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All Journal Jurnal Informatika dan Rekayasa Elektronik Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Publikasi Teknik Informatika (JUPTI) Harmoni: Jurnal Ilmu Komunikasi Dan Sosial Jurnal Sistem Informasi dan Ilmu Komputer Jurnal Penelitian Teknologi Informasi dan Sains Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi RESLAJ: Religion Education Social Laa Roiba Journal Router : Jurnal Teknik Informatika dan Terapan Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi Modem : Jurnal Informatika dan Sains Teknologi Router : Jurnal Teknik Informatika dan Terapan
Andreas Nugroho Sihananto
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Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Social Sciences

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Perbandingan Algoritma Random Forest dan Logistic Regression Untuk Analisis Sentimen Ulasan Aplikasi Tumbuh Kembang Anak Di Play Store Muhammad Alfyando; Fetty Tri Anggraeny; Andreas Nugroho Sihananto
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 1 (2024): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Universitas Katolik Widya Karya Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i1.2262

Abstract

Early childhood plays an important role in forming the basis of development, which involves stimulation of various aspects such as moral religious values, social emotional, language, cognitive, and physical motor skills. The concept of early childhood learning is focused on play, where every activity is designed to be play, so that learning becomes more effective. Parents also need to understand today's children's education to interact with children positively. This research focuses on sentiment analysis of children's education-based app reviews on the Google Play Store, using Random Forest and Logistic Regression methods. The review data is taken from three apps with the theme of child development, namely "About Kids", "PrimaKu", and "Teman Bumil", with a range of review years between 2018 and 2023. The test results show that Logistic Regression has higher accuracy compared to Random Forest, especially in the "About Kids" and "PrimaKu" applications with accuracy above 90%. The conclusion of this research highlights the importance of sentiment analysis in improving understanding of user responses to children's education applications, with suggestions for future research to increase the number of datasets and variations in testing schemes by tuning hyperparameters to improve prediction accuracy and more optimal results.
Implementasi Collaborative Filtering Pada Aplikasi E-Commerce Penyewaan Costume Cosplay Muhammad Eko Prasetyo; Andreas Nugroho Sihananto; Firza Prima Aditiawan
Jurnal Publikasi Teknik Informatika Vol 3 No 1 (2024): Januari: Jurnal Publikasi Teknik Informatika
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v3i1.2517

Abstract

Cosplay, a global popular cultural phenomenon, presents a challenge for cosplayers in obtaining suitable costumes. For instance, with the surge in cosplay events in Surabaya in July 2023, the development of a costume rental application could be a solution. This application allows cosplayers to easily rent costumes, reducing the cost and effort of creating their own attire. Utilizing Collaborative Filtering and K-Nearest Neighbor (K-NN) methods, the app will recommend costumes based on user interactions within an implicit feedback system. This research aims to create a practical and cost-effective solution for cosplayers in fulfilling their costume needs for cosplay events.
Implementasi SuperTML Untuk Klasifikasi Genre Musik Indonesia Joni Bastian; Made Hanindia Prami Swari; Andreas Nugroho Sihananto
Harmoni: Jurnal Ilmu Komunikasi dan Sosial Vol. 1 No. 4 (2023): Desember : Harmoni : Jurnal Ilmu Komunikasi dan Sosial
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/harmoni-widyakarya.v1i4.1516

Abstract

Music genres are becoming increasingly diverse, and many people listen to music because it has benefits such as refreshing, motivating or therapeutic. However, with the increasing number of genres, some listeners have a tendency towards the type of genre they like. In Indonesia itself, there are several popular music genres such as pop, folk, rock, indie and dangdut. Classification of music genres is an interesting topic when looking at this behaviour. Several approaches to classify popular music genres include audio and tabular data approaches. In this research, classifying music genres using an image approach by implementing SuperTML to change the form of tabular data into image form, which is then trained using a pre-trained CNN Densenet, succeeded in achieving an accuracy of 67%.
Pengembangan Game Edukasi Sejarah Perebutan Gudang Don Bosco Berbasis Narasi Menggunakan Interactive Digital Narrative Rifki Riza Alfiansyah; Pratama Wirya Atmaja; Andreas Nugroho Sihananto
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 1 No. 4 (2023): DESEMBER : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v1i4.1264

