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Technologia Journal
Published by PT Anagata Sembagi Education
ISSN : -     EISSN : 30469163     DOI : https://doi.org/10.62872/ezf7zc71
Core Subject : Science,
Computer Science & IT
This journal publishes original articles on current issues and international trends in the field of information engineering and information systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 34 Documents
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Design and Development of a Predictive AI Model for Early Detection of Mental Disorders in Adolescents Robinson Robinson; Ahmad Ari Gunawan Sepriansyah; Ahmad Zarkasih; Selvia Damayanti
Technologia Journal Vol. 2 No. 3 (2025): Technologia Journal-August
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/bx45ph86

Abstract

Adolescents are a vulnerable age group for mental disorders such as depression, anxiety, and stress. Early detection is crucial to enable timely and appropriate interventions. This study aims to design and develop a predictive artificial intelligence (AI) model capable of identifying potential mental health issues in adolescents. The research applies a quantitative experimental approach, collecting data through the locally validated DASS-21 questionnaire. The data were analyzed using Random Forest, Support Vector Machine, and Multilayer Perceptron algorithms, evaluated by accuracy, precision, recall, and F1-score metrics. The findings indicate that the Random Forest model achieved the highest accuracy at 87.4%. The system was designed with a user-friendly interface that delivers prediction results along with initial intervention recommendations. This study offers a significant contribution to preventive efforts in adolescent mental health through adaptive, accurate, and ethical AI-based technology.
Design and Implementation of an Internet of Things (IoT)-Based Smart Agriculture System for Soil Moisture Monitoring Tata Sumitra
Technologia Journal Vol. 2 No. 2 (2025): Technologia Journal - May
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/fqk32y32

Abstract

Modern agriculture requires the use of technology to increase efficiency and productivity, particularly in water resource management. This study aims to design and implement an Internet of Things (IoT)-based smart farming system capable of monitoring soil moisture in real time to support irrigation efficiency. The method used in this study is a descriptive qualitative approach with a field study, which includes the device design process, system trials on agricultural land, and interviews and observations with users (farmers). The system is built using a soil moisture sensor connected to a microcontroller and sent to a web-based monitoring platform. The results show that the system is able to work effectively by providing real-time data that can be accessed anytime by farmers through digital devices. Farmers reported that it is more assisted in determining the right and efficient watering time, and saves water use by up to 20–30 percent. Furthermore, the simple system interface is considered easy to use even by farmers who are not familiar with technology. However, challenges such as limited internet connection and the need for device protection in the field are still encountered. This research makes a significant contribution to the development of low-cost technology-based farming systems that can be applied in rural areas. Thus, the integration of IoT in agricultural practices can be an innovative solution to support precision agriculture and sustainability.
Utilizing Artificial Intelligence to Optimize Public Services: A Case Study in Regional Government Isra Muksin; Mansyur Djamal
Technologia Journal Vol. 2 No. 3 (2025): Technologia Journal-August
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/05hdgw13

Abstract

This study aims to analyze the use of Artificial Intelligence (AI) to optimize public services in local governments, while identifying challenges and opportunities for its implementation. The research method used is a qualitative case study approach, through in-depth interviews, observations, and documentation analysis. The results show that the application of AI through service chatbots, digital queuing systems, and population data analysis can improve bureaucratic efficiency, reduce public waiting times, and increase public satisfaction. However, AI implementation still faces challenges such as limited infrastructure, lack of human resource competency, resistance from some employees, and public doubts about data security. This study confirms that the success of AI adoption in local governments is determined not only by technological readiness, but also by data protection policies, change management, and increasing public digital literacy.
Analysis of the Utilization of Augmented Reality (AR) Technology in Interactive Science Learning in Schools Rustiyana Rustiyana
Technologia Journal Vol. 2 No. 3 (2025): Technologia Journal-August
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/vwq2jc74

