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All Journal Sistemasi: Jurnal Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal TAM (Technology Acceptance Model) Journal of Electrical, Electronics and Informatics JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Tematik : Jurnal Teknologi Informasi Komunikasi PROFICIO: Jurnal Pengabdian Masyarakat JURNAL ELEKTRO DAN INFORMATIKA SWADHARMA (JEIS) Jurnal Pengabdian Masyarakat Tapis Berseri Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat Jurnal TAM (Technology Acceptance Model)
Hendrawati, Theresia
Institut Bisnis Dan Teknologi Indonesia
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Social Sciences Other

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Prediksi Harga Material Bangunan Dengan Autoregressive Integrated Moving Average (Arima) Pada CV. TJA Christina Purnama Yanti; Ni Komang Ita Cahyani; Theresia Hendrawati; Yuri Prima Fittryani; Dewa Ayu Kadek Pramita
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1914

Abstract

The problem most often faced by CV TJA is that the price from the RAB (Cost Budget Plan) calculation is not in accordance with market prices, so it is necessary to predict the price of building materials to help the company prepare the RAB. The aim of this research is to examine predictions of material prices measured using the ARIMA method. The data analysis method in this study used the MA parameter (1) with the ARIMA model (0,1,1) for dynamix cement material, the MA parameter (1) ARIMA model (0,2,1) for cast sand, the MA parameter (1 ) ARIMA model (0,3,1) for threaded iron 13 and AR parameter (2) ARIMA model (2,1,0) for usuk wood material. By using 3 error testing methods, namely Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD) and Mean Squared Deviation (MSD). The results of this analysis show the lowest accuracy value, namely for dynamic cement material with a MAPE value of 5%, a MAD value of 1.986 and an MSD value is 63.584.667. The results of error tests using MAPE, MAD and MSD can be concluded that the ARIMA method is very accurate because the MAPE value is less than 10%.
PKM Pemutakhiran Data Penduduk di Desa Kukuh Kerambitan Tabanan: Indonesia Ginantra, Ni Luh Wiwik Sri Rahayu; Yanti, Christina Purnama; Wulandari, Dewa Ayu Putri; Hendrawati, Theresia
Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) Vol. 2 No. 1 (2023): Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) (Edisi April)
Publisher : Pusat Studi Teknologi Informasi Fakultas Ilmu Komputer Universitas Bandar Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jpmtb.v2i1.49

Abstract

Kukuh Village is a village located in Kerambitan District, Tabanan Regency, Bali. Regional government has been promoting routine population data collection but most people do not yet have awareness of the importance of such data collection. Village population data stored in the Kukuh Village Information System is currently inaccurate, because the population of Kukuh Village is increasing every year, causing population data stored in the Kukuh Village Information System to be less accurate. Because of this, a population data update was carried out in Kukuh Village, Kerambitan, Tabanan. This program is realized in order to make population data on the official website of the Kukuh Village Information System accurate, up-to-date, integrated, of good quality so as to create accurate population data on the official website of the Kukuh Village Information System.
Penerapan Metode Stable Diffusion Dengan Fine Tuning Untuk Pola Endek Bali Ginantra, Ni Luh Wiwik Sri Rahayu; Hendrawati, Theresia; Wulandari, Dewa Ayu Putri
TEMATIK Vol. 11 No. 2 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Desember 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i2.2069

Abstract

Endek Bali fabric is a cultural heritage of Bali renowned for its traditional decorative motifs, including floral, fauna, patra, and diamond patterns. Although rich in cultural value, artisans often face challenges in creating new designs that align with market trends while preserving cultural authenticity. Artificial Intelligence (AI) technology, particularly text-to-image generation models, offers a solution to this issue by streamlining the design process and enabling the exploration of new motifs. The Stable Diffusion model, introduced by Stability.AI in 2022 and open source, can be utilized to generate Endek Bali patterns through Fine Tuning techniques. Fine Tuning allows the model to be adapted to specific domains, enhancing its performance in generating textile patterns based on textual descriptions. This study aims to apply the Stable Diffusion model and Fine Tuning techniques to create new patterns and motifs. By using this model, it is hoped that innovative designs can be produced while maintaining the authenticity and local cultural values of Bali. The research demonstrates that the Fine-Tuned Stable Diffusion model is effective in creating Endek Bali patterns with high accuracy, as evaluated by Clip Similarity, with the highest scores achieved for Floral Patterns (92.43), followed by Decorative (free-form motifs) Floral (88.77), Decorative (free-form motifs) Geometric (87.94), and Decorative (free-form motifs) (85.79). These findings indicate the model’s flexibility and effectiveness in producing intricate textile designs, enabling designers and artisans to generate complex and innovative patterns solely from textual descriptions while preserving Bali’s cultural values.
ANALYSIS OF E-LEARNING ACCEPTANCE IN GENERATION Z STIKI INDONESIA DURING THE COVID-19 PANDEMIC I Gusti Ayu Agung Mas Aristamy; Theresia Hendrawati
Jurnal TAM (Technology Acceptance Model) Vol 13, No 2 (2022): Jurnal TAM (Technology Acceptance Model)
Publisher : LPPM STMIK Pringsewu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/jurnaltam.v13i2.1302

