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All Journal EKONOMIA Jurnal sistem informasi, Teknologi informasi dan komputer JPPUMA: Jurnal Ilmu Pemerintahan dan Sosial Politik Universitas Medan Area Kemudi Lingua Skolastika JURTEKSI Ensiklopedia of Journal Ensiklopedia Social Review JURNAL LENTERA BISNIS bit-Tech Jurnal Ranah Publik Indonesia Kontemporer (Rapik) Journal of Economics Research and Policy Studies Kybernology : Journal of Government Studies Ensiklopedia Research and Community Service Review Tensile : Jurnal Pengabdian Kepada Masyarakat Jurnal Ekonomi dan Bisnis Journal of Contemporary Local Politics PANDAWA : Jurnal Pengabdian kepada Masyarakat Indonesian Journal of Sustainability Policy and Technology
Maulana, Muhammad Akbar
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Optimalisasi Teknologi untuk Efisiensi dan Transparansi Dalam Pengawasan Pengelolaan Sampah di Kota Serang Maulana, Muhammad Akbar; Syukri, Ahmad; Nurfaisal, Muhammad Dwi; Sari, Inrinofita
Kybernology : Journal of Government Studies Vol 5, No 1 (2025): April 2025
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/kjgs.v5i1.17802

Abstract

The problem of waste management in Serang City is still a serious challenge, especially in terms of the efficiency and transparency of the supervision system. The low use of technology in monitoring waste management causes delays in transportation, lack of data accuracy, and lack of community participation in the reporting system. This research aims to develop digital transformation-based solutions to increase the effectiveness of waste management supervision in Serang City. This research uses a qualitative method approach with a participatory strategy involving academics, local governments, and the community. Data was collected through observations, in-depth interviews, and literature studies on digital technology in waste management. The implementation is carried out in Cipocok Jaya Village with the development and implementation of GIS-based applications, the Internet of Things (IoT), and a real-time monitoring system. The results of the study show that the use of digital technology is able to increase the efficiency of waste transportation supervision, reduce the pile of waste at vulnerable points, and strengthen transparency in the reporting system. Thus, digital innovation in waste management supervision can be an effective model in supporting sustainable environmental policies in Serang City.Permasalahan pengelolaan sampah di Kota Serang masih menjadi tantangan serius, terutama dalam aspek efisiensi dan transparansi sistem pengawasan. Rendahnya pemanfaatan teknologi dalam monitoring pengelolaan sampah menyebabkan keterlambatan pengangkutan, kurangnya akurasi data, serta minimnya partisipasi masyarakat dalam sistem pelaporan. Penelitian ini bertujuan untuk mengembangkan solusi berbasis transformasi digital guna meningkatkan efektivitas pengawasan pengelolaan sampah di Kota Serang. Penelitian ini menggunakan pendekatan metode kualitatif dengan strategi partisipatif yang melibatkan akademisi, pemerintah daerah, serta masyarakat. Data dikumpulkan melalui observasi, wawancara mendalam, serta studi literatur mengenai teknologi digital dalam pengelolaan sampah. Implementasi dilakukan di Kelurahan Cipocok Jaya dengan pengembangan dan penerapan aplikasi berbasis GIS, Internet of Things (IoT), serta sistem pemantauan real-time. Hasil penelitian menunjukkan bahwa pemanfaatan teknologi digital mampu meningkatkan efisiensi pengawasan pengangkutan sampah, mengurangi tumpukan sampah di titik-titik rawan, serta memperkuat transparansi dalam sistem pelaporan. Dengan demikian, inovasi digital dalam pengawasan pengelolaan sampah dapat menjadi model yang efektif dalam mendukung kebijakan lingkungan berkelanjutan di Kota Serang.
Transformasi Layanan Publik di Kabupaten Gowa: Penerapan Mal Pelayanan Publik untuk Meningkatkan Efisiensi dan Aksesibilitas Sari, Inrinofita; Dwi Nurfaisal, Muhammad; Akbar Maulana, Muhammad; Syukri, Ahmad; Wahdaniyah, Nurul
Kybernology : Journal of Government Studies Vol. 5 No. 1 (2025): April 2025
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/kjgs.v5i1.17661

