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Konjungsi pada Kanal Youtube Mata Najwa episode “Putusan MK: Publik Memang Seharusnya Marah” Ramadhan, M. Raihan; Asnawi, Asnawi
Jurnal Bahasa dan Sastra Vol 12, No 1 (2024)
Publisher : Faculty of Languages and Arts, Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jbs.v12i1.127741

This research investigates the role of conjunctions in constructing cohesive narratives on Najwa Shihab's YouTube channel in the episode “Putusan MK: Publik Memang Seharusnya Marah”. Employing a qualitative discourse analysis approach, data was collected through non-participant observation and analyzed using Moeliono et al.'s (2017) framework for the types and functions of conjunctions. The analysis results demonstrate that both coordinating and subordinating conjunctions remain integral elements in Shihab's narratives. These conjunctions serve various functions, including providing contextual details to enhance explanations, emphasizing Shihab's viewpoints, and presenting perspectives or alternative choices to the viewers. Ultimately, this study highlights how Shihab's strategic use of conjunctions promotes coherence in her narratives, fostering audience engagement and understanding.

Design of a Quick Response Code-Based Infrastructure Management Information System Sukron, Moh.; Ramadhan, M. Raihan; Sihabillah, Ahmad
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 3 No 2 (2024): September 2024
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v3i2.4653

The management of infrastructure and facilities at MTs Mambaul Hasan Sumberrejo Paiton Probolinggo is currently conducted manually, resulting in significant issues such as data inaccuracies, misplacement of items, and difficulties in tracking asset movements. These challenges reduce efficiency and hinder effective inventory management. The aim of this research is to design and develop a Quick Response (QR) Code-based management information system to enhance the efficiency and effectiveness of infrastructure and facilities management at MTs Mambaul Hasan. This research method is based on Research and Development (R&D) with a quantitative approach and a case study framework. The process includes system requirements analysis through direct observation and interviews with school staff, followed by system design using the Object-Oriented Analysis and Design (OOAD) approach. A prototype is then developed and tested to gather user feedback, and system evaluation is conducted to refine the system before full implementation. The results of this research are a QR Code-based infrastructure and facilities management information system that simplifies asset registration, enhances tracking accuracy, and reduces manual workload. Usability testing with school staff revealed an 82,67% satisfaction rate, indicating a significant improvement in efficiency and traceability of assets. The implementation of this system provides a practical and effective solution for managing infrastructure and facilities at MTs Mambaul Hasan. This study concludes that the QR Code-based system improves efficiency, accuracy, and traceability in inventory management. The implications of these findings suggest that other educational institutions can adopt similar technological solutions to modernize their management processes, with potential future integration of mobile and cloud technologies for enhanced usability and scalability.

Design of a Quick Response Code-Based Infrastructure Management Information System Sukron, Moh.; Ramadhan, M. Raihan; Sihabillah, Ahmad
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 3 No. 2 (2024): September 2024
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v3i2.4653

The management of infrastructure and facilities at MTs Mambaul Hasan Sumberrejo Paiton Probolinggo is currently conducted manually, resulting in significant issues such as data inaccuracies, misplacement of items, and difficulties in tracking asset movements. These challenges reduce efficiency and hinder effective inventory management. The aim of this research is to design and develop a Quick Response (QR) Code-based management information system to enhance the efficiency and effectiveness of infrastructure and facilities management at MTs Mambaul Hasan. This research method is based on Research and Development (R&D) with a quantitative approach and a case study framework. The process includes system requirements analysis through direct observation and interviews with school staff, followed by system design using the Object-Oriented Analysis and Design (OOAD) approach. A prototype is then developed and tested to gather user feedback, and system evaluation is conducted to refine the system before full implementation. The results of this research are a QR Code-based infrastructure and facilities management information system that simplifies asset registration, enhances tracking accuracy, and reduces manual workload. Usability testing with school staff revealed an 82,67% satisfaction rate, indicating a significant improvement in efficiency and traceability of assets. The implementation of this system provides a practical and effective solution for managing infrastructure and facilities at MTs Mambaul Hasan. This study concludes that the QR Code-based system improves efficiency, accuracy, and traceability in inventory management. The implications of these findings suggest that other educational institutions can adopt similar technological solutions to modernize their management processes, with potential future integration of mobile and cloud technologies for enhanced usability and scalability.

Bapak Analisis dan Prediksi Diabetes Menggunakan Artificial Neural Network dengan Dataset CDC Diabetes Health Indicators : Analisis dan Prediksi Diabetes Menggunakan Artificial Neural Network dengan Dataset CDC Diabetes Health Indicators Dwi, Dodi Dwi Riskianto; Afandi, Muhammad; Ramadhan, M. Raihan; Sudriyanto, Sudriyanto
Jurnal Riset Sistem dan Teknologi Informasi Vol. 4 No. 1 (2026): Vol. 4 No. 1 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v4i1.2096

Diabetes mellitus is a chronic disease with increasing prevalence and requires effective early detection efforts. This study aims to develop a diabetes risk prediction model using an Artificial Neural Network (ANN) based on non-laboratory health indicators. The dataset used is the CDC Diabetes Health Indicators with a large amount of data and characteristics of classes that are not fully balanced. The research stages include data preprocessing that includes handling missing values, encoding categorical data using one-hot encoding, normalization of numerical features, and analysis of the target class distribution. The ANN model was trained using a Multilayer Perceptron architecture with dropout regularization and L2 penalty and AdamW optimization. The evaluation results show that the model achieved an accuracy of 86.45%, a precision of 85.2%, a recall of 82.7%, and an AUC-ROC value of 0.89. Although the accuracy is in the medium range for a large dataset, the high AUC value indicates excellent model discrimination ability. This performance is affected by the limited number of non-laboratory features used and the imbalanced class distribution. The findings of this study indicate that ANN based on simple health indicators has the potential to be used as a diabetes risk screening tool in primary healthcare. Further research is recommended to apply class balancing techniques, model interpretability analysis, and external validation in the Indonesian population.

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