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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Techno.Com: Jurnal Teknologi Informasi Jurnal Buana Informatika CESS (Journal of Computer Engineering, System and Science) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURIKOM (Jurnal Riset Komputer) Journal of Information Systems and Informatics Tematik : Jurnal Teknologi Informasi Komunikasi Walisongo Journal of Information Technology Jurnal Indonesia : Manajemen Informatika dan Komunikasi JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Ilmiah Teknologi dan Komputer (JITTER)
I Made Agus Dwi Suarjaya
Universitas Udayana
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science

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Esscore: An OCR-Based Android App for Scoring Short Handwritten Answer Using Levenshtein Distance Apriana, Krisna; I Made Agus Dwi Suarjaya; Ni Kadek Dwi Rusjayanthi
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9708

Abstract

Manual evaluation of short answer tests is time-consuming and prone to subjectivity. This study presents Esscore, an Android-based application that automates the scoring of handwritten short answers using EasyOCR and the Levenshtein Distance algorithm. EasyOCR extracts text from student answers image, while Levenshtein Distance measures similarity against predefined answer keys, allowing tolerance for varied correct responses. The system was tested on 350 student’s handwritten answers, achieving 95.7% accuracy. Functional testing using 14 black box scenarios showed all features operated correctly without failure. A usability test conducted with the SUS method produced a score of 76.5, rated “Good” with a grade “B” and an “Acceptable” acceptance level. The Net Promoter Score (NPS) placed the application in the “Passive” category. These results confirm Esscore as a functional, accurate, and user-friendly solution for automated answer scoring in educational environments.
Food Recipe Recommendation System with Content-Based Filtering and Collaborative Filtering Methods Widiantari, Ni Putu Triska; Suarjaya, I Made Agus Dwi; Rusjayanthi, Ni Kadek Dwi
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 3 (2025): Article Research July 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i3.14778

Abstract

Cooking your own food at home is a good step toward reducing fast food consumption. Fast food increases the risk of dangerous diseases. The diversity of recipe information available on the internet makes it difficult to choose recipes that match user preferences. Mobile technology can help with this by recommending recipes that better suit users' eating habits. This makes the transition to a healthier diet easier. Therefore, in this study, a recommendation system was developed that can recommend recipes based on the preferences of Android users. Two main recommendation methods are used in this study: content-based filtering and collaborative filtering. Using cosine similarity, a content-based recommendation system identifies the proximity between a recipe for food and its related context. The history of user comments on recipes serves as implicit feedback for the collaborative recommendation algorithm. This eliminates the need for explicit evaluations, such as ratings. This recommendation system generates recommendations in the form of the top ten food recipes with an evaluation matrix, referred to as NDCG@k and Hit-Ratio@k. The tests revealed that a content-based filtering technique may produce helpful recommendations, with the highest similarity score of 0.41 for the entry "chocolate cake that you can easily make at home." Meanwhile, in the collaborative filtering method using the Neural Collaborative Filtering (NCF) approach, the system shows consistent performance improvements, with the MAP@10 value increasing from 0.705 to 0.767 and the NDCG@10 from 0.78 to 0.83 after 10 training epochs. Keywords: Recommendation systems; content-based filtering; neural collaborative filtering; cosine similarity; implicit feedback
Analisis Sentimen Publik Terkait Kekerasan Seksual di Indonesia dengan Algoritma Naïve Bayes dan SVM Nalista, Ni Made Naila; Mandenni, Ni Made Ika Marini; Suarjaya, I Made Agus Dwi
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 3 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i3.8556

Abstract

Semakin meningkatnya kasus kekerasan seksual yang terjadi di Indonesia, dan media sosial merupakan ruang bagi masyarakat Indonesia untuk mengekspresikan pendapat. The increasing number of sexual violence cases in Indonesia, along with the role of social media as a space for the public to express their opinions, forms the basis for this research. The study aims to classify various types of public sentiment expressed on X (formerly Twitter) and Instagram comments by applying two algorithms for comparison: Naïve Bayes and SVM. Several processes carried out, including data collection from social media, data preprocessing, manual labeling, and the implementation of both algorithms on the processed dataset. The data sources utilized are posts written in Indonesian on X (Twitter) and Instagram, focusing on issues of sexual violence in Indonesia. The sentiment analysis results were grouped into three main categories: positive, negative, and neutral. The outcomes show that SVM achieved an accuracy of 82.17% using an 80:20 data split without applying GridSearch for optimization. The SVM results outperformed those of Naïve Bayes, which achieved an accuracy of 78.92%. This investigation leads to the conclusion that SVM is more optimal in analyzing public sentiment related to sexual violence in Indonesia compared to Naïve Bayes. The sentiment analysis results from social media regarding sexual violence in Indonesia show that the majority of sentiments are neutral, with the dataset being dominated by informative content, case reports without emotional expression, and off-topic comments
Smart Plug Socket with ESP-NOW and MQTT for Efficient Power Monitoring and Control via Android Dhananjaya, Anak Agung Ngurah Gede; Suarjaya, I Made Agus Dwi; Almantara, I Putu Sugi
JITTER: Jurnal Ilmiah Teknologi dan Komputer Vol. 6 No. 3 (2025): JITTER Vol.6, No.3, December 2025
Publisher : Program Studi Teknologi Informasi, Fakultas Teknik, Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Uncontrolled electricity usage and voltage fluctuations can damage electronic devices and lead to energy waste. This research designs a plug socket system capable of efficiently monitoring and controlling electricity consumption through an Android application. The system consists of two devices: a master and a slave, communicate using the ESP-NOW protocol without an internet connection, and connect to the Android app via MQTT. The slave device, equipped with a PZEM-004T sensor to monitor electrical parameters such as voltage, current, power, and energy. The system is designed to automatically cut off power if voltage fluctuations occur for more than one minute and to restore it when the voltage returns to normal. The Android application provides features such as relay control, scheduling, cost estimation, and historical data visualization for up to 45 days. Testing results shows the system functions well and assists users in monitoring and controlling electricity use more efficiently and safely.
Analisis Sentimen Masyarakat terhadap Tayangan Televisi Nasional menggunakan Metode Deep Learning Ferhati Bouchra; I Made Agus Dwi Suarjaya; Ni Kadek Dwi Rusjayanthi
Jurnal Buana Informatika Vol. 15 No. 2 (2024): Jurnal Buana Informatika, Volume 15, Nomor 02, Oktober 2024
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v15i2.9118

