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Analisis Sentimen Opini Mahasiswa Terhadap Aplikasi Portal Mahasiswa UTY Menggunakan Metode Naïve Bayes Classifier Agus Ardiyanto; Enny Itje Sela
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 1 (2024): Jurnal Indonesia : Manajemen Informatika dan Komunikasi (JIMIK)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) AMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i1.508

University Technology of Yogyakarta (UTY) has released the UTY Student Portal Application since 2020 which is an improvement in services to support student academic activities. The UTY Student Portal application was developed by Puskom from Yogyakarta Technology University. The UTY Student Portal application is a system designed and built to manage data related to academic information which includes student data, lecturer data, lecture results records, lecture schedules and so on. The presence of this Student Portal Application has given rise to various comments from its users, namely UTY students. Seeing this problem, the researchers conducted research on student opinions regarding the UTY Student Portal Application using the Naïve Bayes Classifier. This research uses the Python programming language. Based on the results of the discussion, it was found that the accuracy level was 93% in the training process and the testing accuracy was around 65.2% with a distribution of training and test data of 70%:30% from 150 opinion text data. This model creation experienced overfitting, because the resulting testing accuracy was much smaller than the training accuracy.

Analisis Sentimen Komentar Youtube Tentang Resesi Global 2023 Menggunakan LSTM Ari Hendrawan; Enny Itje Sela
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 1 (2024): Jurnal Indonesia : Manajemen Informatika dan Komunikasi (JIMIK)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) AMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i1.526

The COVID-19 pandemic that occurred in 2020 caused the economy to decline due to declining economic activity, making companies decide to lay off some workers so that the unemployment rate increased. This makes economic activists predict that there will be a global recession in 2023, Youtube as a video-sharing platform is one of the places to discuss through the comment’s column. The increasing number of YouTube users is one of the references for sentiment analysis using data taken from video comments. Long Short-Term Memory (LSTM) is used to perform sentiment analysis, with 500 data divided into training data and test data, resulting in the highest accuracy of 90% training data and 76% test data. This result is obtained from the configuration of the LSTM architecture with dense layers using sigmoid activation and 50 epochs.

Klasifikasi Batik Pekalongan Berdasarkan Citra dengan Metode GLCM dan JST Backpropagation Fathul Am; Enny Itje Sela
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 1 (2024): Jurnal Indonesia : Manajemen Informatika dan Komunikasi (JIMIK)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) AMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i1.532

Batik is an Indonesian cultural heritage that is internationally recognized by UNESCO. However, knowledge about the types of batik, especially traditional Pekalongan batik, is increasingly forgotten due to globalization. This research aims to create a Pekalongan traditional batik image classification system through Gray Level Co-Occurrence Matrix (GLCM) feature extraction and Artificial Neural Network (ANN) classification method. This system aims to make it easier for people to identify Pekalongan batik motifs without requiring special skills. The results showed that the GLCM and JST methods can be used to classify Pekalongan batik can predict correctly. The use of JST Backpropagation architecture with 3 hidden layers resulted in train data accuracy of 46.6% and test data accuracy of 55.5%. This system is expected to help preserve the cultural heritage of batik and increase public understanding of Pekalongan batik motifs.

Perancangan Aplikasi Quiz Sebagai Media Pembelajaran Sejarah Idham Kholed Rachmawan; Enny Itje Sela
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 1 (2024): Jurnal Indonesia : Manajemen Informatika dan Komunikasi (JIMIK)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) AMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i1.575

Mastery of historical concepts is important for students in increasing their understanding of country’s past dan history. However, conventional history learning metodhs still often experience difficulties in attracting and motivating students to learn. Therefore, we need an interactive and fun learning media to increase students’ learning history. One alternative interactive learning media is an interactive quiz application. This study aims to help teachers in the learning process so that students are more interested in learning history with learning media in the form of interactive quiz applications. The interactive quiz application developed in this final project is an android-based application that makes it easier for students to learn history in a fun way. This application provides quizzes rellated to history subject matter wich are presented interactively. In addition, this application also provides an evaluation feature to evaluate students’ ability to master historical concepts.

Nutritional Status Classification Of Stunting In Toddlers Using Naive Bayes Classifier Method Risky Devandra Hartana; Enny Itje Sela
Journal of Technology Informatics and Engineering Vol 3 No 1 (2024): April : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i1.154

Stunting in toddlers is one of the prevalent issues of malnutrition in Indonesia. The causes of Stunting are diverse, and one contributing factor is the insufficient nutritional intake required for toddlers. The categorization of Stunting nutritional status in toddlers is crucial to identify those experiencing Stunting, enabling appropriate interventions to prevent more serious health problems in the future. This research aims to develop a classification model for short nutritional status in toddlers using the Naive Bayes Classifier method. The data utilized in this study originate from anthropometric measurements of toddlers in the Malebo area, Kandangan, Temanggung, Central Java. The anthropometric data include weight, height, and age of the toddlers. This data is then processed using the Naive Bayes Classifier method to classify the nutritional status of Stunting in toddlers. The results of this research are expected to assist in identifying toddlers experiencing Stunting, facilitating appropriate interventions to prevent more serious health issues in the future. Additionally, the Naive Bayes Classifier method employed can be applied in similar studies to enhance the quality of life, especially for children in Indonesia, particularly in the Malebo area, Kandangan, Temanggung, Central Java.

