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All Journal INTEK: Informatika dan Teknologi Informasi Indonesian Journal of Networking and Security - IJNS
Asih Winantu - STMIK EL RAHMA Yogyakarta
STMIK El Rahma Yogyakarta
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Other

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Identifikasi Ikan Mentah Berformalin Menggunakan Nilai HSV Dan Jaringan Syaraf Tiruan Learning Vector Quantization (LVQ) Dari Citra Ikan Mentah Achmad Lukman Lukman; Asih Winantu - STMIK EL RAHMA Yogyakarta
Indonesian Journal of Networking and Security (IJNS) Vol 5, No 1 (2016): IJNS Januari 2016
Publisher : APMMI - Asosiasi Profesi Multimedia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (55.425 KB) | DOI: 10.55181/ijns.v5i1.1399

Abstract

Abstract - STMIK Banjarbaru have a strategic plan , The to do is create a strategic plan in STMIK Banjarbaru Information Systems , focusing attention on the part of human resources using the value chain approach (value chain ). The study was conducted with the objective to build your strategic planning of human resources information system STMIK Banjarbaru to create a competitive advantage in realizing the vision , mission and goals of the organization. Given this research will facilitate the management of Human Resources ( HR) in STMIK Banjarbaru to increase its competitive advantage by using strategic planning of human resources information system .Keywords : strategic planning of information systems , human resources , value chain , five force porter , Mc Farlan . Abstract - STMIK Banjarbaru memiliki rencana strategis, Adapun yang dilakukan adalah membuat rancangan strategis Sistem Informasi di STMIK Banjarbaru, dengan fokus perhatian pada bagian Sumber daya manusia menggunakan pendekatan rantai nilai (value chain)Penelitian dilakukan dengan tujuan Membuat perencanaan strategis sistem informasi sumber daya manusia STMIK Banjarbaru untuk menciptakan keunggulan bersaing dalam mewujudkan visi, misi dan tujuan organisasi,.Dengan adanya penelitian ini akan memudahkan dalam pengelolaan Sumber Daya Manusia (SDM) pada STMIK Banjarbaru untuk meningkatkan keunggulan kompetitifnya dengan menggunakan perencanaan strategis system informasi Sumber Daya Manusia.Kata kunci : Perencanan strategis sistem informasi, Sumber Daya Manusia, Analisa value chain, Five Force Porter
Perbandingan Metode Klasifikasi Naive Bayes Dan K-Nearest Neighbor Dalam Memprediksi Prestasi Siswa Asih Winantu; Chusnul Khatimah
INTEK : Jurnal Informatika dan Teknologi Informasi Vol. 6 No. 1 (2023)
Publisher : Universitas Muhammadiyah Purworejo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37729/intek.v6i1.3006

Abstract

Student achievement is one of the most important aspects in the field of education, so it is necessary to take action to improve the quality of education in dealing with students who have less achievement so that teachers can identify students who need more guidance. This study aims to predict student achievement by processing students' report cards using the Naïve Bayes classification and k-Nearest Neighbor data mining method approach, and utilizing orange software as a testing tool. The data used is data on grade 1 student scores for the 2019 to 2022 academic year totaling 143 data. The evaluation results using test and score yield CA (Classification Accuracy) values ​​for the Naïve Bayes algorithm 0.909 and the k-NN algorithm 0.848, the F1 value for the Naïve Bayes algorithm 0.858 and the k-NN algorithm 0.820, the Precision value for the Naïve Bayes algorithm 0.862 and the k-NN algorithm 0.821 the Recall value of the Naïve Bayes algorithm is 0.857 and the k-NN algorithm is 0.820. The Naïve Bayes AUC value is 0.909 and the k-NN value is 0.848. Therefore, for the case study, the ROC analysis model that has the best accuracy value is Naïve Bayes because the curve is closest to the coordinate point of 0.1. Based on the analysis of each of these values, the amount of False Negative and False Positive data is close to (Symmetric) and the accuracy value is very high, so accuracy can be used as a reference for algorithm performance. With this research, it is hoped that it will make it easier to determine student potential and can help improve the learning system for students who have difficulty in achieving achievement.
Co-Authors Achmad Lukman Lukman Achmad Lukman Lukman, Achmad Lukman Chusnul Khatimah