Abstract

This research aims to analyse the implementation of the Public Service Mall (MPP) in Gowa Regency within the framework of public sector governance, by relating it to governance theories such as New Public Management (NPM), New Public Service (NPS), and New Public Governance (NPG). This research focuses on how MPP is able to improve efficiency, transparency, and accessibility of public services for the community. The research method used is a qualitative method with a descriptive approach. Data was collected through document analysis, official reports, and relevant previous research. Analysis was conducted using data reduction, data presentation, and conclusion drawing techniques to produce an in-depth interpretation of the phenomenon under study. The results show that the MPP in Gowa Regency successfully reflects NPM principles through technology integration and simplification of service processes. In addition, the NPS approach is evident from the government's efforts to involve the community through satisfaction surveys and fair and responsive service delivery. The multi-sector collaboration adopted by the MPP reflects the application of NPG principles in improving the effectiveness and sustainability of governance. However, challenges related to digital literacy and infrastructure still affect service accessibility, especially in remote areas. Research limitations include limited primary data that relies solely on documents and data collection, and ended direct observation of MPP operations in Gowa Regency. The implications of the study include recommendations to improve digital community literacy through education programs and the provision of more equitable technology infrastructure in remote areas. In addition, this study provides guidance for other local governments in adopting agile governance principles to improve the quality of public services through the integration of services and technology.
Optimalisasi Teknologi untuk Efisiensi dan Transparansi Dalam Pengawasan Pengelolaan Sampah di Kota Serang Maulana, Muhammad Akbar; Syukri, Ahmad; Nurfaisal, Muhammad Dwi; Sari, Inrinofita
Kybernology : Journal of Government Studies Vol. 5 No. 1 (2025): April 2025
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/kjgs.v5i1.17802

Abstract

The problem of waste management in Serang City is still a serious challenge, especially in terms of the efficiency and transparency of the supervision system. The low use of technology in monitoring waste management causes delays in transportation, lack of data accuracy, and lack of community participation in the reporting system. This research aims to develop digital transformation-based solutions to increase the effectiveness of waste management supervision in Serang City. This research uses a qualitative method approach with a participatory strategy involving academics, local governments, and the community. Data was collected through observations, in-depth interviews, and literature studies on digital technology in waste management. The implementation is carried out in Cipocok Jaya Village with the development and implementation of GIS-based applications, the Internet of Things (IoT), and a real-time monitoring system. The results of the study show that the use of digital technology is able to increase the efficiency of waste transportation supervision, reduce the pile of waste at vulnerable points, and strengthen transparency in the reporting system. Thus, digital innovation in waste management supervision can be an effective model in supporting sustainable environmental policies in Serang City.Permasalahan pengelolaan sampah di Kota Serang masih menjadi tantangan serius, terutama dalam aspek efisiensi dan transparansi sistem pengawasan. Rendahnya pemanfaatan teknologi dalam monitoring pengelolaan sampah menyebabkan keterlambatan pengangkutan, kurangnya akurasi data, serta minimnya partisipasi masyarakat dalam sistem pelaporan. Penelitian ini bertujuan untuk mengembangkan solusi berbasis transformasi digital guna meningkatkan efektivitas pengawasan pengelolaan sampah di Kota Serang. Penelitian ini menggunakan pendekatan metode kualitatif dengan strategi partisipatif yang melibatkan akademisi, pemerintah daerah, serta masyarakat. Data dikumpulkan melalui observasi, wawancara mendalam, serta studi literatur mengenai teknologi digital dalam pengelolaan sampah. Implementasi dilakukan di Kelurahan Cipocok Jaya dengan pengembangan dan penerapan aplikasi berbasis GIS, Internet of Things (IoT), serta sistem pemantauan real-time. Hasil penelitian menunjukkan bahwa pemanfaatan teknologi digital mampu meningkatkan efisiensi pengawasan pengangkutan sampah, mengurangi tumpukan sampah di titik-titik rawan, serta memperkuat transparansi dalam sistem pelaporan. Dengan demikian, inovasi digital dalam pengawasan pengelolaan sampah dapat menjadi model yang efektif dalam mendukung kebijakan lingkungan berkelanjutan di Kota Serang.
Identifikasi Katarak Mata Pada Kucing Dengan Menggunakan Convolutional Neural Network Mikael; Susilo, Joko; Maulana, Muhammad Akbar
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.1881

