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Muhamad Syazali
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app.sci.def@gmail.com
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Foundation of Advanced Education (FoundAE) Jl. Pramuka Gg. Darfa LK. II, Kel. Langkapura, Kec. Langkapura, Kota Bandar Lampung.
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International Journal of Applied Mathematics, Sciences, and Technology for National Defense
Published by Foundation of Advanced Education
ISSN : 29860776     EISSN : 29859352     DOI : https://doi.org/10.58524/app.sci.def
Core Subject : Science, Education,
Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Mathematics Physics
International Journal of Applied Mathematics, Sciences, and Technology for National Defense (App.Sci.Def) [e-ISSN: 2985-9352, p_ISSN: 2986-0776] is a journal published by the Foundation of Advanced Education. International Journal of Applied Mathematics, Sciences and Technology for National Defense (App.Sci.Def) is an Applied Mathematics, Science, and Technology in National Defense is an international journal dedicated to the publication of high quality, peer-reviewed articles on all aspects of mathematics in defense, complex strategy, modeling, optimization, cybersecurity, and special issues on topics of current interest. The scope of the journal is very broad and interdisciplinary with an integrated, qualitative and quantitative approach. Review papers with insightful, integrative, applicable and up-to-date major topic progress are also welcome. Authors are invited to submit defense-related articles that have not been previously published and are not being considered elsewhere. In addition, the App.Sci.Def editorial board is strongly committed to promoting current advances and interdisciplinary research in defense mathematics, Science, and Technology.
Arjuna Subject : Umum - Umum
Articles 45 Documents
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Automatic fire fighting robot with gas detection and alert system Ashish Karpe; Pradip Targe; Patil, Aditya Shrikant; Rushikesh Gange; Sheetal Waghchaware
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 3 No. 3 (2025): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v3i3.560

Abstract

Fire incidents in residential and industrial environments present serious risks to human safety and infrastructure, requiring rapid detection and effective mitigation systems. This study proposes the design and experimental evaluation of an automatic fire-fighting robot equipped with gas detection and real-time alert capabilities. The system is built around an ESP32 microcontroller and integrates a flame sensor for fire detection, an MQ-135 sensor for hazardous gas monitoring, and a GSM module for transmitting remote alert notifications. A motor-driven water pump is employed to autonomously suppress detected fires, while a dual-mode control mechanism enables both autonomous and manual operation. Experimental evaluations were conducted under controlled indoor conditions to assess system responsiveness and reliability. The results show that the robot is capable of detecting flame sources at distances of up to 80 cm, with an average response time of approximately 3.2 s from detection to fire suppression activation. The gas detection module successfully identified abnormal gas concentrations and triggered SMS alerts with a success rate exceeding 95%. The proposed robot demonstrates a low-cost, portable, and scalable solution for early fire detection and suppression in small-scale indoor environments such as homes, offices, and warehouses. By combining autonomous navigation, gas monitoring, and real-time communication within a single robotic platform, this work contributes to the advancement of intelligent fire-safety systems and IoT-based emergency response technologies.
The least squares concept in reducing noisy signal of single-beam acoustic systems: Ocean depth measurement to support maritime defense systems Alivia, Annisa Risda; Azizah, Syasya Qonita; Alok Shukla
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 3 No. 3 (2025): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v3i3.643

Abstract

Indonesia's vast ocean territory presents both opportunities and security challenges, requiring robust maritime defense. Effective sea defense includes surface patrols with naval vessels and aircraft, alongside underwater surveillance using submarines and detection systems. Advanced acoustic technology, such as Single Beam Echo Sounder (SBES) sonar, is essential for underwater depth measurement. However, environmental noise often disrupts sonar recordings, necessitating noise reduction techniques. This study applies the Least Mean Square (LMS) filter, an adaptive algorithm that adjusts filter coefficients based on error minimization. Its real-time adaptability enhances noise suppression, improving sonar signal quality. The results indicate that the LMS filter achieves an optimal Signal-to-Noise Ratio (SNR) of 6.7248 dB, surpassing other methods. Furthermore, it accurately identifies signal delays, crucial for precise depth measurement. Enhancing underwater acoustic technology through LMS filtering supports improved hydrographic surveys, benefiting scientific research, commercial navigation, and military operations in securing Indonesia’s maritime domain.
Next-Gen SOC: Leveraging generative AI for scalable threat detection and AI-powered alert classification Kotilingala, Sudheer
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 3 No. 3 (2025): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v3i3.670

