicara merupakan teknologi yang dirancang untuk mengidentifikasi keadaan emosi seseorang dari sinyal ucapannya. Hal tersebut menarik untuk diteliti, karena berkaitan dengan teknologi zaman sekarang yaitu pada penggunaan smartphone di berbagai macam aktivitas sehari-hari. Penelitian ini membandingkan ekstraksi fitur Metode LPC dan Metode MFCC. Kedua metode ekstraksi tersebut diklasifikasi menggunakan Metode Jaringan Syaraf Tiruan (MLP) untuk pengenalan emosi. Masing-masing metode menggunakan data emosi marah, bosan, bahagia, netral, dan sedih. Data dibagi menjadi dua, yaitu data testing dan data data training dengan perbandingan 80:20. Arsitektur jaringan yang digunakan adalah tiga lapisan yaitu lapisan input, lapisan tersembunyi, dan lapisan output. Parameter MLP yang digunakan learning rate = 0.0001, epsilon = 1e-08, epoch = 500, dan Cross Validation = 5. Hasil akurasi pengenalan emosi dengan ekstraksi fitur LPC sebesar adalah 28%. Sedangkan hasil akurasi dengan ekstraksi fitur MFCC sebesar 61,33%. Hasil akurasi ini bisa ditingkatkan dengan menambahkan data yang lebih banyak lagi, terutama untuk data testing. Perlunya pengujian pada nilai parameter jaringan MLP, yaitu dengan mengubah nilai-nilai parameter, karena dapat mempengaruhi tingkat akurasi pengenalan. Selain itu penentuan ekstraksi fitur dan klasifikasi metode yang lain juga dapat digunakan untuk mencari nilai akurasi pengenalan emosi yang lebih baik lagi.
From Tafaqquh Fiddin to Applied Sciences: The Transformation of Islamic Education in Indonesia Hanif, Abdullah; Ma'mur, Ilzamudin; Gunawan, Agus
Khazanah Pendidikan Islam Vol. 6 No. 3 (2024): Khazanah Pendidikan Islam
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kpi.v6i3.41500

Abstract

In facing the demands of globalisation and the Fourth Industrial Revolution, Islamic education in Indonesia encounters challenges to remain relevant by preserving religious values while responding to the need for practical skills. This study aims to explore the transformation of Islamic education in Indonesia, particularly in the context of the shift from the scholarly tradition of tafaqquh fiddin (deep understanding of religion) to applied sciences. The research evaluates how Islamic boarding schools (pesantren), Islamic schools (madrasah), and Islamic higher education institutions (PTKI, or Perguruan Tinggi Keagamaan Islam) adapt to the demands of globalisation and modern economic developments requiring practical and professional skills. This study employs a qualitative approach by analysing literature, curricula, and policies related to Islamic education in Indonesia. Data were collected from various sources such as journals, books, and policy documents. The findings reveal that Islamic education in Indonesia has undergone significant transformation. Pesantren have begun integrating vocational skills such as agribusiness and information technology, madrasah have broadened their focus to include academic education and practical skills, while PTKI have adopted non-religious programmes such as economics and health sciences. This transformation has produced graduates who not only possess profound religious understanding but also practical skills relevant to the modern job market. The study underscores the importance of integrating religious education with applied sciences to ensure the relevance of Islamic education in the modern era. These findings provide a foundation for the development of adaptive educational policies, such as competency-based curricula and support for vocational education. This research also offers a unique contribution to the literature on Islamic education by highlighting a significant shift in the scholarly tradition in Indonesia, particularly in balancing religious values with applicative skills for success in the professional world.
INTEGRATION OF RELIGIOUS MODERATION IN ISLAMIC EDUCATION: CHALLENGES AND OPPORTUNITIES IN THE DIGITAL ERA Hanif, Abdullah; Syarifudin, Encep; Muhtarom, Ali
Edukasi Islami: Jurnal Pendidikan Islam Vol. 14 No. 01 (2025): Edukasi Islami: Jurnal Pendidikan Islam
Publisher : Sekolah Tinggi Agama Islam Al Hidayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30868/ei.v14i01.7767

Abstract

Background: In the face of increasing radicalism and intolerance, Islamic education in Indonesia plays a crucial role in fostering religious moderation. Purpose: This study examines the role of Islamic education in promoting religious moderation in Indonesia, focusing on the challenges and opportunities presented by the digital and globalized era. Method: Using a qualitative approach with a literature review, the study analyzes data from journals, research reports, and academic articles on religious moderation and Islamic education. Result: The findings indicate that Islamic educational institutions have successfully integrated religious moderation values into their curricula, emphasizing tolerance, non-violence, and respect for diversity. However, challenges remain, including insufficient teacher readiness, the negative influence of technology, and students' shallow understanding of religious moderation. The study suggests that improving teacher training, managing technology’s impact on education, and providing consistent institutional support are essential for strengthening religious moderation programs. Conclusion: This research contributes to understanding how digitalization and globalization affect religious moderation efforts in Islamic education and offers strategic solutions to enhance their effectiveness.
Implementation of Transdisciplinary Approaches in Islamic Education to Face Contemporary Global Challenges Hanif, Abdullah; Wahyudin, Wawan; Sholahuddin, Sholahuddin
Eduprof : Islamic Education Journal Vol. 6 No. 2 (2025): Eduprof : Islamic Education Journal
Publisher : Program Pascasarjana, Universitas Islam Bunga Bangsa Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47453/eduprof.v6i2.283

Abstract

This research aims to explore the application of a transdisciplinary approach in Islamic education, with a focus on its integration with contemporary global challenges, such as social, environmental, and technological issues. This study uses a qualitative method with a literature study approach. Data is collected from a variety of secondary sources, such as books, journal articles, and official documents. Data analysis was carried out thematically to find patterns and relationships between transdisciplinary approaches and Islamic education. The focus of the research is the theoretical exploration of transdisciplinary education in the Islamic context. The findings show that the transdisciplinary approach at Sakinah Circle successfully integrates various disciplines such as science, mathematics, history, and language with Qur'anic values. Each theme taught, such as "Water" and "Samawat", provides a holistic learning experience, combining scientific, spiritual, and ethical dimensions. This approach prepares students to face contemporary challenges by fostering intellectual and spiritual development simultaneously. This research highlights the important role of a transdisciplinary approach in modernizing Islamic education to confront global issues such as environmental sustainability and social inequality. The study also demonstrates the need for institutional support in implementing this approach, as well as suggesting that transdisciplinary learning can enhance critical thinking skills, creativity, and collaboration in the context of Islamic education. This research makes an original contribution by linking the transdisciplinary approach to Islamic education, emphasizing its potential in bridging the gap between traditional religious teachings and the demands of the 21st century. This research offers a new perspective on how Islamic education can evolve to face global challenges while maintaining its core values.
Co-Authors Agus Gunawan Helmiyah, Siti Ilzamudin Imam Riadi Rusydi Umar Sholahuddin Syarifudin, Encep wahyudin, wawan