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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Pelayanan dan Pengabdian Masyarakat (Pamas) Journal of Applied Data Sciences
Ni Putu Widya Yuniari
Magister Teknik Elektro Universitas Udayana
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Environmental Science

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Enhancing Aspect-based Sentiment Analysis in Visitor Review using Semantic Similarity Iswari, Ni Made Satvika; Afriliana, Nunik; Dharma, Eddy Muntina; Yuniari, Ni Putu Widya
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.249

Abstract

The global economy greatly depends on the tourism industry, which fosters job opportunities and stimulates economic development. With the growing reliance of tourists on online platforms for guidance, evaluations of tourist destinations have gained heightened significance. These assessments, frequently expressed through user-generated content, offer valuable perspectives on customer experiences, viewpoints, and levels of satisfaction. Nevertheless, analyzing and interpreting these reviews can pose difficulties because of the unstructured or semi-structured nature of user-generated content. Conventional sentiment analysis methods might not adequately grasp the intricacies and particular aspects of tourism encounters that users convey in their reviews. The efficacy of sentiment analysis can be augmented by integrating semantic similarity. This study explores methods to enhance aspect-based sentiment analysis within tourism reviews by utilizing semantic similarity approaches. Five aspects have been curated, representing keywords frequently reviewed by visitors to the tourist attraction. These aspects encompass scenery, dusk, surf, amenities, and sanitation. Based on the data analysis, F-Measure values with Semantic Similarity tend to increase for the scenery and dusk aspects. This is because in the sample data used, visitor reviews for the scenery and dusk categories may use other words that are semantically similar. The sample data used for these categories is also quite extensive, resulting in a better classification model for both categories. While it is valuable to analyze user-generated content data from visitor reviews, it's important to consider the limitations and potential biases associated with this data. The classification results per aspect need to be further reviewed in more depth. What aspects lead visitors to give positive reviews will certainly be maintained and even improved by stakeholders. Similarly, for negative review outcomes, it is necessary to investigate more deeply the factors contributing to visitor dissatisfaction so that they can be addressed by stakeholders.
Integrate Yolov8 Algorithm For Rupiah Denomination Detection In All-In-One Smart Cane For Visually Impaired Kumara, I Made Surya; Jati, Gde Putu Rizkynindra Sukma; Yuniari, Ni Putu Widya
Techno.Com Vol. 23 No. 1 (2024): Februari 2024
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v23i1.9734

Abstract

The eyes are crucial tools for human observation and perception, facilitating various tasks in daily life. Individuals, including those with visual impairments or blindness, engage in currency transactions, posing challenges in recognizing notes and preventing mishaps with counterfeit money. Despite government efforts, features like embossing on banknotes have limited effectiveness due to the circulated currency's disheveled condition. Addressing the visually impaired community's needs is imperative. An innovative solution, the "all-in-one smart white cane," integrated with machine learning supports daily activities, enhancing independence for visually impaired individuals. The YOLOv8 algorithm is employed for the precise detection of monetary denominations, subsequently recorded through a camera and seamlessly integrated into a smart cane, resulting in a consolidated device. This device, designed with standout features, excels in detecting Indonesian Rupiah banknote denominations. Detection performance testing, incorporating methods like object rotation, utilized a dataset divided into training (70%), validation (20%), and test (10%) segments. Modifications to contrast and variability rotation are essential in the context of real-time nomination recognition. These adjustments are implemented to ensure accurate and swift identification in dynamic, real-world scenarios. Testing results reveal a 99% average accuracy in recognizing currency note denominations, presenting an effective solution for the visually impaired community.
Environment Sentiment Analysis of Bali Coffee Shop Visitors Using Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-trained Transformer 2 (GPT2) Model Yuniari, Ni Putu Widya; Iswari, Ni Made Satvika; Kumara, I Made Surya
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.302

