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All Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Hamzah Setiawan
Universitas Muhammadiyah Sidoarjo, Sidoarjo, Indonesia
Computer Science & IT Control & Systems Engineering

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Penggunaan Datamining Untuk Memprediksi Masa Studi Mahasiswa di Universitas Muhammadiyah Sidoarjo Dengan Algoritma Naive Bayes Muhammad Mursidil Arif; Hamzah Setiawan; Arif Senja Fitrani
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 3 (2023): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i3.210

Abstract

In the higher education, improving student performance and improving the quality of education is very important. The education system requires innovative ways to improve the quality of education, achieve the best results and minimize student failure rates. One of the innovative ways is to apply data mining to predict students' study period. The results of these predictions will help students or academic adviser to provide early warning or give more precise directions to each student, so that they can do the best things to increase the chances of graduating on time. In this study, 9 academic and non-academic variables were used, consisting of semester grade point index, Semesters 1, 2, 3 and 4, GPA, school origin (public/private), finance (constrained by financial problems or not), scholarship (whether get a scholarship or not), Student Affairs (active or not in the student program). The use of academic and non-academic data variables in this study aims to broaden the predictions of student graduation which are not only assessed from an academic point of view, but also look at non-academic factors. The data used is student’s data for the 2017-2018 Informatics study program at the Muhammadiyah University of Sidoarjo. This data is obtained from the Directorate of Information Systems Technology (DSTI) Muhammadiyah University of Sidoarjo as many as 200 data. Modelling using the naïve Bayes algorithm using Anaconda Navigator software with IDLE Jupyter Notebook and the Python programming language, after evaluation using the confusion matrix and accuracy score, the results obtained were 68% accuracy, precision value 0.67, recall 0.77 and f1-score 0.72. while the accuracy score evaluation value gets 67.35%
Implementasi Jaringan RT/RW Net menggunakan metode IP Binddings dan HTB untuk Usaha Menengah Kecil Mikro Wildan Arif Hidayatulloh; Hamzah Setiawan; S Sumarno
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 2 (2023): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i2.167

Abstract

The Internet is one of the results of technological advancement. Almost all activities can be done online using the Internet. However, the distribution of the Internet has not reached all sectors, especially in remote villages. This is due to the expensive cost of Internet installation, making it inaccessible to middle to lower-class communities. One solution to this problem is the RT RW Net business, which not only benefits the owner but also provides affordable Internet access to lower-middle-class communities. This research discusses the creation of RT RW Net using IP Bindings and HTB methods. IP Bindings is a technique of the hotspot server where the MAC Address of the user's Access Point is registered in the bypass type of IP Bindings so that the user's AP can connect to the Internet without authentication. To manage bandwidth, this research uses Hierarchical Token Bucket (HTB), which is a method of bandwidth management in Mikrotik that applies a hierarchical or tiered grouping concept. By combining these two methods, this research produces a good and appropriate RT RW Net Internet network. This provides access to information, business opportunities, healthcare services, education, and financial transactions online for rural communities. However, factors such as network infrastructure, trained human resources, and transparent and fair policies for all users need to be considered to run the RT RW Net business effectively and provide optimal benefits to the community.
Co-Authors Arif Senja Fitrani Muhammad Mursidil Arif S Sumarno Wildan Arif Hidayatulloh