Abstract

Indonesia’s television industry faces fierce competition, particularly in chasing ratings and ad revenue. This has ultimately led to declining broadcast quality on some national TV stations. This research aims to understand perceptions towards content quality by focusing on public opinion through sentiment analysis of social media (Twitter) using Bi-LSTM and Word2Vec methods. The research involved data collection, preprocessing, vectorization, data splitting, model training and testing, evaluation to find the best model, sentiment data classification, and finally, sentiment data analysis. Using a dataset of 515,492 sentiment points, the model achieved an accuracy of 96.4%, precision of 72.1%, recall of 72.0%, and f1-score of 72.8%. Analysis of Twitter user sentiment leans towards neutral and positive perceptions. The results of the sentiment analysis of Twitter users tend to be neutral and positive. The results of the public satisfaction trend show a change in the pattern of public satisfaction with the quality of television station content.
Co-Authors A.A. Ketut Agung Cahyawan W Aditama, I Putu Dede Raditya Agus Kerta Nugraha, I Wayan Almantara, I Putu Sugi Anak Agung Ketut Agung Cahyawan Wiranatha Anak Agung Ketut Agung Cahyawan Wiranatha Apriana, Krisna Astuti, Ni Nyoman Indri Wika Ayu Krisnasari Ni Komang Ayu Wirdiani Ayu Wirdiani Bakkara, Kevin Christopher Bhagaskara, I Made Bagita Bouchra, Ferhati Cahyawan Wiranatha, Anak Agung Ketut Agung Candra, I Putu Wijaya Adi Danito, Philip Datar, Fandy Kusumaraditya Dewa Gede Kesuma Yoga Dextiro, Kadek Deksy Dhananjaya, Anak Agung Ngurah Gede Dharmawan, I Putu Yogi Prasetya Diatmika, Nyoman Gede Rayka Sedana Dwi Putra Githa Dwi Rusjayanthi, Dwi Efraim William Solang Eva Martina Sitorus Ferhati Bouchra G M Arya Sasmita Gede Widya Dharma Geovaldo, I Putu Hendra Gusti Agung Ayu Putri Gusti Agung Mayun Kukuh Jaluwana I Gusti Ngurah Bagus Picessa Kresna Mandala I Ketut Adi Purnawan I ketut Gede Darma Putra I Made Adhiarta Wikantyasa I Made Sukarsa I Made Sunia Raharja I Made Sunia Raharja, I Made Sunia I Nyoman Piarsa I Putu Agung Bayupati I Putu Agus Eka Pratama I Putu Arya Dharmaadi I Putu Wira Cahaya Pratama Yudha Ida Bagus Gde Dwipermana Sidhi Ida Bagus Kade Taruna Ida Bagus Nyoman Yoga Ligia Prapta Johan Tamin Kadek Suar Wibawa Ketut Mediana Ayu Candrayani Komang Arta Wibawa Krisnadinatha, I Gede Arya Kristina Kristina Luh Kade Devi Dwiyani Made Andika Verdiana Mahadiputra, Putu Gede Krisna Mahaputra, Putu Andre Mahayana, I Putu Gede Panji Badra Nalista, Ni Made Naila Narayana, I Putu Kevin Ari Ngeo Goa, Mario Valentino Ngurah Indra Purnayasa Ni Luh Ketut Inggitarahayu Anggasemara Ni Made Ika Marini Mandenni Ni Putu Ayu Widiari Ni Putu Viona Viandari Novenrodumetasa, Nathania nugraha, gemara adiyasa parahita Nugraha, Made Adhi Satrya Pande Nengah Purnawan Permana, Kadek Arya Putra Prabhaswara, Ilham Yoga Pratama , I Putu Agus Eka Pratama, I Putu Yoga pramesia Putu Adhika Dharmesta Putu Ratih Wulandari Putu Wira Buana Putu Yudha Yarcana Reyhan Todo Noer Yamin Ridho Hisbi Sulaiman Rusjayanthi, Ni Kadek Dwi Sadhaka, Anak Agung Istri Prabhaisvari Salsabila, Archels Ramadhany Saputra, Putu Alta Sari, Ni Kadek Ratna Sasmita, Gusti Made Arya Satriya, Rizki Dwi Savitri, Putu Rheya Ananda Setiawati, Putu Ayulia Shevira, Sheila Solang, Efraim William Susila, A.A Ngurah Hary Trisna, I Nyoman Prayana Vidya Chandradev Wayan Oger Vihikan, Wayan Oger Whurapsari, Gusti Ayu Wahyu Wiartha, I Gusti Made Diva Widia Widhiasih, Ni Putu Nirmala Dewi Widiantari, Ni Putu Triska Wiranatha, A.A. Ketut Agung Cahyawan Wiranatha, Anak Agung Ketut Agung Cahyawan Wiranatha, Anak Agung Ketut Cahyawan Wiratama, Bayu Adhya Zebedeus Cheyso