Analisis Sentimen Opini Mahasiswa Terhadap Aplikasi Portal Mahasiswa UTY Menggunakan Metode Naïve Bayes Classifier Ardiyanto, Agus; Sela, Enny Itje
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 1 (2024): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i1.508

University Technology of Yogyakarta (UTY) has released the UTY Student Portal Application since 2020 which is an improvement in services to support student academic activities. The UTY Student Portal application was developed by Puskom from Yogyakarta Technology University. The UTY Student Portal application is a system designed and built to manage data related to academic information which includes student data, lecturer data, lecture results records, lecture schedules and so on. The presence of this Student Portal Application has given rise to various comments from its users, namely UTY students. Seeing this problem, the researchers conducted research on student opinions regarding the UTY Student Portal Application using the Naïve Bayes Classifier. This research uses the Python programming language. Based on the results of the discussion, it was found that the accuracy level was 93% in the training process and the testing accuracy was around 65.2% with a distribution of training and test data of 70%:30% from 150 opinion text data. This model creation experienced overfitting, because the resulting testing accuracy was much smaller than the training accuracy.

Analisis Sentimen Komentar Youtube Tentang Resesi Global 2023 Menggunakan LSTM Hendrawan, Ari; Sela, Enny Itje
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 1 (2024): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i1.526

The COVID-19 pandemic that occurred in 2020 caused the economy to decline due to declining economic activity, making companies decide to lay off some workers so that the unemployment rate increased. This makes economic activists predict that there will be a global recession in 2023, Youtube as a video-sharing platform is one of the places to discuss through the comment’s column. The increasing number of YouTube users is one of the references for sentiment analysis using data taken from video comments. Long Short-Term Memory (LSTM) is used to perform sentiment analysis, with 500 data divided into training data and test data, resulting in the highest accuracy of 90% training data and 76% test data. This result is obtained from the configuration of the LSTM architecture with dense layers using sigmoid activation and 50 epochs.

Klasifikasi Batik Pekalongan Berdasarkan Citra dengan Metode GLCM dan JST Backpropagation Fathul Am; Sela, Enny Itje
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 1 (2024): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i1.532

Batik is an Indonesian cultural heritage that is internationally recognized by UNESCO. However, knowledge about the types of batik, especially traditional Pekalongan batik, is increasingly forgotten due to globalization. This research aims to create a Pekalongan traditional batik image classification system through Gray Level Co-Occurrence Matrix (GLCM) feature extraction and Artificial Neural Network (ANN) classification method. This system aims to make it easier for people to identify Pekalongan batik motifs without requiring special skills. The results showed that the GLCM and JST methods can be used to classify Pekalongan batik can predict correctly. The use of JST Backpropagation architecture with 3 hidden layers resulted in train data accuracy of 46.6% and test data accuracy of 55.5%. This system is expected to help preserve the cultural heritage of batik and increase public understanding of Pekalongan batik motifs.

Perancangan Aplikasi Quiz Sebagai Media Pembelajaran Sejarah Rachmawan, Idham Kholed; Sela, Enny Itje
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 1 (2024): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i1.575

Mastery of historical concepts is important for students in increasing their understanding of country’s past dan history. However, conventional history learning metodhs still often experience difficulties in attracting and motivating students to learn. Therefore, we need an interactive and fun learning media to increase students’ learning history. One alternative interactive learning media is an interactive quiz application. This study aims to help teachers in the learning process so that students are more interested in learning history with learning media in the form of interactive quiz applications. The interactive quiz application developed in this final project is an android-based application that makes it easier for students to learn history in a fun way. This application provides quizzes rellated to history subject matter wich are presented interactively. In addition, this application also provides an evaluation feature to evaluate students’ ability to master historical concepts.

Pengembangan Sistem Point of Sale Berbasis Web dan Mobile di Kooi Coffee Prawirdani, Adil; Sela, Enny Itje
ILKOMNIKA Vol 6 No 3 (2024): Volume 6, Nomor 3, Desember 2024
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v6i3.689

Kooi Coffee, sebuah kedai kopi di Karimun, Kepulauan Riau, masih menggunakan sistem pencatatan transaksi secara konvensional. Dalam sistem ini, pencatatan pesanan hingga pembuatan setruk dilakukan menggunakan kertas dan direkapitulasi ke dalam buku transaksi di akhir hari. Sistem konvensional tersebut berpotensi menimbulkan berbagai permasalahan, seperti kesulitan dalam pelacakan penjualan, risiko kesalahan pencatatan, ketidakakuratan laporan keuangan, serta belum dapat mengakomodasi permintaan metode pembayaran digital oleh pelanggan. Penelitian ini bertujuan mengembangkan sistem Point of Sale (POS) berbasis web dan mobile untuk mengoptimalkan proses transaksi dan manajemen operasional Kooi Coffee. Sistem POS dikembangkan melalui pendekatan client-server dengan arsitektur REST API, di mana bagian backend dibangun menggunakan bahasa pemrograman Go (Golang), PostgreSQL sebagai basis data relasional, aplikasi web manajerial menggunakan React, dan aplikasi mobile kasir dikembangkan menggunakan Flutter. Pengujian sistem menggunakan metode black box testing menunjukkan keberhasilan 100% pada total 31 skenario yang diuji. Sistem POS yang dikembangkan telah mampu mengintegrasikan proses transaksi, manajemen menu, pengelolaan akun pengguna, pelaporan, serta pembayaran digital melalui payment gateway. Selain itu, aplikasi mobile juga dapat terhubung dengan printer thermal untuk mencetak setruk transaksi. Secara keseluruhan, sistem POS yang dihasilkan dapat memberikan kemudahan dalam operasional Kooi Coffee dan mengoptimalkan proses bisnisnya.

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