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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Sains dan Teknologi JUTIK : Jurnal Teknologi Informasi dan Komputer Jurnal RESISTOR (Rekayasa Sistem Komputer) International Journal of Natural Science and Engineering International Journal of Engineering and Emerging Technology JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) INSERT: Information System and Emerging Technology Journal JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) International Journal Of Computer, Network Security and Information System (IJCONSIST) Jurnal Manajemen dan Teknologi Informasi Jurnal Pengabdian Kepada Masyarakat SEWAGATI Jurnal Bahasa Rupa IJISCS (International Journal of Information System and Computer Science) Jurnal Bahasa Rupa
Wardani, Ni Wayan
LPPM STMIK STIKOM Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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KEGIATAN PENGABDIAN PEMBUATAN FILM LONTAR PRASI UNTUK PELESTARIAN KEARIFAN BUDAYA LOKAL DI DESA TENGANAN PAGRINGSINGAN I Nyoman Agus Suarya Putra; Putu Gede Surya Cipta Nugraha; Ni Wayan Wardani
Sewagati Vol. 2 No. 2 (2023): Sewagati
Publisher : Fakultas Teknik dan Informatika Universitas PGRI Mahadewa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59819/sewagati.v2i2.3317

Abstract

Lontar Prasi is an art that has grown and developed in Tenganan Pagringsingan Village in Karangasem, Bali since the time of our ancestors. Advances in digital technology in the current era are increasingly distancing this art from the younger generation. Other factors such as complicated prasi making, materials that seem ancient and primitive, wayang stories that are difficult to understand, text and illustrations that are less attractive, and their rare existence make it increasingly difficult for the younger generation and the public to get to know Prasi. By utilizing advances in digital technology to maintain the existence of Prasi, the film Lontar Prasi was made. The process of creating the Lontar Prasi film went through 3 stages, namely pre-production, production, and post-production. Evaluation of films is carried out by distributing questionnaires to content experts, media experts, and the public. The evaluation results of the Lontar Prasi film show that the content is quite good and worthy of publication as information media. With the Lontar Prasi documentary film Tenganan Pagringsingan Village, it is hoped that the community, especially the younger generation, will receive information and participate in preserving Balinese culture.
Predicting Wine Quality from Chemical Properties Using XGBoost Application Wardani, Ni Wayan; Sugiartawan, Putu
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 6 No 4 (2024): June
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.239

Abstract

This research applies XGBoost, a gradient boosting machine learning algorithm, to predict wine quality based on physicochemical properties such as acidity, alcohol content, and sulfur dioxide levels. Traditional sensory evaluations of wine, while critical, are subjective, time-consuming, and prone to variability. By utilizing XGBoost, this study aims to offer a scalable, data-driven approach to automate wine quality assessments, addressing the limitations of traditional methods. The model was fine-tuned through hyperparameter optimization, achieving high prediction accuracy and interpretability. Feature importance analysis provided actionable insights for winemakers, highlighting the key chemical attributes influencing quality. Comparative analysis against Random Forest and Support Vector Machines demonstrated XGBoost's superior efficiency and robustness, particularly in handling non-linear relationships and imbalanced datasets. This research not only enhances the automation of wine quality assessment but also provides valuable knowledge to optimize production processes. The findings underscore the transformative potential of machine learning in the food and beverage industry, enabling consistent quality control and informed decision-making for stakeholders.
Machine Learning Forecasting Techniques for Analyzing Tourist Arrivals in Bali Sugiartawan, Putu; Wardani, Ni Wayan
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 7 No 1 (2024): September
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.243

Abstract

This study investigates the application of machine learning (ML) techniques for forecasting tourist arrivals in Bali, leveraging a dataset spanning from 1982 to 2024. The Random Forest model, along with Linear Regression and Decision Tree, was evaluated for its ability to handle the complexities of tourism data, characterized by seasonality and nonlinear patterns. Among the models tested, Random Forest achieved the best performance, with the lowest Mean Squared Error (MSE) and Mean Absolute Error (MAE), demonstrating its robustness in capturing both short-term fluctuations and long-term trends. The findings highlight the potential of ML techniques to improve forecasting accuracy compared to traditional methods, especially in managing seasonal variations and external disruptions like the COVID-19 pandemic. However, limitations in predicting unprecedented events underscore the need for integrating external variables, such as economic indicators and travel restrictions. Future research should focus on hybrid models, scenario-based forecasting, and real-time data integration to enhance adaptability and predictive accuracy. These advancements aim to support policymakers and stakeholders in optimizing resource allocation, designing marketing strategies, and fostering sustainable tourism development in Bali.
Analisis Penggunaan Lego dalam Pembelajaran Sejarah Perang Kusamba untuk Anak Usia Dini Putra, I Nyoman Agus Suarya; Nugraha, Putu Gede Surya Cipta; Wardani, Ni Wayan
Jurnal Bahasa Rupa Vol. 7 No. 3 (2024): Jurnal Bahasa Rupa Agustus 2024
Publisher : Institut Bisnis dan Teknologi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/bahasarupa.v7i3.1569

