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Narabel, Julio
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Computer Science & IT

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Aplikasi Mobile untuk Sistem Antrian Praktek Dokter Dilengkapi dengan Analisis Perhitungan Estimasi Waktu Menggunakan Markov Chain dan Algoritma PageRank: Analisis Perhitungan Estimasi Waktu Menggunakan Markov Chain dan Algoritma PageRank Chandra, Cato; Sanjaya, David; Narabel, Julio; Vilano, Nucky; Budi, Setia
Jurnal Teknik Informatika dan Sistem Informasi Vol 5 No 3 (2019): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v5i3.1990

Abstract

Along with the increasingly rapid development of technology, especially in the field of computers, ways to overcome the problem of patient queues have been developed. One of them is the use of a mobile application to get a time estimate until a patient gets a turn to consult with a doctor. Many industries still use manual methods to overcome this queue problem. Based on this fact, this final project with title "Mobile Applications for Doctor Examination Queue System Equipped with Analysis of Time Estimation Calculation Using the Markov Chain and PageRank Algorithm" has aims to get time estimates for the patients so that time can be more efficient.
Deteksi Dini Status Keanggotaan Industri Kebugaran Menggunakan Pendekatan Supervised Learning Narabel, Julio; Budi, Setia
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i2.2675

Abstract

In the fitness industry, the number of members is a major factor for the sustainability of its business. The ability of managers and trainers to detect members who represent traits to quit membership is critical. Four supervised learning classification methods like Support Vector Machine, Random Forest, K-Nearest Neighbor, and Artificial Neural Network were used to generate early detection using two variants of datasets that have different amounts of data. Classification results are separated into three different zones, which are Green Zone, Yellow Zone, and Red Zone. Artificial Neural Network methods using backpropagation training give 99.90% of accuracy on a dataset which has more amount of data. The evaluation has been done using the confusion matrix and AUC-ROC curves.
Continuous Integration and Continuous Delivery Platform Development of Software Engineering and Software Project Management in Higher Education Ferdian, Sendy; Kandaga, Tjatur; Widjaja, Andreas; Toba, Hapnes; Joshua, Ronaldo; Narabel, Julio
Jurnal Teknik Informatika dan Sistem Informasi Vol 7 No 1 (2021): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v7i1.3254

Abstract

We present a report of development phase of a platform which aims to enhance the efficiency of software project management in higher education. The platform accommodates a strategy known as Continuous Integration and Continuous Delivery (CI/CD). The phase consists of several stages, followed by testing of the system and its deployment. For starters, the CI/CD platform will be deployed for software projects of students in the Faculty of Information Technology, Universitas Kristen Maranatha. The goal of this paper is to show a design of an effective platform for continuous integration and continuous delivery pipeline to accommodate source code compilation, code analysis, code execution, until its deployment, all in a fully automated fashion.
Co-Authors Andreas Widjaja Chandra, Cato Hapnes Toba Joshua, Ronaldo Sanjaya, David Sendy Ferdian Sujadi Setia Budi Tjatur Kandaga Vilano, Nucky