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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

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

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.

Penerapan Metode Single Exponential Smoothing Dalam Peramalan Penjualan Barang Ginantra, Ni Luh Wiwik Sri Rahayu; Anandita, Ida Bagus Gede
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

The technology of buying and selling goods in managing goods in and out will provide convenience for the management in managing stock data, financial control and profit calculation that will be immediately known by stakeholders. Forecasting method is a method that is able to analyze several factors that are known to influence the occurrence of an event with a long grace period between the need for knowledge of an event to occur in the future and the time the event has occurred in the past. In a retail company, if this forecasting method is applied in the planning of goods management, the company will be assisted in the process of planning the sale of goods which is currently still being done by predicting the amount of sales of goods that will come without any calculation, causing excessive purchases of goods that can affect the stock of goods. Single exponential smoothing method is a development of the single moving averages method where the forecasting method is done by repeating calculations continuously using the latest data and each data is weighted. The single exponential smoothing method considers the weight of the previous data by giving weight to each data period to distinguish the priority of data. The single exponential smoothing method is a method used in short-term forecasting that is usually only 1 month ahead which assumes that the data fluctuates around a fixed mean value without consistent trends or growth patterns. The accuracy of the application of the single exponential method in forecasting sales of goods in this study with an alpha value of 0.1 on the MAPE calculation average is 2%.

Sistem Pendukung Keputusan Penerimaan Tenaga Unit Medis di RS Ari Canti dengan Metode Topsis Wiwik Sri Rahayu Ginantra, Ni Luh; Yanti, Christina Purnama; Toraja, Dewa Gede
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i2.257

Ari Canti Hospital selectively conducts selection in the company environment that is by selecting one by one application then do some test on applicants with several criteria. With a large number of applicants making the selection process takes a lot of time and effort, as well as applicant data and the outcomes of the applicants are not well archived. Based on the above problems, need a solution to problem-solving by making a Decision Support System to determine the appropriate applicants to become new employees by facilitating the selection of employees by predetermined criteria. The TOPSIS method is chosen because this method is a form of decision support method based on the concept that the best alternative not only has the shortest distance from the ideal solution but also has the longest distance Of the ideal solution. The result of the design of this Decision Support System is the system has been able to generate reports from the applicant rank calculation by the values that have been obtained on the criteria that have been determined. The calculation results of the Decision Support System is already by the calculations performed manually.

Penerapan Metode Single Exponential Smoothing Dalam Peramalan Penjualan Barang Ginantra, Ni Luh Wiwik Sri Rahayu; Anandita, Ida Bagus Gede
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v3i2.162

The technology of buying and selling goods in managing goods in and out will provide convenience for the management in managing stock data, financial control and profit calculation that will be immediately known by stakeholders. Forecasting method is a method that is able to analyze several factors that are known to influence the occurrence of an event with a long grace period between the need for knowledge of an event to occur in the future and the time the event has occurred in the past. In a retail company, if this forecasting method is applied in the planning of goods management, the company will be assisted in the process of planning the sale of goods which is currently still being done by predicting the amount of sales of goods that will come without any calculation, causing excessive purchases of goods that can affect the stock of goods. Single exponential smoothing method is a development of the single moving averages method where the forecasting method is done by repeating calculations continuously using the latest data and each data is weighted. The single exponential smoothing method considers the weight of the previous data by giving weight to each data period to distinguish the priority of data. The single exponential smoothing method is a method used in short-term forecasting that is usually only 1 month ahead which assumes that the data fluctuates around a fixed mean value without consistent trends or growth patterns. The accuracy of the application of the single exponential method in forecasting sales of goods in this study with an alpha value of 0.1 on the MAPE calculation average is 2%.

