KALBISIANA Jurnal Sains, Bisnis dan Teknologi
Vol. 8 No. 2 (2022): Kalbisiana

Pengembangan Aplikasi Klasifikasi Teks E-mail Keluhan Akademik Pelanggan Studi Kasus: Operasional Kalbis Institute

Daniel Alexander Philip (Institut Teknologi dan Bisnis Kalbis)

Article Info

Publish Date
26 Jul 2022

Abstract

This study aims to develop an application that can classify messages written by Kalbis students. The data used is a text message of student questions or complaints that have been sent to the Academic Operations and Finance through the Gmail service. The message data will be classified into Academic Operation and Finance classes. The data will be weighted based on the frequency of its occurrence in all messages using the Term Frequency – Inverse Document Frequency (TF-IDF) method. Then the weighted data will be classified using the Multinomial Naïve Bayes method. The Incremental Method is a method used to develop applications. The results obtained in this study are applications that are able to classify student messages with a model accuracy value of 86%, with each precision, recall and f1-score : 0.9, 0.83 and 0.84 in iteration one and application interface with objects in it that can be works fine in iteration two.

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Journal Info
KALBISIANA Jurnal Sains, Bisnis dan Teknologi
Website

Abbrev

kalbisiana

Publisher

UNIVERSITAS KALBIS

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences

Description

KALBISIANA Jurnal Sains, Bisnis dan Teknologi adalah jurnal akses terbuka akademik yang bertujuan untuk mempromosikan integrasi sains, bisnis dan teknologi. Fokusnya adalah menerbitkan makalah tentang sains, bisnis dan teknologi. Makalah yang dikirimkan akan ditinjau oleh komite teknis jurnal. Semua ...