Abstract

Katarak merupakan salah satu penyakit yang dapat menyerang hewan, termasuk kucing, ditandai dengan kekeruhan pada lensa mata yang dapat menyebabkan gangguan penglihatan hingga kebutaan apabila tidak ditangani. Penyakit ini sering kali tidak terdeteksi pada tahap awal, sehingga diperlukan metode diagnosis dini yang akurat. Penelitian ini bertujuan untuk mengembangkan model Convolutional Neural Network (CNN) sebagai metode pendeteksian katarak pada kucing melalui analisis gambar mata. Subjek penelitian terdiri dari dataset berjumlah 106 gambar mata kucing, yang meliputi 66 gambar mata normal dan 40 gambar mata katarak. Dataset ini dibagi menjadi data training (85 gambar) dan data validasi (21 gambar). Metode penelitian mencakup beberapa tahapan, yaitu studi literatur untuk mendalami teori terkait, preprocessing data untuk memastikan konsistensi dataset, implementasi model CNN, pelatihan model, dan evaluasi performa model menggunakan confusion matrix. Proses pelatihan model dilakukan selama 100 epoch dengan menggunakan optimizer Adam, yang dikenal mampu mempercepat konvergensi model. Arsitektur CNN yang dirancang terdiri dari tiga lapisan konvolusi, lapisan pooling, dan fully connected layer. Hasil penelitian menunjukkan bahwa model CNN yang dikembangkan mampu mencapai akurasi sebesar 71% dalam mengklasifikasikan gambar mata kucing menjadi kategori "Normal" atau "Katarak." Meskipun akurasi ini belum optimal, keterbatasan jumlah dataset menjadi faktor utama yang memengaruhi performa model. Temuan ini memberikan kontribusi awal dalam penerapan kecerdasan buatan untuk deteksi penyakit pada hewan, khususnya katarak pada kucing. Penelitian ini juga menegaskan pentingnya menambah jumlah dan keragaman dataset untuk meningkatkan performa model dan mengurangi risiko overfitting. Potensi pengembangan lebih lanjut dari model ini diharapkan dapat mendukung diagnosis yang lebih cepat dan akurat, sehingga meningkatkan kualitas hidup hewan peliharaan.
Deteksi Suasana Hati Karyawan Berbasis Deep Learning Menggunakan CNN Michelle; Birowo, Sigit; Maulana, Muhammad Akbar
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.1882

