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All Journal Jurnal Teknik ITS Jurnal Nasional Teknik Elektro dan Teknologi Informasi
R.V. Hari Ginardi
Institut Teknologi Sepuluh Nopember
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Fraud Avoidance Using QR Codes on Transaction Process on Finding – Tutor Application in Android System I Nyoman Pande Wahyu Dharmawan; R.V. Hari Ginardi
Jurnal Teknik ITS Vol 6, No 2 (2017)
Publisher : Direktorat Riset dan Pengabdian Masyarakat (DRPM), ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (662.641 KB) | DOI: 10.12962/j23373539.v6i2.23144

Abstract

Finding – Tutor application is an app with Android basis. This application helps people in finding some tutors that are needed for students. In addition, Finding – Tutor also helps tutor service providers in marketing their services. This application helps the student to create a transaction order according with the students’ criteria. The tutor provider can also choose transaction according to the ability he / she can teach. However, this application should be able to handle a fraud that occurs in a condition where the tutor provider services does not come to the location of the transaction. This condition happens because if there is no feature detecting that the student and tutor service provider has met, the tutor service provider can make a false data. This kind of false data is a tutor service provider give a data to system that the tutor service provider has been in the transaction location where the real condition is different. For that occasion, Finding Tutor application require a feature to handle this fraud. To do so, Finding – Tutor uses QR Codes scanner to handle this fraud.
Pengelompokan Data Menggunakan Pattern Reduction Enhanced Ant Colony Optimization dan Kernel Clustering Dwi Taufik Hidayat; Chastine Fatichah; R.V. Hari Ginardi
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 5 No 3: Agustus 2016
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (758.98 KB)

Abstract

One method of optimization that can be used for clustering is Ant Colony Optimization (ACO). This method is good in data clustering, but has disadvantage in terms of time and quality or solution convergence. In this study, ACO-based Pattern Reduction Enhanced Ant Colony Optimization (PREACO) method with a gaussian kernel function is proposed. First, it sets up initial solution. Second, the magnitude of pheromone is calculated to find the centroid randomly. With the initialized solution, the weight of the solution is calculated and the center of cluster is revised. The solution will be evaluated through a gaussian kernel functions. Function 'pattern enhanced reduction' is useful to ensure maximum value of pheromone update. Those steps will be conducted repeatedly until the best solution is chosen. Tests are performed on multiple datasets, with three test scenarios. The first test is carried out to get the right combination of parameters. Second, the error rate measurement and similarity data using Sum of Squared Errors is done. Third, level of accuracy of the methods ACO, ACO with the kernel, PREACO, and PREACO with the kernel is compared. The test results show that the proposed method has a higher accuracy rate of 99.8% for synthetic data, 93.8% for wine data than other methods. But it has a lower accuracy by 88.7% compared to the ACO.
Co-Authors Chastine Fatichah Dwi Taufik Hidayat I Nyoman Pande Wahyu Dharmawan