Herwanto Herwanto
Universitas Krisnadwipayana, Jakarta

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Implementasi Aplikasi Business Intelligence Untuk Memonitor Efisiensi Pengelolaan Rumah Sakit Herwanto Herwanto; Ali Khumaidi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 3 (2020): Juli 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i3.2090

Abstract

The need for fast and accurate information has become the need of every company, including hospitals. This is one of the factors that makes a company superior to other companies. In making the right and accurate decisions, leaders need information that is presented clearly, easily understood, on time, and in accordance with needs. To support the presentation of such information a database, data warehouse and other applications that are easy to understand are needed. Hospitals as a socio-economic institution are not only required to provide solutions to health problems but are also demanded to always improve the quality of their services. For this purpose to be achieved, its management must be efficient. Service indicators can be used as a measuring tool to assess the level of management efficiency. Business Intelligence (BI) application is one form of implementation that is able to facilitate management to monitor hospital performance. This research explores the use of information technology to build BI applications, reviewing the right approach in building BI applications, as well as several important aspects that must be considered for the system work for the hospital environment. There are two main stages in building this application, namely: building a data warehouse originating from an electronic medical record database and hospital operations, and building a BI application. With the formation of this BI application, it is very useful for hospital management in managing their institutions better
Klasifikasi SMS Spam Berbahasa Indonesia Menggunakan Algoritma Multinomial Naïve Bayes Herwanto Herwanto; Nuke L Chusna; Muhammad Syamsul Arif
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3119

Abstract

Based on a report submitted by Truecaller Insights Report 2020, Indonesia placed sixth position with the most spam messages, one of the spam applications is SMS. Spam SMS contains unwanted or unsolicited messages, including advertisements, scams and so on. The existence of this spam message causes inconvenience from the user's side when receiving spam SMS, and some even become victims of crime after responding to the SMS. To minimize inconvenience and crime caused by spam messages, the purpose of this study is to filter SMS spam or SMS filtering by classifying SMS spam using the Multinomial Naïve Bayes algorithm by looking for the best combination of parameters to improve the performance of the model that is formed. The results of model testing get the highest precision value in the MNB and SVM models by 93%, the highest recall value in the SVM model at 94%, the highest f1-score value in the SVM model at 94%, the highest accuracy value in the SVM model at 95%, and the fastest test time on the MNB model is 2.66 ms