Abstract

Emosi adalah bagian penting dari kehidupan manusia yang membantu kita memahami diri sendiri dan mengekspresikan perasaan. Emosi mencerminkan respons atau reaksi alami pada berbagai situasi yang dihadapi. Penelitian ini bertujuan untuk mengembangkan Model Convolutional Neural Network (CNN) yang mampu mengenali emosi manusia berdasarkan ekspresi wajah, khususnya pada kategori “Senang”, “Sedih”, “Marah” dan “Netral” dengan fokus pada karyawan setelah bekerja, untuk melihat apakah karyawan menikmati pekerjaannya atau tidak. Dengan menggunakan dataset berisi 2.059 gambar dari platform Kaggle, proses penelitian mencakup tahapan pengumpulan data, pre-processing data, pelatihan data hingga klasifikasi. Model ini dilatih selama 200 epoch dan menghasilkan akurasi sebesar 89,11% dengan performa yang cukup baik untuk kategori emosi “Senang” dan “Marah”. Namun, model masih mengalami kesultan dalam mengenali emosi “Sedih” dan “Netral”, kemungkinan karena kurangnya data pelatihan dan fitur yang belum optimal. Selama pelatihan, akurasi pada training menunjukkan peningkatan yang konsisten, sedangkan validasi sempat fluktuatif sebelum stabil. Analisis hasil pengujian menunjukkan bahwa model mampu memprediksi emosi dengan probabilitas tinggi, meskipun terdapat kendala dalam generalisasi ke kondisi yang lebih kompleks. Grafik dan evaluasi metriks,seperti precision, recall dan f1-score, menunjukkan adanya ruang untuk perbaikan, terutama dalam pengenalan emosi dengan nilai recall yang rendah. Penelitian ini memiliki potensi signifikan dalam pengenalan emosi melalui ekspresi wajah, yang digunakan untuk memahami emosi yang dialami oleh karyawan. Penelitian ini juga diperlukan pengembangan lebih lanjut guna meningkatkan kemampuan model dalam menangani komplesitas data.
PENGELOLAAN DOKUMEN SARANA PRASARANA DAN ASET PADA SMP NEGERI XYZ JAKARTA Damiyana, Damdam; Maulana, Muhammad Akbar
JURNAL LENTERA BISNIS Vol. 14 No. 3 (2025): JURNAL LENTERA BISNIS, SEPTEMBER 2025
Publisher : POLITEKNIK LP3I JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34127/jrlab.v14i3.1632

Abstract

Document management of infrastructure and assets is a crucial aspect in supporting operational and administrative efficiency at SMP Negeri XYZ Jakarta. However, the current practice still faces various obstacles, such as a manual recording system that is prone to errors, unorganized storage of physical documents, and limited human resource competency. These problems have an impact on inaccurate asset data, slow access to information, and obstacles in budget planning and auditing. This study aims to analyze the process of managing infrastructure and asset documents at SMP Negeri XYZ Jakarta, identify the obstacles faced, and formulate solutions for improvement. The research method uses a qualitative approach with data collection techniques through observation, interviews, and documentation studies. The results of the study indicate three main problems: (1) lack of trained human resources in document management, (2) vulnerability of physical documents to damage or loss, and (3) data discrepancies between documents and the real condition of assets. As a solution, this study recommends strategic steps such as: (1) regular training for asset management staff, (2) digitalization of documents by utilizing the SIMPAN BMN application and cloud storage, and (3) implementation of a barcode system and routine inventory to ensure data accuracy. The implementation of this solution is expected to improve transparency, efficiency, and accountability of school asset management.
DAMPAK KENAIKAN JUMLAH PENDUDUK TERHADAP TINGKAT PENGANGGURAN TERBUKA DI KOTA SERANG TAHUN 2022-2023 Maulana, Muhammad Akbar; Kusumoningtyas, Anggi Anggraeni; Hanif, Fahmi Aminatul
Ensiklopedia of Journal Vol 8, No 1 (2025): Vol. 8 No. 1 Edisi 2 Oktober 2025
Publisher : Lembaga Penelitian dan Penerbitan Hasil Penelitian Ensiklopedia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33559/eoj.v8i1.3457

Abstract

This study aims to analyze the impact of population growth on the open unemployment rate in Serang City in 2022-2023. Serang City, as the capital of Banten Province, is experiencing rapid population growth due to urbanization, migration, and birth factors. This growth poses a serious challenge to the open unemployment rate in Serang City. The research method used is quantitative analysis with a descriptive approach. Data were obtained from the Central Statistics Agency (BPS) and other official sources, and analyzed using statistical methods to see the relationship between population growth and unemployment. The results of the study show a positive correlation between population growth and increasing open unemployment rates. Structural unemployment and economic fluctuations also exacerbate this condition, showing that the imbalance between population and job opportunities further exacerbates the unemployment problem. This study makes an important contribution to understanding the impact of demographics on the labor market in Serang City, and offers strategic guidance for local governments in addressing unemployment problems arising from rapid population growth. It is hoped that with the right intervention, the unemployment rate in Serang City can be reduced and community welfare can be increased. Overall, this study makes an important contribution to the understanding of the impact of demographics on the labor market in Serang City, as well as offering strategic guidance for local governments in addressing unemployment problems arising from rapid population growth. Keywords: Population, Welfare, Local Government, Open Unemployment, Workforce
MANAJEMEN PEMULIHAN PASCABENCANA GEMPA BUMI CIANJUR TAHUN 2022 DALAM PERSPEKTIF KEBIJAKAN PUBLIK Suhaeti, Suhaeti; Syarkawi, Syarkawi; Windra, Pirma; Maulana, Muhammad Akbar; Nurfaisal, Muhammad Dwi
Ensiklopedia of Journal Vol 8, No 2 (2026): Vol. 8 No. 2 Edisi 1 Januari 2026
Publisher : Lembaga Penelitian dan Penerbitan Hasil Penelitian Ensiklopedia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33559/eoj.v8i2.3663