Abstract

This study aims to analyze the use of Augmented Reality (AR) technology to support interactive science learning in schools. The research method used is a qualitative approach with a case study design, involving direct classroom observation, in-depth interviews with teachers and students, and documentation of learning activities. The results show that the use of AR can increase students' interest in learning and understanding of abstract concepts in science. AR also encourages more interactive and participatory learning. The role of teachers shifts to that of facilitators who need to master technological tools and design innovative learning strategies. However, the implementation of AR in schools still faces obstacles such as limited infrastructure and educators' digital competencies. These findings provide important insights into the potential and challenges of AR integration in education, and serve as a basis for policy development and teacher training to encourage digital transformation in science learning.
Blockchain-Based Digital Transformation in Government Administration System Rustiyana Rustiyana
Technologia Journal Vol. 2 No. 3 (2025): Technologia Journal-August
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/eyrmb910

Abstract

Digital transformation in government administration systems is key to increasing transparency, efficiency, and accountability in public services. The implementation of blockchain technology offers an innovative solution by providing secure, decentralized, and immutable transaction records. This study aims to analyze the role of blockchain in strengthening government administration processes and evaluate its impact on operational performance and public trust. The research method used is a comprehensive literature review and case analysis of blockchain implementation in several local governments and public institutions. The results show that blockchain integration can reduce bureaucracy, improve data security, and promote transparency, but requires the readiness of digital infrastructure and supporting regulations. These findings provide guidance for policymakers and IT practitioners in developing blockchain-based digital transformation strategies in the public sector.
Towards a Sustainable Smart City: The Role of Big Data and Internet of Things (IoT) in Urban Governance Rustiyana Rustiyana
Technologia Journal Vol. 2 No. 3 (2025): Technologia Journal-August
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/epkp1k05

Abstract

The rapid growth of urban populations demands smarter, more efficient, and sustainable city governance. This study aims to analyze the role of Big Data and the Internet of Things (IoT) in supporting urban governance toward a sustainable smart city, with a focus on their contributions to environmental, economic, and social sustainability. The research employed an exploratory-descriptive qualitative method through in-depth interviews, community surveys, field observations, as well as secondary data analysis from official reports and academic publications. Qualitative data were analyzed using thematic analysis, while quantitative data were processed with descriptive and inferential statistics. The findings reveal that the integration of Big Data and IoT enhances the effectiveness of city government decision-making through real-time data and predictive analytics. The application of these technologies contributes to emission reduction, energy efficiency, transportation optimization, increased citizen participation, and operational cost savings. However, implementation still faces obstacles such as limited network infrastructure, digital literacy gaps, high maintenance costs of devices, as well as data security and privacy issues. This study recommends strengthening regulations, fostering government–private sector collaboration, and implementing public education programs to expand technology adoption. These findings highlight that the success of a sustainable smart city requires synergy between technological innovation, inclusive policies, and active community engagement.
Implementation of Software Defined Networking (SDN) Technology in the Campus Network of Ichsan Sidenreng Rappang University Baharuddin Baharuddin
Technologia Journal Vol. 2 No. 4 (2025): Technologia Journal-November
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/hb72d069

Abstract

The development of information technology and the digitalization of higher education demand a more efficient, flexible, and secure network infrastructure. Software Defined Networking (SDN) offers a new paradigm in network management by separating the control plane and data plane, enabling more centralized and adaptive network management. This study aims to analyze the implementation of SDN in campus networks, specifically at Ichsan Sidenreng Rappang University, and identify its benefits, challenges, and implementation strategies. The method used is a systematic literature review of 15 scientific publications from 2020-2025 that discuss the implementation of SDN in the context of campus networks. The results show that SDN provides significant network performance improvements, with a decrease in latency from 37.7 ms to 18 ms, jitter from 40.3 ms to 2.7 ms, and an increase in throughput from 95 Mbps to 98.2 Mbps compared to conventional networks. SDN also increases flexibility through centralized management and automation, strengthens security with adaptive firewall integration, and improves service redundancy and availability. Key implementation challenges include the need for human resource training, the development of comprehensive security policies, and testing on more complex topologies. This study concludes that implementing SDN on campus networks is strategic for supporting the digitalization of higher education, with recommendations for thorough planning, ongoing human resource training, and the development of policies that holistically integrate technical and security aspects.
Design and Construction of a Web-Based Employee Salary Calculation System for the Manokwari Regency Cryptography, Communication and Informatics Service Yopi Giban; Sofyan Sofyan; Joice Pangulimang; Yuliana Sangka
Technologia Journal Vol. 2 No. 4 (2025): Technologia Journal-November
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/jycync95

