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All Journal Jurnal Ilmu Komputer Buletin Udayana Mengabdi (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana Jurnal Sains dan Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer WIDYA LAKSANA Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Pengabdian Informatika (JUPITA) Jurnal Intelek Dan Cendikiawan Nusantara Buletin Pos dan Telekomunikasi Jurnal Nasional Teknologi Informasi dan Aplikasinya
I Gusti Agung Gede Arya Kadyanan
Faculty Of Computer Science University Of Indonesia
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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SISTEM ANALISIS SENTIMEN ULASAN PENGUNJUNG BERBASIS WEBSITE UNTUK MANAJEMEN REPUTASI PROPERTI I Made Sudarsana Taksa Wibawa; Anak Agung Istri Ngurah Eka Karyawati; I Gusti Agung Gede Arya Kadyanan
Jurnal Pengabdian Informatika Vol. 4 No. 1 (2025): JUPITA Volume 4 Nomor 1, November 2025
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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Abstract

Sistem Analisis Sentimen Ulasan Pengunjung berbasis website merupakan teknologi inovatif yang memanfaatkan pemrosesan bahasa alami untuk mengidentifikasi dan menganalisis sentimen dari ulasan pengunjung di berbagai platform online. Dalam konteks perkembangan pesat properti hospitality di wilayah wisata seperti Gianyar, Bali, pengelola properti menghadapi tantangan dalam mengelola ulasan pengunjung yang tersebar luas. Masalah utama adalah bagaimana mengumpulkan dan menganalisis data ulasan secara efisien untuk memperoleh wawasan yang berguna dalam pengambilan keputusan strategis. Solusi yang diusulkan adalah pengembangan aplikasi berbasis website yang mengintegrasikan ulasan dari berbagai platform ke dalam satu dashboard terpadu. Aplikasi ini menggunakan metode Web Scraping untuk mengumpulkan data ulasan dan Natural Language Processing (NLP) untuk menganalisis sentimen dari setiap ulasan, baik positif, negatif, maupun netral. Hasil analisis ditampilkan dalam bentuk statistik yang mudah dipahami, membantu pengelola properti dalam mengambil keputusan yang lebih tepat, seperti peningkatan kualitas layanan atau pengembangan fasilitas baru. Implementasi sistem ini telah menunjukkan bahwa aplikasi mampu memberikan informasi sentimen yang akurat dan bermanfaat bagi pengelola properti. Namun, terdapat tantangan seperti ambiguitas dalam analisis sentimen dan keterbatasan pengumpulan data dari platform tertentu. Dengan demikian, diharapkan sistem ini dapat memberikan kontribusi signifikan dalam meningkatkan kepuasan pengunjung dan kesuksesan operasional properti hospitality.
PERANCANGAN DESAIN USER INTERFACE DAN PENGALAMAN PENGGUNA PADA WEBSITE KANTOR PERBEKEL DESA SANUR KAJA Yudistia, I Komang Maheza Yudistia; I Gusti Ngurah Anom Cahyadi Putra; I Gusti Agung Gede Arya Kadyanan
Jurnal Pengabdian Informatika Vol. 4 No. 2 (2026): JUPITA Volume 4 Nomor 2, Februari 2026
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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Abstract

