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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) The Scientific Journal of Information Systems INTECH (Informatika dan Teknologi)
Alfaujianto, Moh
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Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Environmental Science

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Journal : The Scientific Journal of Information Systems

 1 
UTILIZING LED USAGE ON FORTIMANAGER DEVICE AS A SOFTWARE MONITORING INDICATOR FOR FORTINET ACCESS POINTS Alfaujianto, Moh
Scientific Journal of Information System Vol. 2 No. 2 (2024): Scientific Journal of Information System
Publisher : Universitas Utpadaka Swastika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70429/sjis.v2i2.145

Abstract

In today's digital era, stable connectivity and fast troubleshooting are crucial to support corporate, academic, and research activities. One important component in network infrastructure is the access point (AP) which functions to provide a wireless connection. With the large number of Access Points (AP) provided by campuses or offices, it is required to be easy to monitor and troubleshoot all Access Point (AP) devices. Fortigate, as a solution provider, offers access point and switch monitoring features using LED Usage. This study aims to explain how access point monitoring can be implemented effectively through the FortiManager device and is important to ensure that network devices are functioning properly. FortiManager devices can monitor switches that are connected with active or inactive status, how many active access points are on each switch are monitored, all of which clients are connected to the network can be monitored. Thus, FortiManager devices are very much needed by administrators and network technical teams to facilitate monitoring and troubleshooting.
OPTIMIZATION OF INDOMARET'S BUSINESS STRATEGY IN JAKARTA THROUGH DATA MINING AND INFORMATION SYSTEM TECHNOLOGY Mohamad, Daffa Rafi Aldin; Alfaujianto, Moh; Kudmas, Mikhael; Muttaqi, Fajar; Lahagu, David
Scientific Journal of Information System Vol. 3 No. 1 (2025): Scientific Journal of Information System
Publisher : Universitas Utpadaka Swastika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70429/sjis.v3i1.170

Abstract

This study aims to analyze the number of Indomaret outlets in Jakarta by utilizing informationsystems technology and data mining techniques. Using quantitative data from 500 Indomaretlocations, the analysis was conducted to identify distribution patterns and the factors influencingoutlet growth. Clustering and linear regression methods were employed to evaluate the relationshipbetween the number of outlets and demographic and economic variables, such as population density,per capita income, and distance from the city center. The analysis results indicate a significantrelationship between population density and the number of Indomaret outlets, with a regressioncoefficient of 0.75 (p < 0.01), meaning that every increase of 1,000 people in population density isassociated with the addition of 3 Indomaret outlets. Clustering analysis also identified three strategiclocation groups with high growth potential. The main contribution of this research lies in integratingdata mining methods with spatial analysis to understand modern retail expansion in urban areas—anapproach that is still rarely explored in previous studies. These findings not only enrich the literatureon data-driven retail location analysis but also provide practical insights for industry players informulating data-based expansion strategies. This research offers valuable insights for Indomaret’smanagement in making strategic decisions regarding expansion and store placement, demonstratingthat the use of information systems and data mining is effective in supporting quantitative analysisfor business development in the retail sector.
Implementation and Analysis of Multiple Interface Policies through System Feature Visibility on Fortigate FG-60F Alfaujianto, Moh; Muttaqi, Fajar; Surahmat, Asep; Zogara, Lukas Umbu
Scientific Journal of Information System Vol. 3 No. 2 (2025): Scientific Journal of Information System
Publisher : Universitas Utpadaka Swastika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70429/sjis.v3i2.229

Abstract

Fortigate FG-60F is one of the popular firewall appliances utilized by small and medium-scalenetworks in managing security. However, some of the needed features such as multiple interfacepolicies are not displayed by default on the user interface. This study explores the functionality andeffectiveness of enabling system-feature visibility for easier management of inter-interface policies.Employing an experimental approach, the Fortigate FG-60F device was configured to activate thehidden feature, and subsequently, a set of policy rule scenarios with multiple interfaces wereestablished and tested. The results indicate that supporting system-feature visibility enhancessignificantly the administrator's ability to implement more specific traffic policies that arecommensurate with network topology requirements. Moreover, performance analysis showed nonegative impact on device performance after the implementation of multi-interface policy. Thefindings are expected to serve as a valuable reference for network administrators in optimizingFortigate FG-60F security capabilities by leveraging advanced, previously hidden features
Implementation of Regression CART Decision Tree for Best Cycling Time Recommendation Based on Weather Data Badriah, Nurul; Muttaqi, Fajar; Veri Shandy, Sony; Alfaujianto, Moh
Scientific Journal of Information System Vol. 3 No. 2 (2025): Scientific Journal of Information System
Publisher : Universitas Utpadaka Swastika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70429/sjis.v3i2.233

Abstract

Cycling requires careful time planning to ensure safety and comfort, especially when consideringweather conditions such as temperature, wind speed, and overall weather status. However, cyclistsoften struggle to determine the optimal time to ride due to the lack of accurate and easily accessiblerecommendations. This study aims to design and implement a mobile application that recommendsthe best cycling time based on real-time weather data. The system applies the Regression CARTDecision Tree method, trained using hourly temperature, wind speed, and weather conditionparameters. Unlike classification approaches, Regression CART Decision Tree produces acontinuous percentage score indicating the suitability level of each hour for cycling. Real-time datais obtained via the OpenWeatherMap API to maintain accuracy. The developed prototype displayshourly weather data along with the recommendation percentage, helping users plan their rides moreeffectively. Model evaluation shows that the Regression CART Decision Tree achieved high accuracywith a low Mean Absolute Error (MAE) and strong correlation between predicted and actualsuitability scores. The results confirm that the model performs consistently in various weatherscenarios. Overall, the system successfully delivers reliable, data-driven recommendations, assistingcyclists in selecting the safest and most comfortable cycling times.
Co-Authors Andi, Suhandana Ariawan Badriah, Nurul Dwiyulianti, Susana Kudmas, Mikhael Lahagu, David Lukas Umbu Zogara Mohamad, Daffa Rafi Aldin Muttaqi, Fajar Surahmat, Asep Veri Shandy, Sony