Abstract

Bali is one of the provinces with the most abundant natural and cultural wealth in Indonesia. One commodity that supports it is coffee. Bali Coffee is not only a gastronomic identity, but also a cultural identity which makes it have added value to be developed into various business lines. One business derivative that is quite promising is a coffee shop. However, these favorable conditions also need to be maintained to ensure good quality reaches consumers. One thing that can do is analyze reviews from customers. One of the most popular methods is Sentiment Analysis. This technique allows business to analyze customer reviews on social media. It can be a feedback to maintaining and improving quality and good relationships with customers. This research aims to create a machine learning model to analyze customer reviews at several coffee shops in Bali which are divided into three labels, namely: positive, negative and neutral. The methods used are: scraping, cleaning, stopword removal, embedding, undersampling, and modeling. The algorithms used are Bidirectional Encoder Representation from Transformer (BERT) and Generative Pre-trained Transformers (GPT). The performance metrics used in this research are precision, recall, accuracy and loss. This research succeeded in creating a sentiment analysis model for coffee shop customers in Bali. The BERT model obtained an accuracy value of 78% without undersampling with a loss in the 10th iteration of 0.27. Meanwhile, the BERT model with undersampling obtained an accuracy value of 32.85% with a loss in the 10th iteration of 0.16. The GPT2 model without undersampling gets an accuracy of 78% with a loss in the 10th iteration of 0.25. Meanwhile, the GPT model with undersampling obtained an accuracy value of 32.85% with a loss in the 10th iteration of 0.15.
PENGABDIAN KEPADA MASYARAKAT “TERASDigital Peguyangan Kaja” (Transformasi Era Layanan Administrasi Menuju Sistem Digital Desa Peguyangan Kaja Melalui Tanda Tangan Elektronik) Dana, Gde Wikan Pradnya; Yuniari, Ni Putu Widya; Aryastana, Putu; Kumara, I Made Surya; Bhaskara, Made Adi; Darma, I Gede Wira; Raharja, I Kadek Agus Wahyu
Jurnal Pelayanan dan Pengabdian Masyarakat (Pamas) Vol 9, No 3 (2025): Jurnal Pelayanan dan Pengabdian Masyarakat (PAMAS)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM Universitas Respati Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52643/pamas.v9i3.5189

Abstract

Information technology within organizations, companies, and government institutions today plays a very significant role. However, the implementation of information technology in Indonesia still faces challenges in terms of efficiency and effectiveness, particularly in the village governance sector. On July 9, 2024, the Computer Engineering Faculty at Warmadewa University conducted a Community Service Program titled "TERAS Digital Peguyangan Kaja," which involved outreach and training to maximize the use of electronic signatures, evaluated using SWOT analysis. This program offers benefits such as the effectiveness and efficiency of public services. The implementation of electronic signatures is hindered by infrastructure issues and social resistance, necessitating outreach, intensive training, and infrastructure improvements. This community service program, in collaboration with the Denpasar City Communication and Information Agency (Diskominfo). This activity involved 25 participants consisting of village officials and service implementers, as well as representatives from the Denpasar City Communication and Information Office (Diskominfo). The evaluation of activities was carried out using SWOT analysis, involving socialization, training, and mentoring to implement the use of electronic signatures. evaluation using SWOT analysis. The implementation of socialization and training has increased the digital literacy of the community and village officials, increasing efficiency and effectiveness in solving the problems of the people of Peguyangan Kaja Village when the party whose signature is required by the village apparatus is in the way. . Although electronic signature technology has just begun to be implemented, there are technical obstacles and infrastructure limitations in Peguyangan Kaja Village that need to be overcome to ensure that this technology functions optimally and is accepted by the community. Future plans focus on improving the overall implementation of electronic signatures and increasing socialization to ensure the sustainability and effectiveness of the program. Keywords: Electronic Signatures, Socialization, Training, SWOT Analysis\
Co-Authors Afriliana, Nunik Bhaskara, Made Adi Darma, I Gede Wira Dharma, Eddy Muntina I Made Surya Kumara Jati, Gde Putu Rizkynindra Sukma Ni Made Satvika Iswari Putu Aryastana Raharja, I Kadek Agus Wahyu Wikan Pradnya Dana, Gde