Di era digital, desain UI/UX memainkan peran penting dalam pengembangan website yang berfungsi untuk meningkatkan interaksi dan partisipasi masyarakat dalam layanan publik online. Penelitian ini bertujuan untuk merancang desain UI/UX yang responsif dan user-friendly untuk website Kantor Perbekel Desa Sanur Kaja. Teknologi yang digunakan meliputi perangkat lunak Figma untuk pembuatan wireframe dan prototipe interaktif, serta penerapan prinsip-prinsip desain heuristik dan responsive design dalam proses evaluasi. Meskipun tidak dilakukan pengujian kuisioner secara langsung, evaluasi UX dilakukan secara internal berdasarkan prinsip desain UI/UX dan dilengkapi dengan masukan dari perangkat desa selama kegiatan praktik kerja lapangan. Hasil evaluasi menunjukkan bahwa desain yang dirancang mampu memenuhi ekspektasi pengguna dari sisi kemudahan navigasi, konsistensi visual, dan kesesuaian dengan kebutuhan layanan digital desa. Dokumentasi desain yang lengkap juga memudahkan proses implementasi oleh pengembang. Kesimpulannya, penerapan desain UI/UX yang efektif dapat memberikan dampak positif terhadap aksesibilitas dan efisiensi layanan publik di tingkat desa.
Perancangan dan Pembangunan Sistem Informasi Company Profile Berbasis Web dengan Teknologi HTML dan CSS Pada PT. Ayu Abdi Lestari Surya, Dheva; Cokorda Rai Pramartha; I Gusti Agung Gede Arya Kadyanan
Jurnal Pengabdian Informatika Vol. 4 No. 1 (2025): JUPITA Volume 4 Nomor 1, November 2025
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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Era digitalisasi menuntut perusahaan memiliki kehadiran online untuk meningkatkan brand awareness dan kredibilitas. Penelitian ini bertujuan merancang website company profile responsif menggunakan HTML, CSS, dan JavaScript. Metodologi menggunakan SDLC dengan pendekatan waterfall meliputi analisis kebutuhan, desain, implementasi, dan testing. HTML untuk struktur konten, CSS untuk styling. Testing menggunakan black box dan usability testing. Website menghasilkan fitur: halaman beranda dengan navigasi intuitif, profil perusahaan lengkap, galeri produk, portofolio, form kontak, dan dashboard admin. Implementasi responsive design untuk desktop, tablet, mobile dengan loading time 2.3 detik, kompatibilitas 100% browser modern, skor usability 4.2/5.0. Teknologi HTML, CSSefektif menghasilkan website responsif dan interaktif. Sistem memenuhi kebutuhan fungsional dengan kepuasan pengguna tinggi, meningkatkan professional image perusahaan sebagai platform digital marketing efektif. Penelitian memberikan kontribusi template adaptabel untuk UMKM dalam pengembangan website cost-efficient.
Perancangan UI/UX Aplikasi Wisata Dengan Metode User Centered Design Sang Ayu Putu Eka Trisna Andriani; I Gusti Agung Gede Arya Kadyanan
Jurnal Intelek Dan Cendikiawan Nusantara Vol. 3 No. 01 (2026): Februari - Maret 2026
Publisher : PT. Intelek Cendikiawan Nusantara

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Abstract

Bangli memiliki beragam destinasi wisata yang mampu menarik minat wisatawan domestik dan internasional. Namun, pengembangan potensi pariwisata di Bangli masih menghadapi beberapa kendala, salah satunya adalah terbatasnya akses informasi tentang destinasi wisata dan kurangnya koordinasi optimal antara wisatawan dan pihak terkait, seperti pengelola objek wisata dan penyedia jasa pariwisata. Untuk mengatasi masalah ini, aplikasi Mai Bangli dirancang menggunakan metode User Centered Design (UCD). Studi ini bertujuan untuk meningkatkan kenyamanan dan kepuasan pengguna dalam menggunakan aplikasi Mai Bangli dan mendorong minat wisatawan untuk mengunjungi Bangli. Hasil penelitian menunjukkan bahwa desain User Interface (UI) dan User Experience (UX) yang dikembangkan telah diuji menggunakan metode System Usability Scale (SUS) dan Single Ease Question (SEQ) dan memperoleh skor akhir 80,75, yang menunjukkan tingkat penerimaan yang baik oleh pengguna.
Klasifikasi Citra Jamur Menggunakan SVM dengan PCA Berbasis Ekstraksi Fitur Hibrida I Putu Andika Arsana Putra; I Gusti Agung Gede Arya Kadyanan
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
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.2026.v04.i02.p02

Abstract

The general public still faces significant difficulty in differentiating between poisonous and non-poisonous mushrooms due to their high visual similarity. This has led to numerous poisoning incidents due to consumption of poisonous mushrooms. Between 2010 and 2020, there were 76 reported cases of poisoning involving 550 victims, 9 of whom died. To address this issue, a classification model was developed to differentiate between poisonous and non-poisonous mushrooms using Support Vector Machine (SVM) and Principal Component Analysis (PCA) algorithms based on hybrid feature extraction. The dataset for this study was obtained from Kaggle. The model built using PCA saw an increase in the model training time to 3 minutes 32 seconds from the initial 16 minutes 4 seconds without using PCA. Hyperparameter tuning was performed to find the best combination of parameters, resulting in RBF kernel, C value of 10, and gamma set to scale. The model was evaluated using a confusion matrix to determine accuracy and class-specific metrics. The model performed well, achieving 85% accuracy on the test data.  
Perbandingan Random Forest, Decision Tree, Gradient Boosting, Logistic Regression untuk Klasifikasi Penyakit Jantung I Made Krisna Dwipa Jaya; I Gusti Agung Gede Arya Kadyanan
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 1 (2023): JNATIA Vol. 2, No. 1, November 2023
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.2023.v02.i01.p08

