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Journal : BIMASAKTI

INVESTIGASI PERBANDINGAN COSINE SIMILARITY DAN EUCLIDEAN DISTANCE DALAM DETEKSI PHISHING ATTACK MENGGUNAKAN METODE K-NEAREST NEIGHBOR Da Frosa, Bibiana; Akhmad Zaini; Muhammad Priyono Tri Sulistyanto
Jurnal Fakultas Teknologi Informasi Vol 6 No 2 (2024): BIMASAKTI
Publisher : Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v6i2.10107

Abstract

The development of information technology affects various aspects of life. However, this positive impact also opens up opportunities for growing cybercrime, known as cybercrime (Iman et al., 2020). These crimes, such as carding, hacking, and phishing, threaten security in the digital realm (Gulo et al., 2021). Phishing, as a form of cybercrime, involves sending fake links to steal victim information (Wibowo & Fatimah, 2017). In the midst of the development of information technology systems, data mining has emerged as a solution, enabling all valuable information from big data. K-Nearest Neighbors (KNN) is a machine learning algorithm used for classification and regression (Dewi Obert & Gusmana, 2018). In K-Nearest Neighbor, distance methods such as euclidean distance, Manhattan distance, cosine similarity, and jaccard similarity are commonly used. The focus of this research is on euclidean distance and cosine similarity which are considered efficient and commonly used. The evaluation results show that the second method, cosine similarity and Euclidean distance, has a similar level of accuracy and speed in detecting phishing attacks. However, Euclidean distance stands out in phishing detection with an accuracy rate of 87.70% and a speed of 0.0172. Meanwhile, cosine similarity reaches an accuracy rate of 87.57% with a speed of 0.0360. Looping analysis consistently confirms the Euclidean distance speed advantage. In phishing attack detection, Euclidean distance is proven to be more effective in accuracy and speed.
MONITORING KUALITAS PH DAN KEKERUHAN AIR LAUT DALAM MENJAGA EKOSISTEM TERUMBU KARANG MENGGUNAKAN METODE FUZZY LOGIC Asrori, Hazynatul; EP, Amak Yunus; Muhammad Priyono Tri Sulistyanto
Jurnal Fakultas Teknologi Informasi Vol 7 No 1 (2024): BIMASAKTI
Publisher : Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v7i1.10705

Abstract

 The condition of the sea and coastal areas is getting worse every day. Poor sea conditions will damage the marine ecosystem because the quality of sea water is a very important factor for the survival of coral reefs and other marine biota. To reduce the impacts that occur due to poor water quality, a monitoring and control system is needed so that water quality can be controlled properly. Therefore, the author makes a coral reef ecosystem monitoring system using the Fuzzy Logic method, the system will monitor the pH and turbidity of water, then use fuzzy as a decision support method to determine the quality of sea water.
ANALISIS PERSEDIAAN INVENTORY DENGAN C4.5 DAN PREDIKSI HARGA INVENTORY BERBASIS TIME-SERIES DI KAFE XXX Deslin Anastasia Pekiri; Sulistyanto, Muhammad Priyono Tri; Amak Yunus E.P.
Jurnal Fakultas Teknologi Informasi Vol 5 No 2 (2023): BIMASAKTI
Publisher : Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v5i2.8940

Abstract

Dunia kuliner di Indonesia menyajikan beragam jenis masakan ataupun makanan negara Indonesia yang terdiri dari beragam suku bangsa dan budaya juga memiliki beragam citra masakan yang khas yang membuat banyak masyarakat ingin mengetahui dan mencobanya. Persaingan di dunia kuliner khususnya restoran sangatlah ketat terlebih pada zaman industri 4.0 sehingga sangat ditekankan kecepatan dan pelayanan yang baik untuk pelanggan. Bahan baku merupakan prioritas utama dan sangat vital bagi suatu industri kuliner dalam penyajian makanan, yang tidak jarang stok bahan baku yang diminta merupakan stok yang peminatnya kurang dan terjadi penumpukan stok di inventori dan bahan baku sudah mulai membusuk, hal ini terjadi juga di Kafe XXX. Untuk melakukan analisis ketersediaan bahan baku dengan algoritma C4.5 dapat memberikan gambaran setiap item bahan baku. Prediksi tentang harga bahan baku dengann metode moving-average dapat memberikan gambaran kepada pihak manajemen untuk rekomendasi pembelian harga baku tersebut