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All Journal Jurnal Ilmu Komputer (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana Semantik Jurnal Buana Informatika Jurnal RESISTOR (Rekayasa Sistem Komputer) Jurnal Pengabdian Informatika (JUPITA) Jurnal Nasional Teknologi Informasi dan Aplikasinya
Luh Arida Ayu Rahning Putri
Universitas Udayana
Humanities Computer Science & IT Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Other

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PENGEMBANGAN FRONT-END APLIKASI INFORMASI BERBASIS WEBSITE DI SMK NEGERI 1 TABANAN I Gusti Ngurah Febri Ananda Krisna; Anak Agung Istri Ngurah Eka Karyawati; Luh Arida Ayu Rahning Putri
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

Penelitian ini bertujuan untuk mengembangkan dan mengimplementasikan aplikasi informasi berbasis website di SMK Negeri 1 Tabanan yang fokus pada informasi fasilitas, ekstrakurikuler, dan jurusan yang tersedia di sekolah. Aplikasi ini dirancang untuk memudahkan siswa, guru, orang tua, dan masyarakat terkait dalam mendapatkan informasi terkait fasilitas sekolah, kegiatan ekstrakurikuler, dan jurusan yang ditawarkan Pengembangan aplikasi menggunakan model waterfall dengan menggunakan bahasa pemrograman dan teknologi web yang sesuai. Fitur-fitur yang disediakan dalam aplikasi ini mencakup informasi lengkap mengenai fasilitas yang ada di sekolah, daftar ekstrakurikuler yang dapat diikuti oleh siswa, serta informasi tentang jurusan-jurusan yang tersedia dan deskripsi singkatnya. Aplikasi ini memberikan kemudahan akses informasi, sehingga pengguna dapat dengan cepat mendapatkan informasi yang dibutuhkan.Hasil pengujian menunjukkan bahwa aplikasi informasi berbasis website ini berjalan dengan baik dan memberikan manfaat yang signifikan dalam memperoleh informasi terkait fasilitas, ekstrakurikuler, dan jurusan di SMK Negeri 1 Tabanan. Diharapkan aplikasi ini dapat meningkatkan efisiensi dan efektivitas dalam penyampaian informasi kepada semua pihak yang terkait. Pengembangan aplikasi serupa juga dapat diterapkan di sekolah-sekolah lain untuk meningkatkan aksesibilitas informasi dan memperkuat komunikasi di antara semua stakeholder pendidikan
PEMBUATAN APLIKASI WEBSITE SMARTCARE PARENTING SOLUTION DI PT TAKSU TEKNOLOGI INDONESIA I Dewa Agung Adwitya Prawangsa; Anak Agung Istri Ngurah Eka Karyawati; Luh Arida Ayu Rahning Putri
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

PT Taksu Teknologi Indonesia merupakan perusahaan teknologi yang berlokasi di Bali. Dalam program pengabdian kepada masyarakat, penulis melakukan kegiatan pengabdian di PT Taksu Teknologi Indonesia dengan fokus pada penerapan SmartCare Parenting Solution. SmartCare Parenting Solution adalah aplikasi website yang dibangun menggunakan React JS. Aplikasi ini menyediakan fitur untuk menambahkan profil anak dengan mengisi biodata dan survei perkembangan. Selanjutnya, sistem akan memonitor pertumbuhan dan perkembangan anak berdasarkan dataset yang diambil dari WHO Multicentre Growth Reference Study (MGRS). Hasil monitoring akan memberikan feedback pertumbuhan anak kepada pengguna. Tujuan kegiatan ini adalah meningkatkan pemahaman dan penggunaan aplikasi ini secara berkala oleh orang tua untuk mendapatkan hasil yang memuaskan dalam pengasuhan anak. Dalam upaya menjaga keberlanjutan program, penulis merekomendasikan perbaikan dan pengembangan fitur berdasarkan evaluasi hasil kegiatan serta menjalin kolaborasi dengan mitra terkait. Diharapkan kegiatan ini memberikan manfaat jangka panjang dalam meningkatkan kualitas pengasuhan anak oleh orang tua.
Analisis Kinerja XGBoost Menggunakan Bayesian Optimization dalam Prediksi Harga Ethereum Christian Valentino; Luh Arida Ayu Rahning Putri
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.p09

