cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Naety
Contact Email
jurnalmedicom@iocscience.org
Phone
+6281381251442
Journal Mail Official
jurnalmedicom@iocscience.org
Editorial Address
Perumahan Romeby Lestari Blok C, No C14 Deliserdang, Sumatera Utara, Indonesia
Location
Unknown,
Unknown
INDONESIA
Jurnal Teknik Informatika C.I.T. Medicom
Published by Institute of Computer Science
ISSN : 23378646     EISSN : 2721561X     DOI : -
Core Subject : Science,
Computer Science & IT
The Jurnal Teknik Informatika C.I.T a scientific journal of Decision support sistem , expert system and artificial inteligens which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 2 Documents
 1 
Search results for , issue "Vol 17 No 2 (2025): May: Intelligent Decision Support System (IDSS)" : 2 Documents clear
Hungarian maximization model approach for optimizing human resource assignment in multi-site projects Riandari, Fristi; Dalimunthe, Yulia Agustina; Ginting, Ramadhanu; Afifa, Rizky Maulidya; Afrisawati, Afrisawati
Jurnal Teknik Informatika C.I.T Medicom Vol 17 No 2 (2025): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Digital transformation in project management demands the implementation of computational models that are able to handle the complexity of human resource (HR) allocation efficiently and objectively. This study examines the application of the Hungarian algorithm in the form of maximization as a computer science-based optimization solution to the HR assignment problem in multi-location projects. By constructing a benefit matrix calculated from weighted attributes such as technical expertise, experience, and location preference, this study implements linear transformations and matrix processing procedures using a numerical approach in Python. This digitalization process allows the system to perform assignment evaluation and allocation automatically and with high precision. Simulation results on a case study of five workers and five project locations show that the model produces optimal assignments with a total benefit score of 420. This model proves its effectiveness in solving polynomial assignment problems, while expanding the use of the Hungarian algorithm in the domain of applied computer science to support data-driven decision making. This study emphasizes the role of classical algorithms in supporting scalable and replicable digital solutions for modern HR management systems.
Smart City Weather and Disaster Monitoring Architecture: LoRaWAN Integration with COBIT 2019 Governance Yulistiawan, Bambang Saras; A, Galih Prakoso Rizky; Widyastuti, Rifka; Mulianingtyas, RR Octanty
Jurnal Teknik Informatika C.I.T Medicom Vol 17 No 2 (2025): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol17.2025.1267.pp59-74

Abstract

Climate change, urbanization, and the increasing frequency of natural disasters such as floods and forest fires demand that Indonesian cities adopt real-time, integrated, and reliable environmental monitoring systems. Within the context of smart cities, LoRaWAN technology offers wide coverage, low power consumption, and cost-efficient operations, making it highly relevant for city-scale multi-sensor monitoring systems. This study proposes the design of a LoRaWAN-based weather and disaster monitoring system architecture integrated into the smart city framework, while simultaneously adopting the IT governance principles of COBIT 2019. The methodology includes a literature review and the mapping of five COBIT domains (EDM03, APO03, BAI03, DSS02, MEA01) to LoRaWAN’s technical components, ranging from sensors, gateways, and network servers to application servers, dashboards, and public notification modules. The analysis demonstrates that the proposed design enhances data standardization, end-to-end security, monitoring, scalability, and device governance. The integration of COBIT 2019 further enables the optimization of risk management, monitoring effectiveness, incident response, and regulatory compliance. In conclusion, the proposed architecture provides a comprehensive framework to support resilient, adaptive, and sustainable smart cities. However, this architecture has not yet been implemented in practice, thus necessitating further implementation and evaluation to ensure the system’s effectiveness and sustainability in operational environment.

Page 1 of 1 | Total Record : 2

 1 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol 17 No 2 (2025): May: Intelligent Decision Support System (IDSS) Vol 16 No 6 (2025): January : Intelligent Decision Support System (IDSS) Vol 16 No 5 (2024): November : Intelligent Decision Support System (IDSS) Vol 16 No 3 (2024): July: Intelligent Decision Support System (IDSS) Vol 16 No 2 (2024): May: Intelligent Decision Support System (IDSS) Vol 16 No 1 (2024): March: Intelligent Decision Support System (IDSS) Vol 15 No 6 (2024): January : Intelligent Decision Support System (IDSS) Vol 15 No 5 (2023): November : Intelligent Decision Support System (IDSS) Vol 15 No 4 (2023): September : Intelligent Decision Support System (IDSS) Vol 15 No 3 (2023): July: Intelligent Decision Support System (IDSS) Vol 15 No 2 (2023): May: Intelligent Decision Support System (IDSS) Vol 15 No 1 (2023): March: Intelligent Decision Support System (IDSS) Vol 14 No 2 (2022): September: Intelligent Decision Support System (IDSS) Vol 14 No 1 (2022): March: Intelligent Decision Support System (IDSS) Vol 13 No 2 (2021): September: Intelligent Decision Support System (IDSS) Vol 13 No 1 (2021): March: Intelligent Decision Support System (IDSS) Vol 12 No 2 (2020): September: Intelligent Decision Support System (IDSS) Vol 12 No 1 (2020): March: Intelligent Decision Support System (IDSS) Vol 11 No 2 (2019): Informatik Vol 11 No 1 (2019): Informatika Vol 10 No 2 (2018): Informatika More Issue