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All Journal Jurnal Ilmu Komputer (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana Jurnal Ilmiah Kursor JOIV : International Journal on Informatics Visualization Specta Journal of Technology Jurnal Pengabdian Informatika (JUPITA) Jurnal Nasional Teknologi Informasi dan Aplikasinya
I Made Widiartha
Universitas Udayana
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Other

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IMPLEMENTASI METODE DESIGN THINKING DAN PRINSIP GESTALT PADA RANCANG BANGUN DASHBOARD SMART-FARM Alvin Wiraprathama; I Made Widiartha; I Ketut Gede Suhartana; I Gusti Agung Gede Arya Kadyanan
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 13 No 1 (2024): JELIKU Volume 13 No 1, August 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Bali's agricultural sector experienced a notable downturn in growth during 2022 compared to the preceding year, which had seen substantial expansion. One of the key factors behind this decline was the limited adoption of digital farming practices in Bali. This underutilization of digital technologies in agriculture, including tools for crop monitoring, soil analysis, weather prediction, and market connectivity, likely contributed to decreased productivity and efficiency in farming activities. Addressing this issue could be pivotal for Bali to rejuvenate its agriculture sector and foster growth moving forward. To tackle this challenge, a smart farming dashboard has been developed specifically to address the needs of farmers in Bali. This dashboard boasts a user-friendly interface design and incorporates features tailored to assist farmers in Bali. The dashboard was crafted through the application of design thinking methodology, integrating Gestalt principles to optimize the user interface. The results of the dashboard's usability testing, as measured by the System Usability Scale (SUS), indicate a strong performance with a score of 79.75, reflecting its excellent usability.
Multi-Document Summarization Using Tuna Swarm Optimization and Markov Clustering Widiartha, I Made; Hartati, Rukmi Sari; Wiharta, Dewa Made; Sastra, Nyoman Putra; Astuti, Luh Gede
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.3365

Abstract

The Internet contains a large number of documents from various sources with similar content. The contents of documents that are almost identical will lead to news redundancy, making it difficult for readers to distinguish between factual information and opinions. Multi-document summarization has been designed to enable readers to easily understand the meaning of news documents without needing to read multiple documents. Multi-document summarization aims to extract information from several texts written about the same topic. The resulting summary report enables users to obtain a single piece of information from multiple similar pieces of information sourced from various locations. Various approaches have been used in creating multi-document summaries. Issues regarding accuracy and redundancy are still a significant focus of research. In this paper, a new multi-document summarization model was built using Tuna Swarm Optimization (TSO) and Markov Clustering (MCL) methods. The dataset of this research is Indonesian language news from various online media sources. Based on hyperparameter tuning using training data, the best TSO model performance was obtained at variable values a = 0.7, z = 0.9, and the optimal number of tuna fish > 80. From the research results, it was found that TSO outperformed other swarm intelligence methods. The use of MCL has proven to be effective, as evidenced by the performance results, where TSO achieved an average ROUGE value 7.95% higher when MCL was applied. In this performance test, four standard evaluation metrics of the ROUGE toolkit were used.
SISTEM DROPSHIP BERBASIS WEBSITE PADA CV. EFINDO Anggotra, Puspadevi; Muliantara, Agus; Widiartha, I Made
Jurnal Pengabdian Informatika Vol. 2 No. 2 (2024): JUPITA Volume 2 Nomor 2, Februari 2024
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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Abstract

Dropship adalah mekanisme yang memungkinkan seseorang untuk menjual produk pihak lain tanpa harus membelinya terlebih dahulu. Saat ini, dropship marak dilakukan pada berbagai jenis marketplace dan e-commerce, seperti Shopee, Tokopedia, Lazada, dan lain sebagainya. Sistem dropship diusulkan untuk menyelesaikan keluhan para reseller yang belum memiliki modal namun ingin masih ingin berjualan. Dropship dianggap sebagai usaha yang minim modal karena tidak perlu mengeluarkan modal untuk membeli stok produk secara fisik. Sistem ini berhasil menyelesaikan masalah yang ada pada CV. Efindo dan juga membantu untuk mempermudah pemasaran produk.
LANDING PAGE BERBASIS WEBSITE UNTUK MENINGKATKAN PELAYANAN KONSUMEN DI PT PRATHAMA LAND PROPERTY Wiraprathama, Alvin; Widiartha, I Made; Muliantara, Agus
Jurnal Pengabdian Informatika Vol. 2 No. 3 (2024): JUPITA Volume 2 Nomor 3, Mei 2024
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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Abstract