Abstract

Cryptocurrency is a digital innovation in the financial sector that has revolutionized the global transaction system through blockchain technology. One of the main challenges in the crypto domain today is determining the price of cryptocurrencies, which are highly volatile. Ethereum, one of the largest cryptocurrencies, exhibits complex volatility patterns that require a robust predictive system. This study aims to compare the performance of the standard XGBoost algorithm with XGBoost optimized using Bayesian Optimization in predicting daily Ethereum prices based on time series data from 2016 to June 2025. The dataset includes price-related features such as open, high, low, volume, and percentage price change. The modeling process consists of several stages including feature engineering, time series-based data splitting, and model training. Model performance was evaluated using three primary metrics: MAE, RMSE, and R² Score. The evaluation results show that the standard XGBoost model achieved an MAE of 80.8926 (3.12%), RMSE of 114.1457 (4.40%), and an R² Score of 0.9723. Meanwhile, the optimized model using Bayesian Optimization achieved an MAE of 70.7241 (2.73%), RMSE of 102.5334 (3.96%), and an R² Score of 0.9777. These results indicate that Bayesian Optimization helps improve the model's prediction accuracy. This study concludes that the XGBoost model with a Bayesian optimization approach yields superior and more effective performance in forecasting Ethereum prices based on time series data.
Analisis Sentimen Ulasan Aplikasi Loklok Menggunakan Metode Support Vector Machine (SVM) I Gusti Ngurah Adhiwangsa Devananda; Luh Arida Ayu Rahning Putri; I Komang Arya Ganda Wiguna
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.p09

Abstract

Rapid advances in digital technology have led to an increase in the amount of text data available online, including user reviews of mobile applications. The Loklok application, as a popular entertainment platform, is one source of review data that is rich in user opinions. This research focuses on performing sentiment analysis on user reviews of the Loklok application by employing the Support Vector Machine (SVM) algorithm alongside the Term Frequency-Inverse Document Frequency (TF-IDF) method for feature extraction. The review dataset was sourced from the Kaggle platform and underwent several text preprocessing steps, including data cleaning, tokenization, stopword elimination, and stemming. The evaluation results indicate that the SVM model, combined with TF-IDF, achieved an accuracy of 86%, a precision of 88%, a recall of 86%, and an F1-score of 87%. Classification performance tends to be better for positive sentiment classes compared to negative ones, due to data imbalance. This finding demonstrates that the combination of TF-IDF and SVM methods is effective in classifying user review sentiment and can serve as a foundation for decision-making in the development of digital applications.
Klasifikasi Customer Churn Menggunakan XGBoost dengan Optimasi GridSearchCV Berbasis Shapley Additive Explanations I Gusti Ayu Riyana Astarani; Luh Arida Ayu Rahning Putri
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.p01

Abstract

Customer churn is a significant challenge in the banking sector, often leading to revenue loss and requiring predictive strategies to enhance customer retention. This study implements the Extreme Gradient Boosting (XGBoost) algorithm for churn classification, with hyperparameter optimization using the GridSearchCV technique to improve model performance. The dataset comprises 10,000 banking customers with 9 features and 1 target label. To address class imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied. Prior to tuning, the XGBoost model achieved an accuracy of 80.8%. After applying optimal parameters, the model's performance improved to 81.5%, along with higher precision and recall values, indicating improved robustness and consistency. For model interpretability, Shapley Additive Explanations (SHAP) were used and visualized through a beeswarm Plot. The analysis identified age, customer activity status, and number of products owned as the most influential features in predicting churn. Based on these findings, this study proposes business recommendations including age-based customer segmentation, enhancing active customer engagement, and optimizing product offerings as strategies to reduce churn.
Pengembangan Aplikasi Manajemen Proyek Berbasis Web di PT Guna Teknologi Nusantara (R.E.D System) Culio, Shelomita Putrinda; Luh Gede Astuti; Luh Arida Ayu Rahning Putri
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

