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All Journal IJAIT (International Journal of Applied Information Technology)
Randi Rizal
Dept. of Informatic, Siliwangi University, Indonesia; Faculty of Information and Communication Technology, UTeM, Malaysia
Computer Science & IT

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Implementation of A Motorcycle Vehicle Security System with Arduino-Based Fingerprint, Global Positioning System and Short Message Service Gateway Randi Rizal; Aso Sudiarjo; Nur Widiyasono; Dede Rizal Nusamsi; Muhammad Faiz
IJAIT (International Journal of Applied Information Technology) Vol 08 No 02 (November 2024)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v8i2.6354

Abstract

The increase in demand for motorized vehicles, especially motorcycles, from 2016 - 2021 has recorded an increase of 5.03% per year. Along with the increasing number of people using motorbikes as their main means of transportation, there is a growth in motorcycle theft. One cause of the increase in these cases is that the motorcycle security system still relies on the lock system. So, it is necessary to improve security with unique modern keys that can only be accessed by specific people, one of which is a security system using biometric technology. This research has combined motorcycle security systems using fingerprint, GSM and GPS modules based on Arduino Uno. The results of testing the fingerprint module scanning time obtained an average scanning time of 1.04 seconds. Testing the SIM800L GSM module obtained an average processing time of receiving SMS and sending back a response to a registered number, which is 9.32 seconds and the results of testing the accuracy of data retrieval between the U-blox Neo-6m GPS module and GPS on the Oppo A3S brand smartphone, with the calculation of the average difference distance of 0.75 Meters. Motorcycle vehicle security was successfully implemented by utilizing the fingerprint module, GPS module and GSM module as an intermediary in the form of SMS between the user and the microcontroller so that it functions as layered security.
Implementation of the Apriori Algorithm on Outdoor Equipment Rental Transaction Data Based on Clustering Using the K-Means Algorithm Randi Rizal; Ruuhwan Ruuhwan; Muhammad Al Husaini; Dede Rizal Nursamsi; Meto Rizki M
IJAIT (International Journal of Applied Information Technology) Vol 08 No 02 (November 2024)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v8i2.6367

Abstract

Outdoor equipment rental services play a critical role in meeting climbers’ needs prior to expeditions. Sustaining business continuity in this sector requires effective marketing strategies, particularly given the increasing market competition. This study employs data mining techniques to analyze rental transaction data and identify patterns that support strategic decision-making. Specifically, clustering is performed using the K-Means algorithm to group transactions with similar attributes, followed by association rule mining using the Apriori algorithm within each cluster. A dataset comprising 1,276 valid transactions was processed, resulting in three clusters containing 324, 264, and 688 records, respectively, with an accuracy of 0.998. Apriori analysis generated 13 association rules in Cluster 0 and 2 rules in Cluster 1, while no rules met the minimum support and confidence thresholds in Cluster 2 or the overall dataset. These findings demonstrate that clustering prior to association rule mining can uncover meaningful patterns that are not evident in aggregated data. Such insights can inform targeted marketing strategies, including recommendations for item combinations frequently rented together. Future research may integrate alternative algorithms such as ECLAT or FP-Growth and explore framework-based systems to enhance scalability and precision in data-driven decision-making.
Co-Authors Aso Sudiarjo Dede Rizal Nursamsi Dede Rizal Nusamsi Meto Rizki M Muhammad Al Husaini Muhammad Faiz Nur Widiyasono Ruuhwan Ruuhwan