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All Journal Journal of Computer System and Informatics (JoSYC) Journal of Intelligent Computing and Health Informatics (JICHI) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika)
Widiyanto, Max Teja Ajie Cipta
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Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Electrical & Electronics Engineering Industrial & Manufacturing Engineering Medicine & Pharmacology Public Health

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Implementasi Fingerprint Dan Algoritma Riverst Shamir Adleman Untuk Kemanan Data Widiyanto, Max Teja Ajie Cipta
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.816

Abstract

The use of the internet during the pandemic has increased significantly, one of the risks is cyber attacks. Where in the field of online marketing and sales they can sabotage logins. Collect story shop is one of the providers of photography services in the city of Makassar. Currently the process of ordering customer services comes to the office or orders via social media Instagram or WhatsApp so that it has several problems and has not been able to maintain the security and confidentiality of customer data. This study aims to keep the content of the message secret by changing the message to be difficult to understand when sent and unknown to people who have no interest. In this study, fingerprints are implemented for login security. Fingerprint is a technology that uses biometric verification, namely fingerprints, but when the smartphone does not have a fingerprint feature, the data will be secured using the Riverst Shamir Adleman (RSA) algorithm. The RSA algorithm is one of the public key algorithms that has the advantage of a high level of accuracy due to the difficulty of factoring prime numbers. Every data entered into the ordering application is encrypted using the RSA algorithm in the form of numbers stored in the database and will be decrypted again on the application's user interface display. The results show that fingerprints and RSA algorithms can help the process of securing customer data from the results of accuracy testing, so that the contents of secret messages are difficult to understand when sent and are not known by people who are not interested
E-Tilang Web Based Application for Merangin District Traffic Riders Pratiwi, Regina Gita; Widiyanto, Max Teja Ajie Cipta
Journal of Intelligent Computing & Health Informatics Vol 2, No 2 (2021): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v2i2.7079

Abstract

The development of the e-ticketing application starts from planning is identifying problems, the system running, user needs to designing the uml, database and GUI. Up to the coding stage and the application named Electronic Ticketing Application (E-Tilang) Against Traffic Offenders in Merangin Regency is web-based. The application focuses on recording tickets and the results of recording tickets that can be seen on the web. The system created by the author can simplify the process of counting and processing of numbers, both for the Kasatlanas party and the public in seeing the results of the selection trial because all activities are carried out online and the data is recorded in real time in the database
Perbandingan Kinerja RNN dan CNN Dalam Klasifikasi Sentimen Ulasan Pengguna Aplikasi di Play Store Saputra, Satria Nugraha; Setiaji, Galet Guntoro; Widiyanto, Max Teja Ajie Cipta
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6408

Abstract

The public frequently shares their thoughts and opinions on various topics, such as products, public figures, or government policies, through online platforms. The process of analyzing review data is referred to as sentiment analysis. This study aims to compare the performance of two deep learning models Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) in classifying user sentiments across five review categories from the Google Play Store: design, photography, gaming, social media, and streaming. Choosing the right algorithm is essential to achieving optimal accuracy, given the variations in language and expression patterns within reviews. The dataset used in this study consists of 50,000 reviews with an imbalanced distribution of positive and negative sentiments. To address this imbalance, oversampling techniques were applied using the Synthetic Minority Oversampling Technique (SMOTE). The evaluation process measured each model's accuracy and loss levels. The results show that CNN consistently outperformed RNN across most categories. For the design category, CNN achieved the highest accuracy of 85% with a loss value of 0.41, compared to RNN, which achieved 83% accuracy and a loss of 0.53. On the other hand, the streaming category showed the lowest performance, with CNN achieving an accuracy of 69% and a loss of 0.63, while RNN achieved 67% accuracy with a loss of 0.72. These findings highlight CNN's superior effectiveness in sentiment analysis across diverse user review categories.
Co-Authors Pratiwi, Regina Gita Saputra, Satria Nugraha Setiaji, Galet Guntoro