Pemasaran digital sangat penting bagi PT Prathama Land Properti, perusahaan yang bergerak di penjualan properti tanah di Kabupaten Malang. Saat ini, perusahaan hanya menggunakan penyebaran pamflet digital dan iklan di marketplace sebagai strategi pemasaran digital. Namun, hal ini tidak cukup untuk membangun branding yang kuat dan kredibilitas yang tinggi di mata konsumen. Untuk mengatasi hal tersebut, perlu dilakukan program "Sosialisasi Pengembangan Website Landing Page" yang bertujuan meningkatkan strategi pemasaran digital perusahaan. Program ini akan membekali staf perusahaan dengan pengetahuan dan keterampilan dalam menggunakan halaman landing sebagai strategi baru pemasaran digital. Dengan menggunakan landing page, PT Prathama Land Properti dapat menarik calon konsumen, meningkatkan layanan konsumen, dan memperkuat branding perusahaan. Program ini diharapkan dapat meningkatkan efektivitas pemasaran digital dan memberikan manfaat jangka panjang bagi PT Prathama Land Properti
Optimasi Metode Support Vector Machine (SVM) Mengunakan Particle Swarm Optimization pada Permasalahan Klasifikasi Diabetes Anak Agung Gde Agung Pranandita; I Made Widiartha
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 4 (2025): JNATIA Vol. 3, No. 4, Agustus 2025
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2025.v03.i04.p18

Abstract

Diabetes mellitus is a chronic disease that requires accurate early detection. This study presents a diabetes classification system by integrating Support Vector Machine (SVM) with Particle Swarm Optimization (PSO) to automatically optimize model parameters. The dataset used was obtained from Kaggle, consisting of 100,000 entries and nine medical attributes. Data preprocessing included cleaning, encoding, Min-Max normalization, and undersampling to balance class distribution. Model performance was evaluated using 5-Fold Cross Validation. The results showed that the SVM- PSO achieved an average accuracy of 83.60% which is higher than the conventional SVM with 83.39% accuracy. These findings demonstrate that PSO effectively enhances the classification performance of SVM and is recommended for machine learning-based medical diagnosis, especially in diabetes prediction.
Analisis Sentimen Kebijakan Insentif Mobil Listrik Menggunakan TF-IDF dan Naïve Bayes Yande Pramana Yustika Pradeva; I Made Widiartha; I Putu Satwika
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 1 (2025): JNATIA Vol. 4, No. 1, November 2025
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2025.v04.i01.p20

Abstract

This study aims to analyze public sentiment regarding the Indonesian government’s electric vehicle (EV) incentive policy using YouTube comments as the data source. The research applies text preprocessing steps including cleaning, normalization, stopword removal, tokenization, and stemming to prepare the textual data. The cleaned data is transformed into numerical representation using the Term Frequency-Inverse Document Frequency (TF-IDF) method and classified using the Multinomial Naïve Bayes algorithm. To address class imbalance in the dataset, Synthetic Minority Over-sampling Techique (SMOTE) is applied. The model evaluation metrics include accuracy, precision, recall, and F1-score. Based on the evaluation, the model achieves an accuracy of 71%. The model performs better in classifying negative comments, as shown by a higher recall and F1-score in the negative class compared to the positive class. These findings indicate that public responses to the EV incentive policy tend to be more critical. This study provides insights into public opinion that can serve as a valuable reference for policymakers in designing more effective and well-communicated incentive strategies for promoting electric vehicle adoption in Indonesia.
Implementasi LexRank dan BERT2GPT dalam Auto Summarization Teks Bahasa Indonesia Tristan Bey Kusuma; I Made Widiartha; I Putu Gede Hendra Suputra
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 1 (2025): JNATIA Vol. 4, No. 1, November 2025
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2025.v04.i01.p03