Abstract

This study aims to examine how post-disaster recovery management for the 2022 Cianjur Earthquake was implemented, with a primary focus on the rehabilitation and reconstruction phases after the emergency response period ended. The method used is a literature study, namely by examining various written sources such as official government documents, reports from related institutions, laws and regulations-especially Law Number 24 of 2007 concerning Disaster Management-as well as scientific articles and publications relevant to post-disaster recovery issues. The discussion of this research focuses on the recovery process in Cianjur Regency, which includes physical, social, economic, and public service aspects, including how inter-agency coordination is carried out in the implementation of rehabilitation and reconstruction. The results of the study indicate that post-disaster recovery management for the Cianjur Earthquake has basically referred to the national regulatory framework, but in practice still faces various obstacles, such as weak coordination, inaccurate damage data, and slow recovery of the lives of affected communities. Through this research, it is hoped that it can provide both conceptual and practical contributions for local governments and stakeholders in strengthening post-disaster recovery management to be more effective, integrated, and sustainable in accordance with the provisions of laws and regulations. Keyword : Post-Disaster Recovery, Cianjur Earthquake, Rehabilitation and Reconstruction, Disaster Management 
MULTI-FACE EMOTION DETECTION USING CONVOLUTIONAL NEURAL NETWORKS TINY FACE DETECTOR Istioso, Jason; Gerard, Jeremiah; Marcheleno, Marco; Maulana, Muhammad Akbar
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 12 No. 1 (2025): Desember 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v12i1.4354

Abstract

Abstract: Understanding students’ emotional conditions is important for evaluating engagement and learning atmosphere in classroom environments. However, conventional evaluation methods are often subjective and difficult to apply in real time. Therefore, this study proposes a real-time multi-face emotion detection system designed for classroom learning environments. The system integrates a CNN-based Tiny Face Detector for multi-scale face localization with a convolutional neural network to classify seven facial emotions: angry, disgust, fear, happy, sad, surprise, and neutral. Experimental evaluation was conducted using classroom video data under varying lighting conditions, face orientations, partial occlusions, and different numbers of detected faces per frame. The proposed system achieves stable real-time performance with processing speeds ranging from 10–20 FPS, depending on face density. The results show higher recognition performance for expressive emotions, while subtle emotions remain more challenging. Overall classification accuracy reaches above 80% when emotion predictions are aggregated across multiple faces and time windows. These results indicate that the proposed system is suitable for objective analysis of emotional dynamics in classroom environments and supports the deployment of lightweight emotion-aware monitoring systems for educational applications. Keywords: classroom monitoring; convolutional neural network; facial emotion recognition; multi-face detection; tiny face detector. Abstrak: Pemahaman terhadap kondisi emosional mahasiswa penting untuk mengevaluasi keterlibatan dan suasana pembelajaran di kelas. Namun, metode evaluasi konvensional umumnya bersifat subjektif dan sulit diterapkan secara real-time. Oleh karena itu, penelitian ini mengusulkan sistem deteksi emosi multi-wajah secara real-time yang dirancang untuk lingkungan pembelajaran di kelas. Sistem mengintegrasikan Tiny Face Detector berbasis CNN untuk pelokalan wajah multi-skala dengan jaringan saraf konvolusional untuk mengklasifikasikan tujuh emosi wajah, yaitu marah, jijik, takut, senang, sedih, terkejut, dan netral. Evaluasi eksperimen dilakukan menggunakan data video kelas dengan variasi kondisi pencahayaan, orientasi wajah, oklusi parsial, serta jumlah wajah yang berbeda dalam satu frame. Sistem menunjukkan kinerja real-time yang stabil dengan kecepatan pemrosesan antara 10–20 FPS, bergantung pada kepadatan wajah. Hasil pengujian menunjukkan kinerja yang lebih baik pada emosi ekspresif, sementara emosi dengan ciri halus lebih menantang untuk dikenali. Akurasi klasifikasi keseluruhan mencapai di atas 80% ketika hasil emosi diagregasi berdasarkan banyak wajah dan interval waktu. Hasil ini menunjukkan bahwa sistem yang diusulkan berpotensi digunakan untuk analisis objektif dinamika emosi di kelas serta mendukung pemantauan lingkungan pembelajaran berbasis kecerdasan buatan. Kata kunci: pengenalan emosi wajah; deteksi multi-wajah; Tiny Face Detector; jaringan saraf konvolusional; pemantauan kelas.
Determination of Political Participation: Money Politics and Voter Political Behavior in the 2020 Batanghari Regional Election SYUKRI, AHMAD; SARI, INRINOFITA; MAULANA, MUHAMMAD AKBAR; NURFAISAL, MUHAMMAD DWI
Kemudi Vol 10 No 2 (2026): Kemudi: Jurnal Ilmu Pemerintahan
Publisher : Program Studi Ilmu Pemerintahan Fakultas Ilmu Sosial dan Ilmu Politik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31629/kemudi.v10i2.8255