Abstract

E-Learning has been applied for a long time in Indonesia and other developed and developing countries. However, research by Salloum et.al., said that E-Learning systems in developing countries were partially or completely not adopted; utilization has not been completed and is considered less than a satisfactory level. This refers to the lack of understanding of the factors that influence adoption. One of the latest studies on distance learning during the COVID-19 pandemic said that there were several obstacles experienced by students, and teachers. This study aims to analyze the adoption of E-Learning technology in Generation Z at one of university in Bali during the COVID-19 pandemic. Results of this study indicate that there is a positive impact of computer self-efficacy and accessibility on the perception of the ease with which students use the E-Learning system. The factors of information quality and content quality positively affect the students' perceived ease of use and usefulness of the E-Learning system. It is this perception of the usefulness and ease of use of the E-Learning system that has an increasing impact on students' intentions and attitudes to use the E-Learning system in the future.
Implementasi Aplikasi Buku Kas Untuk Menunjang Kompetensi Siswa Jurusan Akuntansi Ni Luh Wiwik Sri Rahayu Ginantra; Christina Purnama Yanti; Theresia Hendrawati
Darma Abdi Karya Vol. 3 No. 2 (2024): Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM POLITEKNIK LP3I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/darmaabdikarya.v3i2.2167

Abstract

At this time, people are more directed towards consumptive behavior in living their daily lives. The same is true for teenagers, the majority of whom follow a lifestyle in accordance with current trends. By following this trend, it is certain that adolescents will spend more money and not commensurate with existing income. Similarly, students at SMK Dwijendra Denpasar majoring in Accounting have problems where students are difficult to manage their personal finances. With our community service activities, it is hoped that it can help students in terms of a good financial management system and can improve skills and knowledge about how to manage personal finances so that later in the world of work it is expected to be able to manage company finances. The output of this research is that students are able to identify and prioritize the main priorities for allocating their personal funds. In addition, students can feel financial security in meeting sudden needs, because they have sufficient savings in the future.
ANALISIS SENTIMEN CHATGPT DATA SOSIAL MEDIA X(TWITTER) DENGAN MENGGUNAKAN FINE TUNING XL NET Hendrawati, Theresia; Ginantra, Ni Luh Wiwik Sri Rahayu
JEIS: Jurnal Elektro dan Informatika Swadharma Vol 5, No 2 (2025): JEIS EDISI JULI 2025
Publisher : Institut Teknologi dan Bisnis Swadharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56486/jeis.vol5no2.782

Abstract

ChatGPT (Generative Pre-training Transformer) is an artificial intelligence technology designed to mimic human conversation in text form and has become an important tool in various fields, including education. This study aims to analyze public sentiment toward the use of ChatGPT, which can be categorized into positive and negative sentiments. The data for the study was obtained from 5,686 user reviews on the Twitter platform, collected through Google Colaboratory and processed with pre-processing steps. The data was labeled as positive and negative, then classified using fine-tuning on the XLNet model, a Transformer-based language model. The results show that the fine-tuned XLNet model achieved an accuracy of 88.45%, a precision of 89%, a recall of 88%, and an F1-score of 89%, as measured using the Confusion Matrix. This study demonstrates that fine-tuning XLNet is effective in classifying the sentiment of ChatGPT user reviews related to education.ChatGPT (Generative Pre-training Transformer) adalah teknologi kecerdasan buatan yang dirancang untuk menirukan percakapan manusia dalam bentuk teks dan telah menjadi alat penting di berbagai bidang, termasuk pendidikan. Penelitian ini bertujuan untuk mengalisis akurasi kinerja model fine tuning XL Net  dari sentimen masyarakat terhadap penggunaan ChatGPT, yang dapat dikategorikan menjadi sentimen positif dan negatif. Data penelitian diperoleh dari 5.686 ulasan pengguna di platform Twitter, dikumpulkan melalui Google Colaboratory dan diproses dengan tahap pre-processing. Data diberi label positif dan negatif, lalu diklasifikasikan menggunakan metode fine-tuning pada model XLNet, model bahasa berbasis Transformer. Hasil penelitian menunjukkan bahwa model fine-tuning XLNet mencapai akurasi 88,45%, precision 89%, recall 88%, dan F1-score 89%, yang diukur menggunakan Confusion Matrix. Penelitian ini membuktikan bahwa fine-tuning XLNet efektif dalam mengklasifikasikan sentimen ulasan pengguna ChatGPT terkait pendidikan
Klasifikasi Tingkat Keparahan Penyakit Diabetic Retinopathy menggunakan Convolutional Neural Network Ginantra, Ni Luh Wiwik Sri Rahayu; Hendrawati, Theresia; Prasetya, I Kadek Diksa Bayu
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): Juli 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7432