Abstract

In Indonesia, with the rapid growth of internet and social media usage, the amount of information produced in the Indonesian language has reached significant levels. This creates challenges in managing and understanding this information quickly and efficiently. Text summarization has emerged as a potential solution to help users organize and summarize information, enabling easier and more efficient access to relevant content. This study discusses the development of an Indonesian text summarization model using the LexRank algorithm. The results show that this model can produce accurate and concise summaries, with ROUGE-L result of 0.91 and also a ROUGE-1 result of 0.31. Developing an Indonesian text summarization model is important because it can help users manage and understand information quickly and efficiently. This study provides a positive contribution to the development of Indonesian text summarization models, by providing evidence that the LexRank model can produce accurate and concise summaries.
Co-Authors A A I N Karyawati Agus Muliantara Agus Zainal Arifin Alit Indrawan, I Gusti Ngurah Alvin Wiraprathama Anak Agung Gde Agung Pranandita Anak Agung Istri Ngurah Eka Karyawati Anggotra, Puspadevi Anny Yuniarti Apsari, Made Sri Ayu Ari Mogi, I Komang Arsa, Dewa Made Sri Astawa, Ni Wayan Amanda Putri Atmojo, Firman Ali Eka Ayu Nikki Asvikarani bratha, dede khausa bayu Darlis Herumurti Dewa Made Wiharta Firman Ali Eka Atmojo Gede Agung Aji Andar Sakti Gede Wisnu Bhaudhayana Gilang Indrawan, Muhammad Caesar Giri, I Nyoman Yusha Tresnatama Gst. Ayu Vida Mastrika Giri Humaira, Fitrah Maharani Humaira, Fitrah Maharani I Dewa Made Bayu Atmaja Darmawan, I Dewa Made Bayu I Gede Arta Wibawa I Gede Santi Astawa I Gusti Agung Gede Arya Kadyanan I Gusti Ngurah Anom Cahyadi Putra I Kadek Aldy Oka Ardita I Ketut Gede Suhartana I Made Eko Satria Wiguna I Made Nusa Yudiskara I Made Satria Bimantara I Putu Bayu Eka Pratama I Putu Gede Hendra Suputra I Putu Satwika I WAYAN SANTIYASA I Wayan Sugiana I Wayan Supriana Ida Bagus Gede Dwidasmara Ida Bagus Gede Dwidasmara Ida Bagus Made Mahendra Julianti, Syelvia Kadek Nanda Banyu Permana Ketut Ardha Chandra Kusuma, Putu Agus Dharma Luh Arida Ayu Rahning Putri Luh Gede Astuti Luh Gede Astuti Nathanael Richie Thomas Ngurah Agus Sanjaya ER Ni Made Elvina Aryadhika Putri Nyoman Putra Sastra Octavia, Hana Christine Panji Palguna, I Gusti Agung Ngurah Pijar Candra Mahatagandha Pramana, I Gst Bgs Bayu Adi PRATIWI, NI MADE DINDA Priandana, Bhisma Satwika Ari Purba, Kevin Joel Putra, I Gusti Ngurah Agung Widiaksa Raharja, Made Agung Ramadhan, Zhaqy Hikkammi Gullam Rukmi Sari Hartati Ryan, Ida Bagus Putu Saiful Bahri Musa Satria Wiguna, I Made Eko Satya, I Dewa Gede Rama Sitinjak, Anugrah Ignatius Tegar Palyus Fiqar Tristan Bey Kusuma Widnyana, I Kadek Agus Candra Wijaya, Partha Wikardiyan, Aditya Wiraprathama, Alvin Yande Pramana Yustika Pradeva