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All Journal Teknosains: Media Informasi Sains dan Teknologi Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal INSYPRO (Information System and Processing) JURNAL INSTEK (Informatika Sains dan Teknologi) Iqtishaduna : Jurnal Ilmiah Mahasiswa Hukum Ekonomi Syariah Agents: Journal of Artificial Intelligence and Data Science Jurnal Rekayasa Sistem Informasi dan Teknologi Journal of Information Technology and its Utilization
Andi Kambau, Ridwan
Universitas Islam Negeri Alauddin Makassar
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Physics

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Agentic AI untuk Otomatisasi dan Personalisasi Layanan Akademik di Perguruan Tinggi Kambau, Ridwan Andi
Jurnal INSYPRO (Information System and Processing) Vol 10 No 1 (2025)
Publisher : Prodi Sistem Informasi UIN Alauddin

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Abstract

The transformation of higher education institutions from conventional Information Technology (IT)-based systems to Smart Universities requires a systemic and adaptive approach based on artificial intelligence. This study proposes and evaluates the design of an Agentic AI architecture to support academic management and services proactively and autonomously. Using a Design Science Research (DSR) approach, this study designs a multi-agent architecture-based system consisting of sub-agents such as Academic Planner, Advising Agent, and Evaluation Agent. The system was tested with a data sample based on academic service simulation using 500 student entries. The test results show an increase in academic service efficiency, characterized by an average response time of 880 ms, a KRS recommendation accuracy of 92.4%, and a user satisfaction level of 4.5 out of 5. A comparison of the baseline and state-of-the-art shows significant improvements in terms of interoperability, personalization, and operational efficiency. This study concludes that the Agentic AI architecture can be a strategic framework in accelerating the digitalization of academic services and supporting the transformation of higher education institutions towards AI-based Smart Universities.
SISTEM PENDUKUNG KEPUTUSAN REKOMENDASI PEMBERIAN BANTUAN SOSIAL DENGAN MULTI OBJECTIVE OPTIMIZATION BY RATIO ANALYSIS (MOORA) Ramli, Zulhisham; Kambau, Ridwan Andi; Hariani, Hariani
AGENTS: Journal of Artificial Intelligence and Data Science Vol 4 No 1 (2024): Vol 4 No 1 (2024): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/jagti.v4i1.78

Abstract

Cash Direct Assistance (BLT) is one of the conditional assistance programs from the government as a form of poverty alleviation program. The selection process of potential recipients of BLT in Lamatti Riaja Village, Sinjai Regency, it is not entirely accurate as it is still done manually, resulting in many recipients not meeting the criteria. Based on this, research is conducted to design a decision support system that will facilitate the automatic checking of data for eligible residents who are entitled to BLT funds for each disbursement. This aims to make the selection process more objective, time-efficient, and minimize potential errors in selecting BLT recipients. In this research, the Multi Objective Optimization By Ratio Analysis (MOORA) method is employed. The calculation process utilizes the MOORA algorithm, and the implementation of the system is in the form of a website using the System Development Life Cycle design method, providing good and accurate results. The testing method used is Black Box testing. This research produces a Decision Support System  website with the implementation of a data management subsystem using MySQL. The simulation results of the BLT recipient data calculation using the MOORA algorithm minimize errors in the selection process for potential BLT recipients.
LOOKING FOR QUR’AN TEACHER WITH THE HAVERSINE FORMULA METHOD A. MUHAMMAD SYAFAR; RIDWAN A. KAMBAU; NURUL HIKMAH MULYANAH
Journal of Information Technology and Its Utilization Vol 4 No 2 (2021)
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.4.2.4251

Abstract

Education to read and write the Qur'an is the most important thing in Muslim life. The problem that arises is the difficulty of getting a schedule fit between prospective Koran teachers and students, besides the lack of places to study the Koran for adults is also a problem that should be a concern for the sake of the ongoing process of learning the Qur'an.The research method used in this study is a qualitative research method with an experimental approach for programming methods using the Haversine Formula method. The results of this research are in the form of the development of Private Recitation Service and Report Applications Using the Android-Based Haversine Formula Method which can be used to facilitate the community in the process of searching for private Using the Haversine Formula Method Based on Android with distance calculation accuracy rate is 98.92%  
PEMETAAN PERKEMBANGAN BISNIS DIGITAL ISLAM DI INDONESIA: ANALISIS BIBLIOMETRIK Jessika Gafur Lamba; Sudirman; Ridwan Kambau; Syaifullah
Iqtishaduna: Jurnal Ilmiah Mahasiswa Hukum Ekonomi Syariah Vol 7 No 2 (2026): Januari
Publisher : Jurusan Hukum Ekonomi Syariah Fakultas Syariah dan Hukum Uin Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/iqtishaduna.v7i2.63177