Abstract

Heart disease is a condition characterized by disorders affecting the heart. These heart disorders include infections, abnormalities in heart valves, blockages in the heart's blood vessels, irregular heartbeats, and so on. According to a report by the World Health Organization (WHO) in 2019, approximately 17.9 million people died from cardiovascular diseases, with 85% of them attributed to heart attacks and strokes. The shortage of doctors and specialists can lead to negligence and the overlooking of patients' symptoms, which can result in disabilities or even death for the patients. Therefore, the need for an expert system arises, which can be utilized as a tool to classify or detect heart diseases based on patients' medical records. Based on the results of the conducted research, random forest is a fairly effective algorithm for classifying heart diseases, with a recall value of 80.6% and ROC AUC of 76.3%. 
Implementasi Random Forest pada Klasifikasi Penyakit Kardiovaskular dengan Hyperparameter Tuning Grid Search I Ketut Adian Jayaditya; I Gusti Agung Gede Arya Kadyanan
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 1 (2023): JNATIA Vol. 2, No. 1, November 2023
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.2023.v02.i01.p25

Abstract

Cardiovascular disease has the potential to cause death if not treated right, because it interferes with the function of the heart. Machine Learning algorithm can be used to do early diagnosis of cardiovascular disease to lower the risk of death. In this study, the classification of cardiovascular disease uses the Random Forest algorithm to determine whether a person has cardiovascular disease or not. Grid Search is also used to do hyperparameter tuning to find the optimal hyperparameter for the Random Forest algorithm. The performance results of the classification model using Random Forest with Grid Search are 73.06% in accuracy, 75.15% in precision, 68.72% in recall, and 71.79% in f1-score. 
Chatbot Pelayanan Informasi Kampus Detriasmita Saientisna; I Gusti Agung Gede Arya Kadyanan; Ida Bagus Made Mahendra; V. G. A. Pradika
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 1 (2023): JNATIA Vol. 2, No. 1, November 2023
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.2023.v02.i01.p29

Abstract

As technology advances in the world of education, information about campuses becomes very important. Searching for information that is fast, precise, and easy is needed for prospective students, university students, other campus residents, and the public. Chatbots are the solution of choice because of their popularity. The use of chatbots is useful in finding information about campuses quickly and easily, where users no longer need to browse every website or go to campus officials to find out information. This chatbot can provide basic information about the services provided by the campus, information on study programs, faculties, and even campus officials. 
Penggunaan Algoritma C4.5 dan Random Forest guna Meningkatkan Efisiensi Klasifikasi Penyakit Stroke I Agus Indra Dipta Prayoga; I Gusti Agung Gede Arya Kadyanan
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 3 (2025): JNATIA Vol. 3, No. 3, Mei 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.i03.p09

Abstract

Stroke is a very serious problem throughout the world. According to a report from the World Heart Organization (WHO), in 2022, more than 12.2 million, or one in four people aged 25 years will experience a stroke, and more than 7.6 million new stroke sufferers every year throughout the world. An irregular lifestyle is the main cause of someone having a stroke. Therefore, we need a system that can be used as a stroke classification or detection tool based on a person's disease history. The stroke disease data used in this study was obtained through Kaggle with a total of 5110 data. Based on the results of research that has been carried out using two algorithm models, namely the C4.5 algorithm and Random Forest. A combination of these two algorithms has been obtained which produces a stroke classification system with fairly good accuracy, with an accuracy value of 92.4%. 
Analisis Prediktif Bitcoin dengan Metode SVM serta Pembobotan TIF-IDF Berbasis Data Narrative Danendra Darmawansyah; I Gusti Agung Gede Arya Kadyanan
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 1 (2024): JNATIA Vol. 3, No. 1, November 2024
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.2024.v03.i01.p10