Abstract

Diabetic Retinopathy is an eye condition in Diabetes sufferers that causes damage to the retina, which can result in permanent blindness if not treated properly. The initial stage of this disease is the widening of the blood vessels in the eye which, if left untreated, can cause the formation of new blood vessels which can cover the retina of the eye, thereby increasing the risk of vision loss. There are several classes of Diabetic Retinopathy disease; to determine the class you can use the Deep Learning method which can model various data such as images. The classification process is carried out by training a Convolutional Neural Network model on a disease image dataset taken from the Kaggel repository with a total of 5 classes. This research uses a Fine Tuning strategy and the EfficientNetB1 model to determine the performance of the CNN model in the Diabetic Retinopathy Classification process. Based on training results, the EfficientNetB1 model produces 92.51% accuracy in detecting Diabetic Retinopathy. These results show that the model can provide optimal results in the dataset training process.
PKM Penggunaan Teknologi Augmented Reality Pelajaran Biologi Untuk Meningkatkan Pemahaman Siswa SMA Christina Purnama Yanti; Ginantra, Ni Luh Wiwik Sri Rahayu; Theresia Hendrawati; Dewa Ayu Putri Wulandari
Darma Abdi Karya Vol. 3 No. 1 (2024): Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM POLITEKNIK LP3I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/darmaabdikarya.v3i1.1972

Abstract

Biology is a science that studies everything about everyday life, such as living things, health, the environment, and biology can also be used to solve problems that occur in everyday life. One of the things that is discussed in biology is viruses. A virus is a living creature with parasitic properties, which means that the life of this living creature depends on other living creatures by infecting the cells of other living creatures. Studying biology at high school level is considered quite important because it is considered to be an opportunity for students to get to know themselves, the environment and the living creatures around them. Based on interviews conducted with Mr. Tisnawan as one of the biology subject teachers at SMA Negeri 8 Denpasar, the results showed that there are challenges in studying the structure and shape of viruses which can influence students' interest in learning, such as the abstract shape of viruses, lack of variation in learning media, and limited equipment and practical space such as microscopes and others. Therefore, the service team plans to introduce teachers and students to the use of Augmented Reality in learning media where the topic used is the structure and shape of viruses in class X high school material. Assistance to teachers and students in using Augmented Reality applications needs to be provided so that teachers and students can use them well. Apart from that, this assistance is also expected to increase teachers' digital literacy in using technology in learning.
Co-Authors Aristamy, I Gusti Ayu Agung Mas Christina Purnama Yanti Christina Purnama Yanti Christina Purnama Yanti Dewa Ayu Putri Wulandari Dewa Ayu Putri Wulandari Duman Care Khrisne Dwipayana, Ida Bagus Rama I Gde Swiyasa Surya Dharma Kadek Listy Mas Setya Devi Ni Komang Ita Cahyani Ni Luh Wiwik Sri Rahayu Ginantra Ni Luh Wiwik Sri Rahayu Ginantra, M.Kom Pramita, Dewa Ayu Kadek Prasetya, I Kadek Diksa Bayu Saiman, Clarita Mutiara Sandhiyasa, I Made Subrata Santi Ika Murpratiwi Sastaparamitha, Ni Nyoman Ayu J Wulandari, Dewa Ayu Putri Yuri Prima Fittryani, Yuri Prima