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All Journal International Journal of New Media Technology Jurnal ULTIMATICS Jurnal ULTIMA Computing Jurnal Informatika: Jurnal Pengembangan IT
Alethea Suryadibrata
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Journal : Jurnal ULTIMATICS

 1 
Visualisasi Algoritma sebagai Sarana Pembelajaran K-Means Clustering Alethea Suryadibrata; Julio Christian Young
Ultimatics : Jurnal Teknik Informatika Vol 12 No 1 (2020): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (553.166 KB) | DOI: 10.31937/ti.v12i1.1523

Abstract

Algorithm Visualization (AV) is often used in computer science to represents how an algorithm works. Educators believe that visualization can help students to learn difficult algorithms. In this paper, we put our interest in visualizing one of Machine Learning (ML) algorithms. ML algorithms are used in various fields. Some of the algorithms are used to classify, predict, or cluster data. Unfortunately, many students find that ML algorithms are hard to learn since some of these algorithms include complicated mathematical equations. We hope this research can help computer science students to understand K-Means Clustering in an easier way.
Prediksi Kedatangan Turis Menggunakan Algoritma Weighted Exponential Moving Average Sherly Florencia; Alethea Suryadibrata
Ultimatics : Jurnal Teknik Informatika Vol 12 No 2 (2020): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v12i2.1831

Abstract

Tourism is an important factor for the development of a country. Tourism can be used as a promotion to introduce natural beauty and cultural uniqueness. Government needs to predict how many tourists will come every year to do a planning. Therefore, an application is needed to help to predict the arrival of tourists in each country. In this paper, we use Weighted Exponential Moving Average (WEMA) method to predict the arrival of tourist, tourism expenditure in the country, and departure using data from 2008 to 2018. Error measurement is calculated using the Mean Absolute Percentage Error (MAPE). The result shows that the lowest average MAPE on arrival data with span 2 is at 3.28. The lowest average MAPE on tourism expenditure data with span 2 is at 3.99%. The result shows that the lowest average MAPE on departure data with span 2 is at 3.63%.
Implementasi Algoritma Complement dan Multinomial Naïve Bayes Classifier Pada Klasifikasi Kategori Berita Media Online Muhammad Naufal Randhika; Julio Christian Young; Alethea Suryadibrata; Hadian Mandala
Ultimatics : Jurnal Teknik Informatika Vol 13 No 1 (2021): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v13i1.1921

Abstract

Perkembangan teknologi dan penyebaran informasi di internet terus mengalami peningkatan. Salah satu bentuk informasi yang jumlahnya terus bertambah adalah berita. Media cetak dan elektronik yang kini telah dikemas dalam bentuk digital atau sering dikenal dengan portal berita online atau media online. PT Merah Putih Media merupakan media berita online. Berita yang disampaikan terdiri dari tiga kategori mulai dari berita tentang Indonesia, Hiburan dan Gaya Hidup, serta Olahraga. Namun, pembagian artikel berita ke dalam kategori dilakukan secara manual oleh kepala redaksi jurnalis. Text Mining adalah salah satu teknik yang dapat digunakan untuk melakukan klasifikasi sebuah dokumen. Pada penelitian ini dilakukan klasifikasi kategori otomatis dengan algoritma Multinomial Naïve Bayes, Complement Naïve Bayes, dan gabungan kedua model. Model yang memiliki performa terbaik dinilai dari metrik F1-Score dengan jumlah pembagian data latih dan data uji sebanyak 80:20, diperoleh keberhasilan performa sebesar 90,13% F1-Score.
Co-Authors Andre Budiman Dian Puspita Chandra Efraim Yahya Wijaya Hadian Mandala Julio Christian Young Julio Christian Young Muhammad Naufal Randhika Sherly Florencia