Abstract

The volume of alerts produced by the SIEM system causes SOC analysts to experience alert fatigue, with actual security incidents obscured by more than fifty percent of notifications being considered false positives. This inefficiency causes delays in response times and puts organisations at risk due to insufficient resource allocation. We have, therefore, introduced a new framework in this paper, which incorporates LLMs into SOC initiatives. Overall, with the help of contextual understanding elements of LLMs, our framework concludes with 95,5% accuracy to classify the alerts as false positives or actual threats. The study’s results, therefore, validate less alert fatigue, improved systems functioning, and shorter time to critical security events using the proposed methodology. As a result, this paper outlines the proposed system’s description, development, and evaluation to determine its potential for future SOC operations.
Towards a standard framework for cybersecurity readiness for Nigerian universities Olugbile, Olusegun Hamed; J. A. Ojeniyi; Tochukwu Kene Anyachebelu
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 3 No. 3 (2025): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v3i3.780

Abstract

niversities rely substantially on digital infrastructure and host vast amounts of data that are of interest to malicious actors.  Thus, they are vulnerable to cyber-attacks, making their protection a significant issue. While technology continues to improve, educational system infrastructures and system security lag behind. However, to ensure the continuous availability of university digital assets, the infrastructure must be prepared to withstand cyber-attacks. The results of research indicate that several models exist for evaluating the readiness of universities for cybersecurity. These models have been established for developed nations with more sophisticated and mature cyber networks, and may not be directly applicable to developing economies like Nigeria. Therefore, the Design Science Research strategy was adapted to develop a framework for assessing cybersecurity readiness in Nigerian universities. Taking into account pre-event, event management, and post-event factors, the concept of Cybersecurity Readiness Tiers (CRT) was developed to compare the cybersecurity readiness of universities. The Cybersecurity Readiness Framework was evaluated using data collected from candidate universities sampled for this study; Principal Component Analysis was carried out on the dataset to reduce the dimension. The Cybersecurity Readiness Index (CRI) scores, along with their respective distributions, indicate that 14 (65%) of the twenty universities fall in T1, while 6 (35%) fall in T2. The grouping was based on their overall cybersecurity readiness, as computed using the mathematical equations of the framework. Thus, it implies universities in T2 have a high level of readiness to resist cybersecurity incidents, while universities in T1 are at a very low level of readiness due to the weak and inconsistent cybersecurity controls implemented. This study suggests that these universities have gaps in event management and post-event capabilities that require attention. Therefore, a holistic web-based Cybersecurity Assessment tool that will incorporate all security and privacy regulations and best practices can be considered for future studies.
Evaluating multiple time series models for consumer price index forecasting to support national defense decision-making Al Habsy, Muhammad Yusuf; Nur Rachmawati, Ro'fah; Jumadil Saputra
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 3 No. 3 (2025): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v3i3.865

Abstract

Price stability, as reflected in the Consumer Price Index (CPI), plays a crucial role in supporting economic resilience and national defense readiness. This study evaluates multiple time series forecasting models, including Error-Trend-Seasonal (ETS), Holt, Holt–Winter, SARIMA, SARIMAX with exogenous variables, and hybrid approaches combining Holt/Holt–Winter with SARIMA, to identify the most accurate method for predicting Indonesia’s CPI. Monthly data from 2017–2022 were analyzed using a training–testing split, and forecasting accuracy was assessed based on RMSE. The results show that the Holt–Winter model outperforms all other approaches, achieving the lowest RMSE value of 1.9159. Residual diagnostics confirm that the Holt–Winter model effectively captures trend and seasonal patterns, with errors behaving close to white noise. These findings highlight the superiority of Holt–Winter in providing reliable CPI forecasts, offering significant implications for economic policy formulation and strategic planning in the context of national resilience.

Page 5 of 5 | Total Record : 45

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