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All Journal Jurnal INSYPRO (Information System and Processing) Journal of Big Data Analytic and Artificial Intelligence
Endyk Noviyantono
STMIK PPKIA TarakanitaRahmawati Jl. YosSudarso 8 Tarakan, Indonesia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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STUDI PERBANDINGAN AVALANCHE EFFECT PADA ALGORITMA KRIPTOGRAFI TRANSPOSISI UNTUK MENINGKATKAN KEAMANAN DATA Noviyantono, Endyk; Fadlan, Muhammad; Muhammad; Suprianto
Jurnal INSYPRO (Information System and Processing) Vol 9 No 1 (2024)
Publisher : Prodi Sistem Informasi UIN Alauddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/insypro.v9i1.46509

Abstract

Various cryptographic techniques have been used as a solution to maintain data security, one of which is the transposition technique which is included in the classic type of cryptography. This research aims to conduct a comparative study of two classic transposition techniques, namely Route Transposition and Rail Fence Transposition. Apart from that, this research aims to find out whether various classical transposition techniques are still relevant in the process of securing data in the current cyber era. In this research, comparative analysis was carried out based on the Avalanche Effect (AE) value. The research results show that the route transposition technique has the highest value compared to the rail fence transposition technique. However, based on the minimum standard AE value, it shows that the two techniques are still in a position below the minimum AE value, namely below 50%.
Rekayasa Aplikasi Rekomendasi Pencarian Lokasi Dan Analisis Sentimen Menggunakan Penambangan Teks Febriyanti, Eka; Noviyantono, Endyk; Praseptian M, Dikky
Journal of Big Data Analytic and Artificial Intelligence Vol 7 No 2 (2024): JBIDAI Desember 2024
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v7i2.66

Abstract

 This research aims to provide information and assessments about tourist attractions and culinary attractions that are popular on social media (Instagram and Twitter). The research process uses a text mining approach, starting with text processing (case folding, tokenizing, stopword removal, and stemming) to filter comments. Furthermore, weighting is carried out using the TF-IDF method to determine the relevance of words. The process of classifying comments by location name is carried out using the Naïve Bayes algorithm, followed by sentiment analysis to assess positive, negative, or neutral comments. The research application was built using PHP with a MySQL database and utilized a dataset of 73 comments (17 for tourism and 56 for culinary) collected from social media. The results of the study show that the system is able to produce recommendations for tourist and culinary attractions effectively based on data analysis
Co-Authors Dikky Praseptian M Fadlan, Muhammad MARIA BINTANG Muhammad Nurwijayanti