Abstract

There is limited research that combines three things, namely, early childhood, technology and local wisdom. Current conventional education requires digital-based technology with all its advantages. Historical knowledge is best instilled as knowledge in early childhood in the age range of 4-6 years. The knowledge taken in this research is knowledge from a hero statue located in Kusamba village in the form of a woman holding a palm leaf named I Dewa Agung Istri Kanya. This research aims as an educational tool. Through the means of animated films, the Lego game is hoped to be able to provide historical education and be able to become a visual attraction in the educational process. The method in this research is a descriptive qualitative method by visualizing illustrations of historical toy stories of heroes that are close to children's tastes. Next, exploration and experimentation were carried out on the work by designing Lego with Balinese characters and clothing and creating the setting at the scene, namely Goa Lawah and Puri Klungkung. The production technique uses stop motion techniques. The process of making an animated film is carried out in three stages, namely pre-production, production, and post-production. Testing was carried out on material experts and media experts as well as parents who educate children aged 4-6 years. The results of 87% of respondents stated that it was suitable as a learning medium. The results of anecdotal notes on a sample of young children showed an increase in knowledge from not yet developing to developing according to expectations.
GDSS for Selecting Culinary Tourism in Bali Using Profile Matching and Borda Sugiartawan, Putu; Wardani, Ni Wayan
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 5 No 4 (2023): June
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.246

Abstract

This research proposes a method for determining the best culinary tourism destinations in Bali. Currently, being able to determine the best and potential destinations is a problem for people who want to travel tourism in Bali, both domestic and foreign people. Factors that have a dominant influence in determining potential destinations that still cannot be determined with certainty. This will greatly affect the results of decisions that will be taken by the community in determining the destination to be chosen. For this reason, it is very important to create a model to determine the best destination that can be chosen by the community as a decision support system in making decisions. In this journal Profile Matching has been used to determine the best destination as a category that can be obtained from the rating shown on the selected destination.
Time Series Prediction of Doge Coin Prices Using LSTM Networks Kusuma, Aniek Suryanti; Wardani, Ni Wayan
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 5 No 3 (2023): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.255

Abstract

This research explores the application of Long Short-Term Memory (LSTM) networks for predicting Dogecoin prices, addressing the challenges of cryptocurrency market volatility and non-linearity. A historical dataset spanning November 2017 to the present, including features such as opening and closing prices, daily highs and lows, and trading volume, was used for model development. Data preprocessing involved handling missing values, normalization, and structuring the data into a supervised learning format. The LSTM model was designed with optimized hyperparameters, trained using the Adam optimizer, and evaluated against metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). Benchmarking with traditional models like ARIMA and SVR demonstrated the LSTM model's superior performance in capturing temporal dependencies and adapting to high volatility. Despite its robust performance, the study highlights limitations, including the exclusion of external factors like market sentiment and a dataset limited to specific timeframes. Future research could integrate broader datasets and advanced features to enhance model precision. This work contributes to the field of cryptocurrency forecasting, offering insights for traders, investors, and researchers navigating volatile markets.
Sistem Informasi Laporan Keuangan pada Salon Berbasis Website Dengan Metode SDLC Desmayani, Ni Made Mila Rosa; Wardani, Ni Wayan; Nugraha, Putu Gede Surya Cipta; Mahendra, Gede Surya
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 4 No 2 (2021): December
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.118

Abstract

Jimmy Salon merupakan salah satu bisnis yang bergerak di bidang jasa tata rias rambut. Jimmy salon beroperasi sudah hampir 37 tahun. Jimmy salon berdiri pada tahun 1983 didirikan oleh Bapak Jimmy Waworuntu. Jimmy Salon terletak di Kompleks Pertokoan Nakula Plaza blok B-3 Jalan Nakula, Kecamatan Kuta, Kabupaten Badung, Provinsi Bali. Pelaporan keuangan di Jimmy Salon sudah terkomputerisasi namun masih menggunakan perangkat lunak microsoft excel sehingga untuk membuat laporan keuangan memakan waktu cukup lama dan laporan keuangan yang dihasilkan belum mampu menghasilkan laporan yang optimal. Tujuan dibangunnya sistem ini adalah untuk membantu administrator dalam menghasilkan laporan keuangan. Metode penelitian yang digunakan adalah metode SDLC. Metode pengujian yang digunakan adalah black box testing. Hasil dari sistem yang telah dibangun yaitu sistem telah berhasil dibuat berdasarkan kebutuhan usaha. Sistem berhasil memberikan laporan arus kas, laporan neraca, laporan laba rugi, dan laporan perubahan modal.
OPTIMALISASI SUMBER DAYA DAN PENGUATAN DIGITALISASI DESA BELUMBANG I Nyoman Agus Suarya Putra; Ni Wayan Wardani; Putu Satria Udyana Putra
Sewagati Vol. 4 No. 2 (2025): SEWAGATI
Publisher : Fakultas Teknik dan Informatika Universitas PGRI Mahadewa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59819/sewagati.v4i2.5647

