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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Informatika dan Rekayasa Komputer
Desi Kisbianty
Informatics Engineering, Faculty Of Computer Science, Universitas Dinamika Bangsa, Jambi, Indonesia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Implementasi Algoritma Haar Cascade Classifier Dalam Mendeteksi Robot Sepak Bola Beroda Joshua Sitompul; M Irwan Bustami; Desi Kisbianty
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.3929

Abstract

In soccer robot contests, generally soccer robots can recognize their own team robots through color detection using the HSV model. Robots that use color detection to identify their own team robot can detect objects that have the same color value, so objects that have the same color will be considered as their own team robot. However, if you only rely on this method, it is still lacking when viewed in terms of object tracking. Haar like feature or known as Haar Cascade Classifier is a rectangular (square) feature method, which gives a specific indication of an image. This method is able to detect quickly and in real time. Therefore, the researchers tried to unite these two detections to be able to produce a better detection system than before. It is hoped that hoped that in this study, researchers can provide input for the Robotics team of Dinamika Bangsa University in improving the accuracy of robot detection against robots in the same team. From the results of the study it was found that the detection of objects with a distance from the camera as far as 100 cm to 150 cm was successfully carried out, but with a distance of more than 150 cm the object was not detected.
Penerapan Data Mining Algoritma Naive Bayes Clasifier Untuk Mengetahui Minat Beli Pelanggan Terhadap INDIHOME Adi Wahyudi; Silvia Ovelia Tampubolon; Nurul afrilia Putri; Aji Ghassa; Errisya Rasywir; Desi Kisbianty
Jurnal Informatika Dan Rekayasa Komputer(JAKAKOM) Vol 2 No 2 (2022): JAKAKOM Vol 2 No 2 September 2022
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1240.111 KB) | DOI: 10.33998/jakakom.2022.2.2.111

Abstract

Abstrak− Persaingan yang terjadi dalam dunia bisnis memaksa para pelakunya untuk selalu memikirkan strategi-strategi dan terobosan yang dapat menjamin kelangsungan dari bisnis yang dijalankannya. Hal ini akan memunculkan persaingan antar sesama provider kartu terhadap kartu internet. Para provider kartu internet berlomba-lomba menarik minat pelanggan dengan berbagai macam strategi pemasaran agar tidak kalah saing dan tetap eksis. Dan perusahaan ingin selalu meluncurkan kartu internet terbaru tanpa memikirkan kartu internet tersebut akan laku atau tidak dipasaran. Maka, metode klasifikasi mampu menemukan model yang membedakan konsep atau kelas data, dengan tujuan untuk dapat memperkirakan kelas dari suatu objek yang labelnya tidak diketahui. Oleh sebab itu, algoritma naive bayes dapat memprediksi peluang di masa depan berdasarkan pengalaman dimasa sebelumnya. Hasil dari penelitian ini agar dapat memprediksi atau memperkirakan laku atau tidak kartu internet yang baru, sehingga pemilik usaha dapat mengambil keputusan dan meningkatkan strategi pemasaran. Kata Kunci: Data Mining; Kartu Internet; Klasifikasi; Algoritma Naïve Bayes Abstract− Competition is happening in the business world to force the perpetrators to always think of the strategy - and a breakthrough strategy that can guarantee the continuity of the business being operated. This leads to competition among card providers on the internet card. The provider of internet card race-the race to attract customers with a variety of marketing strategies in order not to lose competitiveness and still exist. And the company wants to always launch the latest internet card without thinking of internet cards will be sold in the market or not. Thus, the classification method is able to find a model that distinguishes the concept or class of data, in order to be able to predict the class of an unknown object label. Therefore, Naive Bayes algorithm can predict future opportunities based on the experience of earlier. Results from this study in order to predict or estimate the behavior or the new Internet card, so that the bussines owner can make decisions and improve marketing strategy. Keywords: Data Mining; Internet Cards; Classification; Naïve Bayes Algorithm
Co-Authors Adi Wahyudi Aji Ghassa Errisya Rasywir Joshua Sitompul M Irwan Bustami Nurul afrilia Putri Silvia Ovelia Tampubolon