Abstract

Abstract This study explores the development of Islamic Digital Business in Indonesia, focusing on the growth and trends of digital transformation within Islamic business practices from 2011 to 2026. With the rapid growth of digital technologies, this research examines how Islamic principles are integrated into digital business models, particularly in the context of e-commerce, small and medium-sized enterprises (SMEs), and digital innovation. The study aims to identify key themes, emerging trends, and gaps in the existing literature, providing a comprehensive understanding of the field. A bibliometric analysis of relevant scholarly articles is conducted to assess global contributions and identify leading countries, institutions, and authors. The research methodology includes thematic analysis to explore dominant themes such as business performance, digital transformation, and business sustainability, along with underexplored areas like halal certification and Islamic finance. The study also examines the social and ethical implications of digital business in the Islamic context, emphasizing the importance of aligning business practices with Islamic values. Findings reveal that while e-commerce and digital transformation dominate the research landscape, areas like Islamic finance and sustainability remain underexplored. The research highlights the importance of interdisciplinary collaboration and suggests future research directions, particularly in integrating AI with Islamic business models and ensuring ethical and sustainable business practices. This study significantly contributes to the understanding of Islamic digital business in Indonesia, offering insights that can guide future research and practices in the field. Keyword: Islamic Digital Business, Islamic E-commerce, Digital Transformation
COMPARATIVE EVALUATION OF LSTM VARIANTS FOR TRADITIONAL MUSICAL INSTRUMENT AUDIO CLASSIFICATION USING MFCC FEATURES Kambau, Ridwan Andi; Muhammad Syawal Idil Fitrah Baharuddin
Jurnal INSTEK (Informatika Sains dan Teknologi) Vol 11 No 1 (2026): APRIL
Publisher : Department of Informatics Engineering, Faculty of Science and Technology, Universitas Islam Negeri Alauddin, Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/instek.v11i1.66225

Abstract

Classifying traditional musical instrument audio remains challenging due to limited labeled data, strong acoustic variability, and spectral similarity across instruments. This paper proposes an attention-based Long Short-Term Memory (LSTM) model for traditional instrument sound classification using Mel-Frequency Cepstral Coefficients (MFCC) as the feature representation. Three LSTM variants, Bidirectional LSTM, Residual LSTM, and Attention-based LSTM are investigated to identify the most effective temporal architecture for this task. The attention mechanism is specifically integrated to enable the model to prioritize discriminative temporal segments, such as unique attack phases and harmonic decay, which are often obscured in traditional instruments. The dataset comprises 1,000 audio samples from 10 traditional instrument classes. All samples are normalized to 3-second duration and augmented via pitch shifting, time stretching, and additive noise to improve generalization. Using 5-fold cross-validation, the Attention-based LSTM consistently achieves the highest performance, with average accuracy 96.73%. This superiority stems from the mechanism’s ability to surpress irrelevant noise frames while focusing on key spectral-temporal features. Robustnes experiments maintain accuracy above 90% under noisy conditions, suggesting that coupling MFCC with attention-enchanced modeling provides a robust solution for cultural heritage preservation through digital audio recognition.
Co-Authors A. MUHAMMAD SYAFAR ABDI NOOR ALI Hariani Hariani Hariani, Hariani Jessika Gafur Lamba M. HASRUL H Muhammad Syawal Idil Fitrah Baharuddin Mustikasari NURUL HIKMAH MULYANAH Ramli, Zulhisham REZA FAISAL Rismawati. S Rohada Nurman Sri Wahyuni Sudirman Syaifullah Wahyuddin Saputra Yulia Ardana Zainal Arifin Hasibuan Zainal Arifin Hasibuan Zaskia Darajat