Abstract

The development of information technology provides a significant opportunity for government agencies to improve the efficiency and effectiveness of administrative services, including in the management of employee salaries. The Manokwari Regency Code, Communication and Informatics Office still uses a manual system in the process of calculating and recording employee salaries, which is prone to errors, delays, and a lack of transparency. Therefore, this study aims to design and build a web-based employee salary calculation system that can help the salary data processing process to be more accurate, fast, and easily accessible. The method used in designing this system is the waterfall software development method, which includes the stages of needs analysis, system design, implementation, testing, and maintenance. This system is designed using a web-based programming language with an integrated database to store employee data, salary components, and deductions such as bank credit, social gatherings, and other contributions. The result of this study is a salary calculation information system application that can be accessed via a local network or the internet, with automatic calculation features, payslip printing, and employee salary history.
Cloud Computing Integration in the Digital Transformation of MSMEs: A Case Study on the Retail Sector Nila Natalia; Errysa Subekthi; Febri Dolis Herdiani; Foezi Arisandi SJ
Technologia Journal Vol. 2 No. 4 (2025): Technologia Journal-November
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/jkbsjt34

Abstract

This study aims to analyze the role of cloud computing integration in supporting the digital transformation process of Micro, Small, and Medium Enterprises (MSMEs) in the retail sector in Indonesia. Digital transformation has become a strategic necessity in facing the dynamics of global competition and changes in technology-based consumer behavior. This study uses a qualitative method with a case study approach on several retail MSMEs that have adopted cloud computing services. Data were obtained through in-depth interviews, field observations, and documentation, then analyzed descriptively through the stages of data reduction, data presentation, and conclusion drawing. The results show that the implementation of cloud computing can improve operational efficiency, strengthen data management, and accelerate the decision-making process based on real-time information. MSMEs that adopt this technology experience a reduction in IT infrastructure costs of up to 40% and an increase in employee productivity of up to 30%. However, challenges remain such as limited digital literacy, uneven internet infrastructure, and concerns about data security. This study confirms that cloud computing functions not only as a technological solution, but also as a catalyst for changing work culture and business management systems towards sustainable digitalization.
Analysis of Order Data Customer Segmentation in Logistics Companies Using K-Medoids and DBSCAN Algorithms Mujiono Sadikin; Nanda Azvita
Technologia Journal Vol. 2 No. 4 (2025): Technologia Journal-November
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/d6hbsb69

Abstract

The development of the logistics industry makes the use of customer data to understand market behavior and needs increasingly important. This study aims to segment customers based on logistics company order data using the K-Medoids algorithm and Density-Based Spatial Clustering of Applications with Noise (DBSCAN). This approach is used to identify customer groups with similar characteristics to support more effective marketing and service strategies. This study uses 12,000 customer order data entries from the past year, with variables including order, cost, and receiving location. The data is processed through preprocessing stages (cleaning, transformation, and normalization) before being applied to two clustering models. The analysis results show that the K-Medoids algorithm produces a Silhouette Score of 0.3559, while DBSCAN obtained a score of 0.3233. These values ​​indicate that K-Medoids has more compact and well-separated clusters than DBSCAN. Thus, the K-Medoids method is more effective in segmenting customers to support strategic decisions of logistics companies.

Page 3 of 4 | Total Record : 34

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