Kebutuhan akan manajemen proyek yang efektif semakin mendesak pada era digital, terutama untuk perusahaan yang menangani banyak proyek, seperti PT Guna Teknologi Nusantara dengan lebih dari 200 klien. Untuk membantu dalam pemantauan dan koordinasi proyek, dikembangkan sebuah aplikasi manajemen proyek berbasis web menggunakan framework Laravel dan database MySQL. Metode Waterfall diterapkan dalam proses pengembangan, yang meliputi fase analisis, desain, implementasi, pengujian, dan pemeliharaan. Aplikasi ini menawarkan fitur-fitur seperti login, registrasi, manajemen pengguna, manajemen proyek dan tugas, serta pelaporan bulanan. Pengujian dengan metode Black-Box menunjukkan bahwa aplikasi berfungsi sesuai dengan spesifikasi.
CLOCKINTIME APLIKASI BERBASIS WEBSITE UNTUK ABSENSI PEGAWAI Julianti, Syelvia; Widiartha, I Made; Putri, Luh Arida Ayu Rahning
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

Produktivitas karyawan sangat bergantung pada sistem absensi yang efektif dan efisien. PT Guna Teknologi Nusantara menghadapi tantangan dalam pengelolaan absensi dengan sistem konvensional, sehingga dikembangkanlah aplikasi ClockInTime, sebuah platform absensi berbasis web. Aplikasi ini memungkinkan pencatatan absensi secara real-time, pengajuan izin dan cuti, serta pelaporan kehadiran. Pengembangan sistem ini menggunakan metode Waterfall yang terdiri dari tahapan analisis kebutuhan, desain sistem, implementasi, pengujian, dan pemeliharaan. Fitur-fitur utama dalam ClockInTime mencakup absensi harian dan pengajuan izin. Hasil pengujian black-box dan user acceptance set menunjukkan bahwa sistem berfungsi sesuai dengan spesifikasi dan mendukung pengelolaan absensi yang lebih efisien. Sistem ini diharapkan dapat terus dikembangkan untuk memenuhi kebutuhan perusahaan yang dinamis.
Analisis Sentimen Pengguna TikTok Terhadap Progres Pembangunan IKN Menggunakan LSTM dan FastText Gusti Agus Sakah Aditia; Luh Arida Ayu Rahning Putri
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.p21

Abstract

The development of the Capital City of the Archipelago (IKN) is one of the national strategic projects that has generated various reactions and public opinions. Social media, especially TikTok, has become an important platform for people to voice their views through video content and interactive comments. This research aims to analyze the sentiment of TikTok users towards the progress of IKN construction using a deep learning approach, namely the Long Short-Term Memory (LSTM) algorithm. Sentiment data was collected from Kaggle as many as 1472 Indonesian comments, then processed through the stages of normalization, tokenization, and conversion into word embeddings. The LSTM model was designed and trained to classify sentiment into positive, negative, and neutral. The results of the analysis are expected to provide a comprehensive picture of public perception towards IKN, identify critical issues that are often discussed, and measure the level of public acceptance or rejection of this project. This research is expected to contribute to a better understanding of the dynamics of public opinion in the digital era.
Evaluasi Desain Aplikasi Delivery Menggunakan Metode System Usability Scale Matthew Novan Sidharta; Luh Arida Ayu Rahning Putri
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.p24

Abstract

Technology continues to develop from time to time and has been widely used to support various forms of services, such as delivery service. However, not every aspect can be fulfilled by this kind of application. The delivery application which is selected by researcher in this paper is disguised. The application under this research will be evaluated in terms of UI/UX design. The usability testing method that will be used in the evaluation process is the system usability scale. The result shows that the system usability scale’s score on the application is at 54,16. To improve the application performance, especially in terms of UI/UX, the application can be redesigned for the next research. 
Simulasi IoT Pemantauan Tanaman Lidah Buaya Berbasis Algoritma Fuzzy Bayu Yudistira Ramadhan; Luh Arida Ayu Rahning Putri
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.p22