Abstract

The cryptocurrency market has experienced significant volatility in recent years, making it challenging for investors to make informed decisions. This study aims to develop a predictive model for cryptocurrency price increases using TF-IDF (Term Frequency-Inverse Document Frequency) and SVM (Support Vector Machine) based on narrative data. Narrative data, such as news articles and social media posts, can provide valuable insights into investor sentiment and market trends. The proposed model extracts relevant features from narrative data using TF-IDF and employs SVM to classify cryptocurrency price movements into positive, negative, or neutral categories. Experimental results demonstrate the effectiveness of the proposed model in predicting cryptocurrency price increases, with an accuracy of over 70%. The findings suggest that narrative data can be a valuable source of information for cryptocurrency price prediction and that TF-IDF and SVM are effective methods for analyzing narrative data. 
Co-Authors Aditya Premana Putra Affila Pradika, Valentin Gea Agus Muliantara Alim Ikegami Alvin Wiraprathama Anak Agung Istri Ngurah Eka Karyawati Anak Agung Istri Ngurah Eka Karyawati Anggara Putra, I Wayan Aditya Aniati Murni Arymurthy Artanta Wibawa, Putu Widyantara Benny Elia Brahmantha, Gede Putra Aditya Cokorda Pramartha Cokorda Pramartha Cokorda Rai Pramartha Danendra Darmawansyah Darmayasa, I Nengah Oka Detriasmita Saientisna Dewi, Ni Wayan Sani Utari Dharmajaya, Gede Putra Dwipa Jaya, I Made Krisna Gde Deva Dimastawan Saputra Gede Krisnawa Sandhya Wandhana Gede Sukadarmika Gorianto, Frisca Olivia Hanif, Muhammad Hanif I Agus Indra Dipta Prayoga I Dewa Made Bayu Atmaja Darmawan I Dewa Made Bayu Atmaja Darmawan, I Dewa Made Bayu I Gede Adrian Satria Pratama S. I Gede Angga Narotama I Gede Arta Wibawa I Gede Made Sankhya Saiyoga Krisna I Gede Santi Astawa I Gede Tendi Ariyanto I Gusti Ngurah Anom Cahyadi Putra I Gusti Ngurah Made Dika Varuna I Ketut Adian Jayaditya I Ketut Gede Suhartana I Ketut Gede Suhartana I Ketut Kusuma Merdana I Ketut Manik Ambarawan I Ketut Teguh Wibawa Lessmana Putra. T I Komang Roni Sudarmawan I Komang Surya Adinandika I Komang Tryana Mertayasa I Made Adi Susilayasa I Made Anditya Mahesastra I Made Krisna Dwipa Jaya I Made Paramadhika Dwi Putra I Made Suastika I Made Sudarsana Taksa Wibawa I Made Wasanta Bhaskara I Made Widhi Wirawan I Made Widiartha I Nyoman Gunantara I Putu Andika Arsana Putra I Putu Fajar Tapa Mahendra I Putu Gede Hendra Suputra I Putu Yoga Laksana Putra I WAYAN SANTIYASA I Wayan Supriana I Wayan Trisna Wahyudi I.B.M. Mahendra I.M. Widiartha Ida Bagus Gagananta Amartya Ida Bagus Gede Dwidasmara Ida Bagus Gede Dwidasmara Ida Bagus Made Mahendra Ida Bagus Made Mahendra Ida Bagus Wahyu Semara Kamajaya Jayaditya, I Ketut Adian Kadek Bakti Pramanayoga St Kurniawan, Darryl Patrick Matheuw Luh Arida Ayu Rahning Putri Luh Gede Astuti Luh Gede Ayu Candrawati Made Yayang Eka Prananda Manuaba, Ida Bagus Gede Marselinus Putu Harry Setyawan Ngurah Agus Sanjaya ER Ni Made Ary Esta Dewi Wirastuti Parmawati, Putu Yuki Pradika, V.G.A. Putra, I Gusti Ngurah Agung Widiaksa Putra, I Putu Yoga Laksana Putra, Putu Mas Anggita Putra. T, I Ketut Teguh Wibawa Lessmana Putu Praba Santika Putu Yuki Parmawati Rizky, Muhammad Firyanul Sagung Putri Nariswari Saientisna, Detriasmita Sang Ayu Putu Eka Trisna Andriani Saputra, Komang Oka Saputra, Made Yosfin Sudarmawan, I Komang Roni Suputra, I Nengah Aryadi Surya, Dheva Theresia Margaretha Purba V. G. A. Pradika Valentin Gea Affila Pradika Wahyudi - Widiastawan, Gede Yasa, I Ketut Gede Udha Krisna Yudistia, I Komang Maheza Yudistia