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All Journal Jurnal Informatika Global Jurnal Ilmiah Sistem Informasi Journal of Computer Science Application and Engineering Jurnal Sistem Informasi dan Teknik Informatika (JAFOTIK)
Maulana, Muhammad Mico
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Other

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PERENCANAAN ARSITEKTUR ENTERPRISE MENGGUNAKAN TOGAF ADM PADA SARANA WEDDING ORGANIZER Ariati, Nining; Maulana, Muhammad Mico; Juliansyah, M. Agung; Febrianza, M.; Setiawan, Ichan; Fahlevi, Reza; Syaharena, Syaharena
Jurnal Ilmiah Sistem Informasi Vol. 4 No. 2 (2024): Jurnal Ilmiah Sistem Informasi
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/sm.v4i2.108

Abstract

This study aims to design an enterprise architecture using TOGAF ADM for CV Sarana Wedding Organizer. The methodology used is qualitative with a literature study and theoretical analysis approach. Data collection was conducted through observation and interviews. The results show that the implementation of TOGAF ADM can provide structured guidance in developing integrated information systems. The research produced an architectural planning that includes the preliminary phase, architecture vision, business architecture, information systems architecture, technology architecture, and opportunities and solutions. This architectural design is expected to assist CV Sarana Wedding in digital transformation and improving its business operational efficiency.
Early Detection and Mapping of Dengue Fever Outbreaks in Urban Areas Maulana, Muhammad Mico
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 3 No. 1 (2025): JOSAPEN - January
Publisher : PT. Lentera Ilmu Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70356/josapen.v3i1.48

Abstract

Dengue Hemorrhagic Fever (DHF) poses a significant public health challenge in tropical regions like Indonesia, where environmental conditions favor the proliferation of Aedes aegypti mosquitoes. The Karya Maju Health Center, serving eight villages in South Sumatra, struggles with monitoring dengue cases due to manual data recording and limited tools for analyzing outbreak patterns. This study aims to address these challenges by developing a system for early detection and mapping of dengue outbreaks. The methodology employs Unified Modeling Language (UML) diagrams, including use case, activity, and class diagrams, to design an intuitive, user-centered system. Use case diagrams outline interactions between healthcare staff and the system, while activity diagrams map the process flow from data collection to visualization. The interface design prioritizes usability, providing stakeholders with clear and accessible tools for monitoring outbreaks. The system was evaluated through pilot testing, which confirmed its ability to meet all predefined criteria. Users found the interface intuitive, with well-structured menus and visualizations facilitating efficient interaction and data analysis. This study contributes to public health by offering a scalable and effective tool for dengue monitoring, enabling healthcare providers to proactively manage outbreaks and allocate resources more effectively.
A Data-Driven Approach to Dengue Fever Mapping: A Review Maulana, Muhammad Mico; A, Sanmorino
Jurnal Sistem Informasi dan Teknik Informatika (JAFOTIK) Vol. 3 No. 1 (2025): JAFOTIK - February
Publisher : PT. Lentera Ilmu Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70356/jafotik.v3i1.54

Abstract

Dengue fever remains a pressing public health issue, especially in tropical and subtropical regions where urbanization, climate change, and ineffective vector control contribute to frequent outbreaks. Traditional surveillance methods often fall short in providing timely and accurate insights, necessitating data-driven approaches for improved monitoring and intervention. This review explores various computational methodologies, including Geographic Information Systems (GIS), machine learning, and predictive modeling, to enhance dengue outbreak mapping and risk assessment. Studies from Bangladesh, Thailand, Malaysia, and Reunion Island demonstrate how integrating epidemiological data with environmental and socio-economic factors improves outbreak prediction and control efforts. Advanced techniques, such as dynamic mapping of the basic reproduction number (R0) and deep learning models like Long Short-Term Memory (LSTM) networks, further enhance forecasting accuracy. Additionally, innovative control strategies, such as Wolbachia-infected mosquito releases, show promise in reducing dengue transmission. By synthesizing recent research, this review underscores the critical role of data science in strengthening dengue surveillance, prediction, and intervention strategies.
Sistem Informasi Geografis Pemetaan Data Sebaran Penyakit Demam Berdarah Di Wilayah Kerja Puskesmas Karya Maju Maulana, Muhammad Mico; Sanmorino, Ahmad; Marcellina, Dona
Jurnal Ilmiah Informatika Global Vol. 16 No. 2: August 2025
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v16i2.5406

Abstract

Dengue Hemorrhagic Fever (DHF) remains a serious public health problem in Indonesia. In rural areas with limited infrastructure, conventional disease monitoring methods hinder effective dengue prevention. This study aims to design and implement a Web-Based Geographic Information System (GIS) to map the distribution of DHF cases in the working area of Puskesmas Karya Maju. The system is developed using the Agile method through stages of observation, system design, implementation, and testing. The application is built using Laravel, MySQL, and Leaflet.js and includes features such as interactive maps, patient and village data, and real-time statistical visualization. Black Box Testing ensures that all features function correctly. The results show that the system helps improve dengue surveillance and facilitates better decision-making for prevention.
Co-Authors A, Sanmorino Ahmad Sanmorino Ariati, Nining Febrianza, M. Juliansyah, M. Agung Marcellina, Dona REZA FAHLEVI Setiawan, Ichan Syaharena, Syaharena