Abstract

In the digital era, technological advancements have entered the Industrial Revolution 4.0, and the agricultural sector in Indonesia is adapting to this revolution. Using a fuzzy algorithm, this research simulates an IoT-based monitoring system for Aloe vera plants. The system aims to assist farmers in real-time and accurately monitor Aloe vera plant conditions. Aloe vera has a narrow optimal temperature range of 16-33°C and an ideal soil moisture range of 40-75% for optimal growth. By implementing fuzzy logic, a mathematical concept that is easy to understand, the system can accurately map input conditions to output decisions. The simulation uses MATLAB and the Tinkercad website to design a fuzzy logic system that controls a water pump and fan based on soil moisture and temperature inputs from SEN1 and LM35 sensors, respectively. The fuzzy rules maintain the ideal conditions for Aloe vera growth, reducing energy consumption and water waste. The results demonstrate the high accuracy of the fuzzy logic system in making control decisions for maintaining optimal growing conditions. 
Co-Authors Agus Muliantara Anak Agung Istri Ngurah Eka Karyawati Anak Agung Istri Ngurah Eka Karyawati Ari Putra, I Kadek Riski Ariyawan, Made Dwi Artayani, Adis Luh Sankhya Bayu Yudistira Ramadhan Bhavanta, I Made Adika Christian Valentino Cokorda Pramartha Cokorda Rai Adi Pramartha Culio, Shelomita Putrinda Diatmika, I Kadek Angga Kusuma Diputra Wiraguna, I Gusti Agung Ngurah Dwi Payana, I Kadek Krisna Eka Wijaya, I Komang Sutrisna Enga Prinda Adu Gede Sudimahendra Genaldy Septianto Mbuik Giri, I Nyoman Yusha Tresnatama Gst. Ayu Vida Mastrika Giri Guna, Putu Wahyu Tirta Gusti Agus Sakah Aditia Gusto Gibeon Ginting I Dewa Agung Adwitya Prawangsa I Dewa Made Bayu Atmaja Darmawan, I Dewa Made Bayu I Gede Arta Wibawa I Gede Erwin Winata Pratama I Gede Santi Astawa I Gede Tendi Ariyanto I Gede Yogananda Adi Baskara I Gusti Agung Gede Arya Kadyanan I Gusti Agung Ngurah Diputra Wiraguna I Gusti Ayu Riyana Astarani I Gusti Ngurah Adhiwangsa Devananda I Gusti Ngurah Anom Cahyadi Putra I Gusti Ngurah Febri Ananda Krisna I Kadek Angga Kusuma Diatmika I Kadek Krisna Dwi Payana I Kadek Riski Ari Putra I Ketut Adian Jayaditya I Ketut Gede Suhartana I Komang Arya Ganda Wiguna I Komang Kumara Saduadnyana I Komang Sutrisna Eka Wijaya I Made Suma Gunawan I Made Teja Sarmandana I Made Widiartha I Made Widiartha I Putu Gede Hendra Suputra I Putu Indie Surya Jayadi I Putu Rama Anadya I Wayan Gede Adi Palguna I WAYAN SANTIYASA I Wayan Supriana Ida Ayu Gde Suwiprabayanti Putra Ida Bagus Ari Widhiana Ida Bagus Made Mahendra Julianti, Syelvia Kadek Cahya Dewi Kadek Vincky Sedana Kompiang Gede Sukadharma Luh Gede Astuti Matthew Novan Sidharta Ngurah Agus Sanjaya ER Ngurah Diputra Wiraguna, I Gusti Agung Ni Putu Sintia Wati Ni Putu Subhasini Dewi Sukma Ni Wayan Windayani Palguna, I Wayan Gede Adi Pradnyaditha, Kadek Yoga Vidya Pratama, I Gede Erwin Winata Putu Audy Cipta Pratiwi Putu Risky Andrean Rizky, Muhammad Firyanul Satria Mahagangga, Made Dhandy Sidharta, Matthew Novan Sri Hartati Sudimahendra, Gede Wahyu Ramadhan Wayan Gede Suka Parwita Wayan Kiki Oktalao Wikardiyan, Aditya Yana, Santa Yasa, I Gede Cahya Purnama