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All Journal JOSINFO : Jurnal Online Sistem Informasi JOURNAL OF APPLIED INFORMATICS AND COMPUTING
IGKG Puritan Wijaya, IGKG Puritan
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Computer Science & IT

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Sistem Pendukung Keputusan Pemilihan Ekstrakurikuler SMPK Soverdi Tuban Menggunakan MetodeMultifactor Evalaution Process (MFEP) Parwata, IB. Krisnanda; Wijaya, IGKG Puritan; Hadi, Rosalia
JOSINFO : Jurnal Online Sistem Informasi Vol 1, No 1 (2015)
Publisher : JOSINFO : Jurnal Online Sistem Informasi

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Abstract

Dalam membangun suatu aplikasi sistem pendukung keputusan untuk pemilihan ekstrakurikuler pada sebuah sekolah khususnya SMPK Soverdi Tuban.  Sebelum suatu keputusan diambil maka akan dilakukan suatu proses, sehingga didapat suatu keputusan yang cepat, tepat dan akurat. Metode yang digunakan dalam pengambilan keputusan menentukan jurusan ini adalah MFEP. Adapun sistem ini dibuat dengan menggunakan PHP dan Database untuk pengolahan data menggunakan MySQL. Pada skripsi ini sistem pendukung keputusan berbasis web menggunakan metode MFEP mampu menganalisa kriteria dan alternative yang dibandingkan, dapat memberikan rekomendasi ekstrakurikuler pada siswa yang tepat sesuai dengan kriteria dan alternatif yang dibandingkan dan dapat meberikan nilai dari hasil perhitungan metode. Kata kunci:Sistem Pendukung Keputusan, Pemilihan Ekstrakurikuler, MFEP. 
Real-Time Visitor Counting with Dynamic Facial Recognition using Python and Machine Learning Gautama, I Made Bhaskara; Arsa, I Gusti Ngurah Wikranta; Saputra, I Made Arya Budhi; Wijaya, IGKG Puritan; Sutha, Dewa Gede Yudisena Nanda
Journal of Applied Informatics and Computing Vol. 7 No. 2 (2023): December 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i2.6452

Abstract

Visitor data or the number of visitors at a particular location is crucial information to be obtained. This data can serve various purposes, particularly in enhancing customer satisfaction. For instance, predicting the number of visitors at tourist destinations enables tourism management to be better prepared for welcoming and providing optimal services to arriving visitors. Visitor count data can also be employed to automatically restrict visitors during the COVID-19 pandemic, ensuring a safe and comfortable environment with limited attendees. To acquire visitor data, a system capable of accurate visitor detection is required. This research utilizes computer vision to detect visitor faces. The developed system, programmed in Python, functions by detecting visitor faces and conducting a count based on the detected faces. To prevent the same visitor from being detected multiple times, a facial recognition method with dynamic facial data collection is implemented in this study. The constructed system successfully counted 27 out of 28 visitors over a two-day period. However, the system has limitations, particularly in terms of the restricted detection area. Therefore, a physical mechanism mandating visitors to undergo facial scanning and registration needs to be established, ensuring recorded data corresponds to the actual visitor count.
Co-Authors Arya Budhi Saputra, I Made Gautama, I Made Bhaskara I Gusti Ngurah Wikranta Arsa IB. Krisnanda Parwata, IB. Krisnanda Rosalia Hadi Sutha, Dewa Gede Yudisena Nanda