Abstract

The development of technology has facilitated easy access to information through the internet. Nevertheless, many students are still less interested in studying Indonesian history. To capture the interest of current students, integrating learning methods with gaming is a step that can be taken. The aim of this research is to create an interactive narrative-based educational game that conveys knowledge about the historical battle in Surabaya, specifically the Don Bosco warehouse raid. This study uses the Unified Modeling Language (UML) model and the Interactive Digital Narrative (IDN) development method as the framework and foundation for writing interactive storytelling narratives, resulting in a gaming application that is both enjoyable and educational. Based on Likert scale testing, this educational game application provides insights into the history of the Don Bosco warehouse raid with a score of 3.65 on the Likert scale.
Penggunaan Teknologi Unity Dalam Pembuatan Gim Edukasi Sejarah: Pertempuran 10 November 1945 Achmad Zahrul Ali Zadan; Pratama Wirya Atmaja; Andreas Nugroho Sihananto
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 1 No. 4 (2023): DESEMBER : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v1i4.1267

Abstract

The development of technology in learning has opened up new opportunities to improve historical understanding through innovative approaches. In this context, this research focuses on the use of Unity technology in the development of an educational game that explores the events of the Battle of November 10, 1945 in Surabaya. This research aims to design and implement an educational game that is interactive and deepens understanding of the historical event. Researchers utilized the Unity development platform to create a near-native environment and provide a fun learning experience. The method used is Interactive Digital Narratives (IDN). The result of this research is an educational narrative-based game the history of the Battle of November 10, 1945.
Pembuatan Game Edukasi Bernarasi Sejarah Insiden Perobekkan Bendera Belanda Di Hotel Yamato Menggunakan Unity Mochammad Yanuar Fitroni; Pratama Wirya Atmaja; Andreas Nugroho Sihananto
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 1 No. 4 (2023): DESEMBER : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v1i4.1271

Abstract

The development of technology is increasingly advanced, there are many new innovations that are useful to facilitate activities, one of which is in the world of education. One of the innovations is an educational game that was created as a means of teaching and learning so that students and teachers can understand the material easily. The purpose of this research is to create a narrative game about one of the histories in Indonesia, where this educational game is a means of learning and to increase curiosity about the history of Indonesia. This educational game is made with a game engine called unity and the method used is interactive digital narratives (IDN) with several stages of development, namely requirements, general design, and detailed design. The result of this research is an educational game application narrating the history of the tearing of the Dutch flag at the Yamato Hotel and as a means of learning and introducing more history in Indonesia.
Klasifikasi Lexicon-Based Sentiment Analysis Tragedi Kanjuruhan pada Twitter Menggunakan Algoritma Convolutional Neural Network Arif Widiasan Subagio; Anggraini Puspita Sari; Andreas Nugroho Sihananto
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 4 No. 1 (2024): Maret : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v4i1.759

Abstract

This study aims to conduct a sentiment analysis of conversations on social media Twitter related to the Kanjuruhan Tragedy. Social media, especially Twitter, has become a significant platform for Indonesians to share their thoughts and feelings regarding this tragic event. We used two approaches for sentiment analysis, namely Lexicon-based and Convolutional Neural Network (CNN), with a focus on classifying sentiments in positive, negative, and neutral categories. This study also involves references to several previous studies that implemented various sentiment analysis methods. It is hoped that the results of this study can provide deep insight into the responses and feelings of the public on social media related to the Kanjuruhan Tragedy. The lexicon-based sentiment analysis classification of the Kanjuruhan Tragedy on twitter social media using the CNN algorithm successfully analyzed the sentiment results of tweets related to the tragedy where most of the tweets obtained had negative sentiments with test results of precision value 87.74%, recall 87.51%, and f1-score 87.27% with a classification accuracy of 87.27% and took 3 minutes 23 seconds of training time.
Analisis Sentimen Pada Pembatalan Tuan Rumah Indonesia Di Piala Dunia U-20 Menggunakan Fasttext Embeddings Dan Algoritma Recurrent Neural Network Aan Evian Nanda; Andreas Nugroho Sihananto; Agung Mustika Rizki
SABER : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Vol. 2 No. 2 (2024): April : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi
Publisher : STIKes Ibnu Sina Ajibarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59841/saber.v2i2.1000

