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Chandra, Cato
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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.
Analisis Komparatif ARIMA dan Prophet dengan Studi Kasus Dataset Pendaftaran Mahasiswa Baru Chandra, Cato; 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.v6i2.2676

Abstract

This research presents all studies, methodologies, and results about testing the accuracy of predictions on new student marketing data by region using the Prophet and Autoregressive Integrated Moving Average (ARIMA) methods. The dataset selected for this study uses 26 years of actual data that has an annual interval. The data was prepared for time series forecasting analysis, therefore, several numbers of data preprocessing were applied such as log transformation and resampling. To get efficient variables, the best variables will be sought to improve the accuracy of predictions. Both models will conduct training and test data to produce values that can be compared using the metric regression model. Based on the training conducted, Prophet has better performance than ARIMA.
Co-Authors Narabel, Julio Sanjaya, David Setia Budi Vilano, Nucky