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Olivia Kembuan
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oliviakembuan@unima.ac.id
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+6281340403034
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jointer@unima.ac.id
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Program Studi Teknik Informatika Fakultas Teknik, Kampus Unima di Tondano, Minahasa, Sulawesi Utara
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JOINTER : Journal of Informatics Engineering
Published by Universitas Negeri Manado
ISSN : -     EISSN : 27237958     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
Journal of Informatics and Engineering (Jointer) diterbitkan oleh Program Studi Teknik Informatika, Fakultas Teknik (FATEK) Universitas Negeri Manado (UNIMA) setiap bulan Juni dan Desember dengan nomor e-issn : 2723-7958. Jointer merupakan jurnal open-access atau dengan kata lain semua artikel yang diterbitkan bersifat terbuka dan dapat diakses tanpa biaya untuk mendukung pertukaran pengetahuan secara global. Jointer menerbitkan artikel penelitian (research article), artikel telaah/studi literatur (review article/literature review), laporan kasus (case report) dan artikel konsep atau kebijakan (concept/policy article), di bidang-bidang menyangkut Teknologi Informasi seperti berikut : Business Process Management Business Intellegent Computer Architecture Design Computing Theory Conceptual Modeling, Languages and design Computer Network Data Mining Data Warehouse Decision Support System e-Healthcare, e-Learning, e-Manufacturing, e-Commerce Embedded system Enterprise Application ERP dan Supply Chain Management Geographical Information System Human Computer Interaction Image Processing and Pattern Recognition Information Infrastructure for Smart Living Spaces Information Retrievel Information Security Information-centric Networking Intelligent Transportation Systems IT Management dan IT Governance Media, Game and Mobile Technologies Models, Methods and Techniques Natural Language Processing Network Computer Security Remote Sensing Robotic Systems Smart Appliances & Wearable Computing Devices Smart City Smart Cloud Technology Smart Sensor Networks Smart Systems Software Engineering
Arjuna Subject : Teknik (semua kategori) - Teknologi Media
Articles 5 Documents
 1 
Search results for , issue "Vol 2 No 01 (2021): JOINTER : Journal of Informatics Engineering" : 5 Documents clear
Aplikasi Augmented Reality Penuntun Shalat Untuk Anak Usia Dini Ramdan Adjis; Vivi Pegie Rantung; Sondy Kumajas; Gladly Caren Rorimpandey
JOINTER : Journal of Informatics Engineering Vol 2 No 01 (2021): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v2i01.21

Abstract

Abstract— This prayer guide Augmented Reality application is designed for early childhood with parental supervision. The purpose of developing this application is to give new experiences for early childhood in learning prayer with technology of Augmented Reality Application. The method used is Multimedia Development Life Cycle (MDLC) wich consists of six stages, namely Concept, Design, Material Collection, Assembly, Testing, and Distribution. After the application development process, the result of this research is anAugmented Reality Application that is used by early childhood in learning prayer using a Smartphone.
Perancangan Dan Implementasi Manajemen Stok Obat di Apotek RSUD Berbasis Web Sandika Karepouwan; Verry Ronny Palilingan; Olivia Kembuan
JOINTER : Journal of Informatics Engineering Vol 2 No 01 (2021): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v2i01.26

Abstract

Tujuan penelitian ini adalah untuk merancang dan mengimplementasi manajemen stok obat berbasis web di Apotek RSUD Amurang. Penelitian ini menggunakan metode pengembangan sistem Prototype, dengan 5 tahapan yaitu komunikasi, perancangan secara cepat, pemodelan perancangan secara cepat, pembuatan prototype dan penyerahan sistem & dan umpan balik, dengan menggukan Bahasa PHP (Hypertext Preprocessor) dan databse MySQL. Berdasarkan penelitian yang dilakukan maka didaptkan hasil bahwa aplikasi manajemen stok obat ini dapat mempermudah proses pengelolaan, pencarian, dan pelaporan data obat di Apotek RSUD Amurang.
Analisis Prediksi Jumlah Pasien Rawat Inap di Rumah Sakit GMIM Siloam Sonder Menggunakan Metode Triple Exponential Smoothing Feibe Lawalata; Eko Sediyono; Hindriyanto Purnomo
JOINTER : Journal of Informatics Engineering Vol 2 No 01 (2021): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v2i01.28

Abstract

The increase in patients that occurs every month needs to be considered by every hospital, be it private hospitals or government hospitals. With the predictive value of the number of patients for each month. It is hoped that it can help hospital management, in making decisions to improve patient service facilities, especially in inpatient installations. In this study, the forecasting method used is Triple Exponential Smoothing, because this method is quite simple and also has advantages. The triple exponential smoothing method can adjust the trend of changes and seasonal components. The research was conducted at GMIM Siloam Sonder General Hospital, by taking samples in the form of data on the number of patients for the last 3 years using excel format. From the results of the analysis carried out, the forecast results obtained for the next 3 years are an increase seen from the increase in the total number of patients each year. The forecast value obtained is classified into high-accuracy forecasting because it has a MAPE value ≤ of 10%.
Penerapan Algoritma K-Nearest Neighbors Pada Analisis Sentimen Metode Pembelajaran Dalam Jaringan (DARING) Di Universitas Kristen Wira Wacana Sumba Andry Tanggu Mara; Eko Sediyono; Hindriyanto Purnomo
JOINTER : Journal of Informatics Engineering Vol 2 No 01 (2021): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v2i01.30

Abstract

The education sector is one of the areas that has felt the major impact of the Covid-19 pandemic. The impact that arises is teaching and learning process must be carried out from home using the online learning method. This teaching and learning method raises a variety of responses from students. This is what makes researchers analyze these views, both in the form of positive opinions or negative opinions. The analysis process is carried out by applying sentiment analysis or opinion mining from the comment on Facebook, text mining is processed using the prepocessing method, labeled it to positive and negative. Based on the available data, a classification process is carried out using the K-Nearest Neighbors algorithm. Rapid Miner is used to experiment text data with the KNN algorithm in order to find the value of accuracy, precision and recall. From the results of research, it was obtained a value of 87.00% for accuracy and 0.916 for the AUC value. The values ​​are high enough for the classification of student opinion against this pandemic so that this research is classified as Excellent Classification.
Analisis Sentimen New Normal Pada Masa Covid-19 Menggunakan Algoritma Naive Bayes Classifier Shania Kaparang; Daniel Riano Kaparang; Vivi Pegie Rantung
JOINTER : Journal of Informatics Engineering Vol 2 No 01 (2021): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v2i01.33

Abstract

The impact of the covid-19 pandemic is so great that the government must have policies to reduce its impact. One of the government's policies is the new normal which requires all people to wear masks, keep their distance and wash their hands. In its application, of course, there are positive and negative sentiments uploaded to Twitter. This study aims to model the analysis of public sentiment regarding the government's new normal policy during the covid-19 pandemic in Indonesia. The stages of this research are data crawling, labeling, neutral data removal, preprocessing, distribution of training data and data testing, creation of a nave Bayes classification system, system testing and visualization of research results using wordcloud. The classification system performance includes 80.37% accuracy, 87.38% precision, 82.57% recall and 84.91% f-measure. The results of this study are 5194 tweets classified as positive sentiment and 2908 tweets classified as negative sentiment, this shows that there are more positive sentiments than negative sentiments. But from the numbers it can be seen that the comparison is not too far between positive and negative sentiments, meaning that there is a lack of public response to the new normal government policies during the pandemic.

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