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Henry Novianus Palit
Program Studi Teknik Informatika, Universitas Kristen Petra Surabaya
Computer Science & IT

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Aplikasi Analisa Sentimen Bilingual dan Emoji pada Komentar Media Sosial Instagram Menggunakan Metode Support Vector Machine Satria Adi Nugraha; Henry Novianus Palit; Hans Juwiantho
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Indonesia is ranked 4th as the most Instagram user in the world. This makes business people triggered to promote their products and services to content creators to make reviews and upload them on Instagram. Business people need to evaluate uploads to assess whether the promotions carried out get a positive or negative response from netizens. Evaluation can be done by checking the comments column. Instagram comments not only contain comments in Indonesian but in English along with emojis. However, checking manually will certainly take a lot of time. Therefore, it is necessary to build an application system that can detect bilingual sentiments and emojis in Instagram comments. This system was built using the Support Vector Machine method to classify language, Indonesian sentiment, and English sentiment and then evaluated using the accuracy value. The data used is a sample of uploaded comments in the form of posts, reels, and IGTV. The combination of preprocessing cleansing, normalization, stopwords removal, and stemming as well as parameter tuning using GridSearchCV was also tested to find the best model. The model is divided into language classification models with Indonesia, Inggris, and Campuran labels, Indonesian sentiment classifications, and English sentiment classifications with positive, neutral, and negative labels. The best accuracy obtained by the model for language classification, Indonesian sentiment, and English sentiment is 88.77%, 73.10%, and 71.56%, respectively. In addition, emojis need to be analyzed because the model that analyzes emojis has 3.875% better accuracy than the model that ignores emoji.
Game RPG Berbasis Android untuk Mendorong Pengguna Berolahraga Wilson Mark; Henry Novianus Palit; Djoni Haryadi Setiabudi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

With the lockdown period due to Covid-19, maintaining stamina and body health is a priority. People are advised to reduce activities outside the home and work from home. Working from home is often done behind a desk, and after work people do activities to relieve boredom such as watching television, playing games, and other sedentary activities that cause them to be unhealthy. Playing games on a smartphone is becoming more popular because they are easily accessible and only require a smartphone that has many features already on it. This thesis research aims to create a game application on a smartphone to overcome this problem. This RPG game application, is hoped to increase people's interest in exercising by playing on a smartphone that detects motion using the accelerometer sensor and calculates calorie burned using the MET formula. The results of testing the game show that 40% of respondents are more interested in exercising. In addition, the calculation of calories is quite accurate compared to other tools. And it is also proven that this game can meet the recommended daily exercise.
Prediksi Penjualan Pada Data Penjualan Perusahaan X Dengan Membandingkan Metode GRU, SVR, DAN SARIMAX Jordan Nagakusuma; Henry Novianus Palit; Hans Juwiantho
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Sales forecasting is an attempt to predict sales using several methods, such as statistical methods, machine learning, and others. Sales forecasts are considered important because poor forecasts can have an impact on the company's inventory so that it can cause storage of too much or too little goods, causing the company to lose. Therefore, we need a model that can predict sales so that companies can plan before filling stock. However, forecasts cannot be done directly, because a company's sales data is definitely influenced by various factors and sales last month are not always the same as in the future, so external data is needed in predicting future sales. Therefore, in this thesis a prediction will be made using 3 models, namely the GRU, SVR and SARIMAX models with the help of external data in the form of CPI data and inflation data. In addition, this thesis also conducted a correlation test to determine whether the sales data to be predicted has significance/relationship with external data so that it helps in predicting sales data. The results obtained from this study are that pot data is more suitable for using univariate data with the GRU model, with RMSE Train 3.22, RMSE Test 2.93. For hanger and sealware data, the best model for prediction is the SARIMAX model with univariate data type (RMSE 30.43) and multivariate data type (RMSE 8.07).
Hybrid Recommendation System untuk Peminjaman Buku Perpustakaan dengan Collaborative dan Content-Based Filtering Adrianus Aditya Widjaja; Henry Novianus Palit
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

The development of technology is growing rapidly and followed with the growth of digital data in the internet. Therefore, recommendation system was invented and can be used in many aspects of human life. For example, a book recommendation system can be used to help user to choose a book to be read which is suitable with their preferences. Using a recommendation system can help to reduce the required time to choose a book because of the massive choices of books. This research using hybrid recommendation system which combined collaborative filtering and content-based filtering method. The purpose of this study was to achieve a better recommendation outcome. To measure how well the result of the recommendation, mean reciprocal rank and mean average precision was used. The results showed that weighted hybrid yields a better score than the other two methods. The score was 0.2113 and 0.0988 respectively
Co-Authors Adrianus Aditya Widjaja Agustinus Noertjahyana Alvin Nathaniel Tjondrowiguno Andre Gunawan Anita Nathania Purbowo Christianto Imanuel Aryanto Cristine Ferlly Wiyanto Daniel Jeremia Djoni Haryadi Setiabudi Hans Juwiantho Ivana Jovita Handoko Jennifer Soeryawinata Jordan Nagakusuma Kevin Hartono Leo Willyanto Santoso Liliana Liliana Meliana Kusuma Pangkasidhi Michael Jonathan Misael Rithe Setio Satria Adi Nugraha Silvia Rostianingsih Sugiyanto Goutama Wilson Mark