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All Journal Nuansa Informatika Jurnal Accounting Information System (AIMS)
Setiana, Elia
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Computer Science & IT Economics, Econometrics & Finance Education Other

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ANALISIS SENTIMEN PELAKSANAAN KULIAH ONLINE MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE Setiana, Elia; Marwondo; Venia Retreva Danestiara; Wiyanudin
NUANSA INFORMATIKA Vol. 17 No. 2 (2023): Volume 17 No 2 Tahun 2023
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v17i2.11

Abstract

This writing aims to assess the satisfaction of students regarding the implementation of online lectures, categorized into three classes: positive, neutral, and negative. Data collection was conducted using Twint from the social media platform Twitter, with a total of 25,000 tweets. The data processing process to determine sentiment analysis utilized the support vector machine algorithm. With this algorithm, the obtained results show an accuracy rate of 76.86% for positive sentiment. The precision is 0.49, recall is 0.53, and the F1 score is 0.51
P Pengujian Perangkat Lunak Metode Black Box Pada Aplikasi Sistem Pakar Pola Latihan dan Asupan Makanan Setiana, Elia; Ramadhan, Muhammad Rizki; Budiman; R. Yadi Rakhman A4
NUANSA INFORMATIKA Vol. 18 No. 1 (2024): Nuansa Informatika 18.1 Januari 2024
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v18i1.67

Abstract

Software testing is an important part of expert system application development. This software testing aims to ensure optimal performance and functionality of this application, where the application must be able to run according to a previously created design and application testing must ensure that the program is free from errors. The testing methodology includes a series of steps designed to identify potential bugs, ensure proper integration between components, and verify that the application meets functional and non-functional requirements. Testing is carried out using various functional testing scenarios. Test results show that this application is able to provide accurate and relevant solutions in the context of exercise patterns to achieve the desired body goals. Additionally, application performance is tested to ensure fast response and good user experience, even under high load conditions. The findings from this test provide confidence that the "Exercise Pattern and Food Intake Expert System" is ready for use by end users.
Algoritma Gated Recurrent Unit untuk Prediksi Harga Indeks Penutupan Saham LQ45 Danestiara, Venia Restreva; Setiana, Elia; Akbar, Imannudin; Hidayah, Taufik
Jurnal Accounting Information System (AIMS) Vol. 7 No. 1 (2024)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v7i1.814

Abstract

The Indonesia Stock Exchange (IDX) states that stocks, including LQ45 stocks, which constitute the stock market index for the IDX, have become one of the preferred investment options for the public. Investors need to have accurate analysis and information to gain significant profits as stock prices fluctuate due to company performance, industry factors, changes in interest rates, liquidity, global market conditions, market sentiment, and investor psychology. The Gated Recurrent Unit algorithm is suitable for application on historical stock data sets because they are time series data, can be computed and compared on a numerical scale. This algorithm is a variant of the Long Short-Term Memory algorithm or other types of processing modules for Recurrent Neural Networks. The data set used consists of closing price data or close features, comprising a training data set of 4,406 data and a test data set of 1,889 data that have undergone data preparation using various techniques, including data cleansing, data scrubbing, data splitting, data normalization, and data reshaping. The results showed that the Gated Recurrent Unit algorithm is the right strategy because it obtains a good evaluation of model performance, namely MSE of 0.0009; RMSE of 0.17325 and MAE of 0.0207.
Co-Authors Akbar, Imannudin Budiman Danestiara, Venia Restreva Marwondo R. Yadi Rakhman A4 Ramadhan, Muhammad Rizki Taufik Hidayah Venia Retreva Danestiara Wiyanudin