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All Journal Jurnal Teknologi Informasi dan Multimedia JITU : Journal Informatic Technology And Communication Jurnal Manajemen dan Teknologi Informasi Jurnal Pengabdian Kepada Masyarakat SEWAGATI
Luh Putu Risma Noviana
Univeristas PGRI Mahadewa Indonesia
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Mechanical Engineering Other

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Perbandingan Klasifikasi Citra Daun Herbal Menggunakan Metode Logistic Regression dan Decision Tree Classifier Berdasarkan Fitur (Warna, GLCM, Bentuk) Luh Putu Risma Noviana; I Nyoman Bagus Suweta Nugraha
JITU : Journal Informatic Technology And Communication Vol. 7 No. 2 (2023)
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jitu.v7i2.1241

Abstract

The development of plant science is growing rapidly regarding herbal plants. Herbs have many benefits for life to prevent, cure diseases. To find out the types of herbal plants is done by the classification process. Classification of herbal plants can be done by identifying the shape of the leaf image of herbal plants by extracting color features, GLCM and shape from herbal leaves. The 275 dataset consists of 25 leaf types with 11 total datasets. There are several kinds of classification methods that can be used. In this study, the classification methods used were the Logistic Regression and Decision Tree Classifier methods. Based on the results of trials conducted using the Logistic Regression method, the train classification accuracy value was 72.9% and the classification test accuracy was 60.24%, while the Decision Tree Classifier method had a train classification accuracy value of 100% and the accuracy of the classification test was 78.31. This shows that the performance of the Decision Tree Classifier method is better than the Logistic Regression method
Analisis Kinerja Logistic Regression Classifier Berdasarkan Seleksi Fitur Warna, GLCM (Gray Level Co-occurrence Matrix) dan Bentuk (Studi Kasus Jenis Ketupat Khas Bali) Luh Putu Risma Noviana; I Nyoman Bagus Suweta Nugraha
Jurnal Teknologi Informasi dan Multimedia Vol. 6 No. 2 (2024): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v6i2.521

Abstract

Ketupat is a unique culture and tradition in Bali. Ketupat is often used as a banten offering. This unique procession of the ketupat war is held once a year to coincide with the Purnama Kapat. The ketupat war is a traditional event with participants throwing ketupat at each other. It aims to be grateful for all the gifts that the Creator has given to humans in this world. This tradition has existed since the 1970s with the beginning of its appearance involving two shirtless men. The ketupat war ceremony is part of the yadnya as the basis for the return of the Tri Rna. In today's era of the development of science and technology, people are only focused on meeting material needs, understanding the meaning of rituals and religious events is decreasing, and it is considered an incriminating or even meaningless activity. In this study, a dataset of 90 was used with 18 types of ketupat used, namely: bagia, batu dam-pulan, bracelet, kale, mattress, kedis, kepel, kroso, lepet, pengambean, sai, cow, sari, sirikan, suna, tulud, tumpeng. This study aims to determine the per-formance of Logistic Regression Classifier by using color, HSV, GLCM and shape features. The dataset used is a typical Balinese ketupat type of 90 data. In this test, 4 test scenarios are used: 1) The first test scenario, the dataset input performs the preprocessing process, HSV imagery, and the color feature extraction process where the output results are in the form of hue, saturation and value values in the form of excel files. 2) The second test scenario, the input dataset performs a preprocessing process, grayscale, and performs the GLCM feature extraction process where the output results are in the form of feature values of angle 00, angle 450, angle 900 and angle 1350 in the form of an excel file. 3) The third test scenario, the dataset input performs the preprocessing process, binner, performs the form feature extraction process where the output results are in the form of metric, eccentricity in the form of excel files. 4) The fourth test scenario, from the 3 (three) feature extractions carried out, the new dataset, the next stage is to implement the Logistic Re-gression classifier method to obtain accuracy values. Based on the results of the classification, testing and analysis, the level of accuracy from each of them was obtained with a training accuracy value of 69.84% and a testing accuracy of 22.2%, which means that the classification method was declared ineffective in analyzing the features used in the ketupat classification, so it is necessary to compare it with other methods so that it gets an accuracy result above 90%.
OPTIMALISASI PENGELOLAAN BUMDES MELALUI IMPLEMENTASI SISTEM INFORMASI TERINTEGRASI BERBASIS WEB DI DESA SINGAPADU EFEKTIF Gde Indra Ananta Wijaya; Ayu Aprilyana Kusuma Dewi; Ni Made Asri Sasmita; Luh Putu Risma Noviana; I Kadek Juni Arta
Sewagati Vol. 5 No. 1 (2026): SEWAGATI
Publisher : Fakultas Teknik dan Informatika Universitas PGRI Mahadewa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59819/sewagati.v5i1.6363