Abstract

Political participation is an activity or various voluntary activities of the community to take part in the election process for the ruler. The purpose of this study is to see whether Money Politics and Voter Political Behavior have an influence on the Level of Political Participation in the 2020 Batanghari Regency Election. This study uses a quantitative method with data collection techniques assisted through Google Forms in compiling questionnaires distributed to respondents. This study uses simple random sampling with a population of people who have the right to vote in the 2020 Batanghari Regency Election. This study uses the Slovin formula by taking a sample of 50 respondents. The results of this study indicate that the variables of Giving Money (X1), Giving Goods (X2), and Psychological Approach (X4) have a positive value or have a significant effect on the Level of Political Participation in the 2020 Batanghari Regency Election. Meanwhile, the Sociological Approach variable (X3) has a negative value or does not have a significant effect on the Level of Political Participation in the 2020 Batanghari Regency Election. Furthermore, the interpretation of the regression results and R-Square on the Political Participation Level (TPP) variable is 95%, so the scale obtained is in the strong or good category.
Co-Authors Achmad Nurmandi Ahmad Syukri Ahmad Syukri . Aprilia Sapira Aptasari, Fety Widianti Az Zahro, Luthfi Alya Damdam Damiyana Dian Eka Rahmawati, Dian Eka Dwi Nurfaisal, Muhammad Fahmi Amanatul Hanif Faiz Izzuddin Febiona, Adra Olivia Gerard, Jeremiah Hanif, Fahmi Aminatul Hanif, Nita Aribah Inrinofita Sari Istioso, Jason Joko Susilo Kusumoningtyas, Anggi Anggraeni Marcheleno, Marco Michelle Mikael Muhammad Dwi Nurfaisal Muhammad Helmi Falah Nabil Al Fatih, Muhammad Nadifa, Najwa Tyas Novera Martilova Nurfaisal, Muhammad Dwi Pramesti, Ervy Agisti Ardhia Purnomo, Juanda Gilang Putri Pratama, Andayani Putri, Giesta Rahguna Sigit Birowo Situmeang, Firman Yahya Suhaeti, Suhaeti Sulastri Sulastri Syarkawi Tutik Lestari Wahdaniyah, Nurul Winata, Leonard Windra, Pirma Yusa’ Farchan Yuwono, Althanino Ligar Zakaria Habib Al-Ra’zie