Publication Search

World civilization with very rapid changes in various countries is characterized by the unlimited use of information systems based on computing and big data. Information technology utilizes computers and computer software to convert, store, process, protect, transmit and obtain information securely. Designing an administrative service information system to assist students and final assignment coordinators in the registration process, filing requirements and submitting titles for final assignments and obtaining supervisor assignment letters. Therefore, this problem can be solved by building an information system design for final assignment administration services that will be implemented in the Industrial Engineering Study Program, namely SIMENTARI (Industrial Engineering Final Assignment Management Information System). In this research, the SIMENTARI design method used was waterfall. The waterfall method suggests systematic and sequential software development starting from the highest system level and continuing to the analysis, design, coding, testing and maintenance stages. The existence of a SIMENTARI Information System can make it easier for the Final Assignment Coordinator in the Industrial Engineering Study Program to serve students who will submit their Final Assignments more easily and systematically and the data entered by the user can be stored neatly in the system. In this research, the tools used to create a SIMENTARI information system were Xampp and Php MySQL software.

Phishing is a crime that uses social engineering techniques, both in deceptive statements and technically, to steal consumers' personal identification data and financial account credentials. With the new Phishing machine learning approach, websites can be recognized in real-time. K-Nearest Neighbor(KNN) and Naïve Bayes (NB) are popular machine learning approaches. KNN and NB have their own strengths and weaknesses. By combining the two, deficiencies can be covered. So this study proposes to combine K-Nearest Neighbor with Naïve Bayes to classify phishing websites. Based on the results of the accuracy test of the combination of KNN with k=8 and Naïve Bayes, a maximum accuracy of 93.44% is produced. This result is 6.25% superior compared to using only one classifier.

Konter Fakhri cellular saat ini belum memiliki media khusus untuk mempromosikan produk-produknya. Saat ini konsumen masih langsung datang ke toko apabila ingin mendapatkan informasi produk aksesoris dan HP yang diinginkan. Selain itu pengolahan data juga masih dilakukan secara manual dengan menggunakan media buku. Penelitian ini menggunakan metode waterfall. Tahapan-tahapan dalam metode waterfall sebagai berikut system engineering, analysis, design, code, testing, dan maintenance. Hasil penelitian ini adalah sistem informasi penjualan HP dan Aksesoris yang ada di Konter Fakhri cellular berbasis web. Kesimpulan dalam penelitian ini adalah sistem informasi penjualan HP dan aksesoris ini dapat memudahkan pembeli dalam mencari HP serta aksesoris HP secara online tanpa harus datang ke toko. Cara pengaksesannya pun sangat mudah yaitu website dapat diakses dengan menggunakan media HP, komputer, dan laptop.