Sistem Pendukung Keputusan Penerimaan Tenaga Unit Medis di RS Ari Canti dengan Metode Topsis Wiwik Sri Rahayu Ginantra, Ni Luh; Yanti, Christina Purnama; Toraja, Dewa Gede
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i2.257

Ari Canti Hospital selectively conducts selection in the company environment that is by selecting one by one application then do some test on applicants with several criteria. With a large number of applicants making the selection process takes a lot of time and effort, as well as applicant data and the outcomes of the applicants are not well archived. Based on the above problems, need a solution to problem-solving by making a Decision Support System to determine the appropriate applicants to become new employees by facilitating the selection of employees by predetermined criteria. The TOPSIS method is chosen because this method is a form of decision support method based on the concept that the best alternative not only has the shortest distance from the ideal solution but also has the longest distance Of the ideal solution. The result of the design of this Decision Support System is the system has been able to generate reports from the applicant rank calculation by the values that have been obtained on the criteria that have been determined. The calculation results of the Decision Support System is already by the calculations performed manually.

Optimizing convolutional neural networks-based ensemble learning for effective herbal leaf disease detection Ginantra, Ni Luh Wiwik Sri Rahayu; Yanti, Christina Purnama; Ariantini, Made Suci
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp2416-2426

This study aims to optimize convolutional neural networks (CNN)-based ensemble learning models to enhance accuracy and stability in detecting herbal leaf diseases. The dataset used in this study is sourced from the “Lontar Taru Pramana” collection, which includes various images of herbal leaves affected by different diseases such as Ancak Bacterial Spot, Dapdap Mosaic Virus, and Kelor Powdery Mildew. Several CNN models, including VGG16, AlexNet, ResNet50, DenseNet121, MobileNetV2, and InceptionV2, were evaluated. Among these, the ensemble models combining VGG16, DenseNet121, and MobileNetV2 were selected due to their superior performance. The ensemble model achieved precision scores of 0.81 for class 1, 0.76 for class 2, and 0.78 for class 3, with corresponding recall scores of 0.8167, 0.74, and 0.7633, and F1-scores of 0.8133, 0.75, and 0.7717 respectively. These results indicate significant improvements in model performance and robustness.

Penerapan Metode Metode Weighted Aggregated Sum Product Assesment (WASPAS) dalam Pemilihan Supplier Faisal Amir; Pressa Persana Surya Saputra; Jasmir; Samsul Lutfi; Ni Luh Wiwik Sri Rahayu Ginantra; Ilham Tri Maulana
Journal of Informatics Management and Information Technology Vol. 3 No. 1 (2023): January 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v3i1.241

The most important activity carried out by companies is to make a profit. Very subjective decision making can lead to errors in supplier selection. In supplier selection, the purchasing department often experiences difficulties in determining the selection of suppliers to be given orders because of the large number of suppliers and the criteria used in the assessment. Therefore, a supplier selection decision support system is needed so that the purchasing department can determine the best supplier. This decision support system uses the Weighted Aggregated Sum Product Assessment (WASPAS) method where this method can be used to overcome existing problems, because there are many alternatives and criteria that must be considered in selecting suppliers such as: price, quality, availability of goods and others. This research will raise a case that is looking for the best alternative based on predetermined criteria. In order to find the weight of each attribute, then a ranking process is carried out which will determine the optimal alternative, namely the best supplier.

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

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.

Measurement of the Similarity of Indonesian Papers on One Journal Topic with the Naive Bayes Algorithm and Vector Space Model Ni Luh Wiwik Sri Rahayu Ginantra; Ni Wayan Wardani
IJCONSIST JOURNALS Vol 1 No 1 (2019): September
Publisher : International Journal of Computer, Network Security and Information System

Abstract— One way to maintain the quality of scientific work in Indonesia is by checking articles before they are published. Checking before the publication was done so that the similarity level is not high because the published papers can be quoted to cause a high level of similarity. The next problem is the importance of grouping topic papers, where papers to be checked should have the same category as comparative papers. In this study, to classify the topic of the journal using the Naïve Bayes algorithm and to measure the similarity of papers using the Vector Space Model method. Naïve Bayes algorithm can better classify the test data with the .docx file format than to the test data in the .pdf file format. The results of the calculation of text similarity detection by the Vector Space Model can reach 90% and above for test data with the .docx file format, while for test data with the .pdf file format the calculation results by the Vector Space Model are on average less than 90%. The results of the calculation of text similarity detection by the Vector Space Model method are also strongly influenced by training data. The more complete and complex of the training data, then more valid the results of the Vector Space Model performance testing

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