Abstract

The Community Service Program will be implemented for approximately three months, from March 2025 to June 2025, in Belumbang Village, Kerambitan District, Tabanan Regency, Bali. This program is driven by the challenges faced by villages in optimizing information technology for data collection, news input on the Village Information System (SID), and digital promotion due to limited human resource knowledge. The main goal is to help village officials digitize Belumbang Village and develop students' soft skills. This method involves situation analysis, preparation (surveys, permits, material preparation), and the implementation of nine main programs, including managing the OPEN SID website, creating village introduction videos, optimizing posyandu and elderly data, and digital literacy training for students. The results show that this activity facilitates data management, introduces the village digitally, raises public awareness about organic waste management, and improves the digital skills of village staff and students. In conclusion, this Community Service Program successfully contributed to digital transformation and community development in Belumbang Village.
DenseNet121 and Transfer Learning for Lung Disease Classification from Chest X-Ray Images Sugiartawan, Putu; Wardani, Ni Wayan
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 8 No 2 (2025): December
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.266

Abstract

Lung-related disorders, including pneumonia, are still among the primary causes of death and illness worldwide, particularly in areas where medical imaging facilities and trained radiologists are scarce. The manual assessment of chest X-ray (CXR) images demands significant time and is prone to subjective interpretation, limiting its scalability for mass screening and early disease identification. To overcome these challenges, this study introduces an automated classification approach utilizing the DenseNet121 convolutional neural network through transfer learning for the detection of lung diseases from CXR scans. The pretrained ImageNet weights were adopted to capture hierarchical visual features efficiently, while overfitting was mitigated using dropout and batch normalization layers. The dataset employed consisted of 1,880 training images and 235 testing images, equally distributed between Normal and Viral Pneumonia categories. Experimental evaluation revealed an overall classification accuracy of 97%, alongside precision, recall, and F1-score metrics of 0.97 each, indicating reliable and balanced model performance. These outcomes suggest that DenseNet121 offers a highly effective foundation for computer-aided diagnostic systems capable of differentiating between healthy and infected lungs with high precision. The proposed framework provides a scalable diagnostic tool suitable for healthcare environments with limited radiological expertise. Future improvements will include expanding toward multi-class disease classification, incorporating explainable artificial intelligence (XAI) techniques to enhance interpretability, and validating the system on larger, more diverse clinical datasets.
Co-Authors Aniek Suryanti Kusuma, Aniek Suryanti Baehaqi Batubulan, Kadek Suarjuna Desak Dwi Utami Putra Devi Valentino Waas Dewa Ayu Giovany Angga Indrya Dirgayusari, Ayu Manik Eddy Hartono Erawati, Kadek Nonik Gede Indrawan Gede Rasben Dantes Gede Surya Mahendra I Dewa Made Krishna Muku I Gede Andika I Gusti Ayu Agung Diatri Indradewi I Kadek Adiana Putra I Nyoman Agus Suarya Putra I Putu Agus Eka Darma Udayana, I Putu Agus Eka I Putu Yoga Indrawan I Wayan Darmadi I Wayan Dharma Suryawan I WAYAN SUDIARSA Indra Pratistha Kadek Arya Wirtiana Putra M Kotama, I Nyoman Darma Luh Gede Bevi Libraeni Luh Putu Rara Ayu Ratnaningrum Ma’sum, M. Arif Mega Dewi Setyawati Ni Kadek Ariasih, Ni Kadek Ni Kadek Ayu Nirwana Ni Luh Wiwik Sri Rahayu Ginantra Ni Made Mila Rosa Desmayani, Ni Made Mila Rosa Nugraha, Putu Gede Surya Nyoman Arya Wiradarma Pradhana, Anak Agung Surya Putra, Putu Satria Udyana Putu Gede Surya Cipta Nugraha PUTU SUGIARTAWAN Saraswati, Ni Wayan Sumartini Silaen, Debora Hotnauli Sita Haniyatus Salimah Sutarwiyasa, I Ketut Willdahlia, Ayu Gede Winatha, Komang Redy