Abstract

Indonesia's golden opportunity to take part in a world-class soccer competition at the U-20 World Cup competition was wiped out, as FIFA gave the decision to revoke Indonesia's status as host of the U-20 World Cup. Indonesian netizens who felt disappointed expressed their opinions and trended on social media Twitter. This research focuses on sentiment analysis of tweets using a combination of FastText embeddings method for word vectorization and using LSTM type RNN algorithm for sentiment classification. The dataset used totals 9,645 data consisting of 4,141 positive data and 5,504 negative data taken from March 29, 2023 to April 05, 2023. The test results on the LSTM model provide the best performance with an accuracy value of 74.92%, precision 74.74%, recall 74.92%, and f1-score 74.78%. The conclusion of this research is that the majority of datasets have negative sentiments, which means that people are more likely to give negative opinions than to provide support to Indonesian football which is experiencing problems. It is hoped that with this conclusion in the future people will better control their opinions and provide positive opinions when Indonesia is experiencing problems.
Pengembangan Aplikasi Pembelajaran Grammar Bahasa Inggris Menggunakan Gamifikasi dan ChatGPT Lintang Pramudya Anpurnan; Andreas Nugroho Sihananto; Pratama Wirya Atmaja
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 2 (2024): Juni : Router: Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i2.60

Abstract

Education serves as the main pillar in the effort to develop human resources, continually evolving in line with the progress of time. Within the realm of education, English language learning plays a crucial role. However, the process of English language learning often faces challenges, including low levels of student motivation. This research explores the use of gamification with integrated chatGPT as an innovative solution capable of boosting student motivation and making learning more engaging and effective. Adapting previously proposed methodologies, this application is web-based, developed using Laravel, and tested using Likert scale. The testing yielded a satisfactory average result of 83%, with a 15.64% increase in user scores. The findings of this research provide a positive contribution to enhancing the quality of English language education in Indonesia, particularly at the Junior High School level.
Perbandingan Performa Labeling Lexicon InSet dan VADER pada Analisa Sentimen Rohingya di Aplikasi X dengan SVM Muhammad Fernanda Naufal Fathoni; Eva Yulia Puspaningrum; Andreas Nugroho Sihananto
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 3 (2024): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v2i3.112

Abstract

Rohingya in Indonesia has become trending conversation on social media. Sentiment analysis can get public responds. Big data makes the problem time efficiency labeling process, therefore the lexicon dictionary is needed for the labeling process. Data is growing and circulating very rapidly so it takes a fast and efficient time. Although it is fast and makes it easier to solve problems, it is still necessary to question the accuracy produced when using the lexicon labeling. A comparison of the labeling process between the InSet lexicon and the VADER lexicon was conducted to determine the accuracy of the labeling. It was done by combining lexicon with machine learning method of support vector machine and TF-IDF weighting and accuracy result calculated using confusion marix. Data from social media X as many as 9117 lines and labeled with InSet lexicon result 5241 negative sentiments, 1369 positive, and 521 neutral. Then the labeling results with VADER produced 2749 positive, 2523 negative, and 1881 neutral. After labeled, processed SVM and calculated accuracy with results of InSet lexicon accuracy having an average of 85.8% while the VADER SVM lexicon has an average of 82.65%.
Co-Authors Aan Evian Nanda Achmad Zahrul Ali Zadan Agung Mustika Rizki Alfian Dorif Murtadlo Anggraini Puspita Sari Arif Widiasan Subagio Basuki Rahmat Eren Dio Sefrila Eva Yulia Puspaningrum Fetty Tri Anggraeny Firza Prima Aditiawan Joni Bastian Lintang Pramudya Anpurnan Made Hanindia Prami Swari Moch Firman hidayat Mochammad Yanuar Fitroni Muhammad Alfyando Muhammad Eko Prasetyo Muhammad Fernanda Naufal Fathoni Pratama Wirya Atmaja Rifki Riza Alfiansyah