Abstract

This community service activity aims to optimize the management of Village-Owned Enterprises (BUMDes) through the implementation of an integrated web-based information system in Singapadu Village. The primary problems identified include low administrative efficiency, limited financial transparency, and the suboptimal use of technology in managing village business activities. The method employed is a participatory approach based on capacity building, involving stages of needs assessment, system development, usability testing, and implementation through socialization, training, and mentoring. The results indicate that the developed system demonstrates a very high level of feasibility based on the USE Questionnaire, achieving an average score of 6.63 out of 7 and an overall feasibility rate of 94.8%. The Ease of Use dimension recorded the highest score, indicating that the system is user-friendly and easily adopted by BUMDes managers. Furthermore, the mentoring activities significantly improved users’ understanding and skills in managing business data digitally. The system implementation also contributed to increased operational efficiency, improved financial transparency, and enhanced real-time performance monitoring. However, the sustainability of system usage depends on institutional commitment and the consistency of users in integrating the system into daily governance practices. Therefore, this activity contributes to accelerating the digital transformation of BUMDes, promoting a more adaptive, transparent, and data-driven management model to support sustainable rural economic development.
KOMPRESI CITRA DIGITAL ORNAMEN UKIRAN BALI MENGGUNAKAN METODE RLE I Putu Eka Indrawan Eka; Luh Putu Risma Noviana; Ayu Aprilyana Kusuma Dewi
Jurnal Manajemen dan Teknologi Informasi Vol. 16 No. 1 (2026): Jurnal Manajemen dan Teknologi Informasi
Publisher : Fakultas Teknik dan Informatika Universitas PGRI Mahadewa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59819/jmti.v16i1.6164

Abstract

This study investigates the implementation of Run Length Encoding (RLE) for compressing digital images of Balinese carved ornaments as a representation of local cultural heritage. The increasing need for high-resolution digital documentation of cultural artifacts leads to larger file sizes and higher storage and transmission demands. This research adopts an experimental quantitative approach to evaluate compression performance based on compression ratio, file size reduction, and processing time. The results demonstrate that RLE produces compression ratios ranging from 17.04% to 79.08%, depending on the visual complexity and repetitive structure of the ornament patterns. Images with dominant homogeneous areas and repetitive motifs achieved higher compression efficiency, while highly detailed and complex textures resulted in lower ratios. All decompressed images were identical to the original files, confirming that RLE operates as a lossless compression method and preserves visual integrity. The findings highlight the strong relationship between visual structure and algorithmic efficiency, contributing to the integration of information technology in the digital preservation of Balinese cultural artifacts.
PEMBERDAYAAN KELOMPOK POKDARWIS DESA BUKIT JANGKRIK LEWAT BUDIDAYA LEBAH TRIGONA DAN KEBUN PAKAN I Putu Eka Indrawan; Ni Nyoman Parmithi; Ayu Aprilyana Kusuma Dewi; Luh Putu Risma Noviana
Sewagati Vol. 4 No. 1 (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.v4i1.4787

Abstract

The development of Trigona honey bee farming by the Pokdarwis Group in Bukit Jangkrik Village, Gianyar, is still in its early stages toward becoming a productive economic activity. However, several fundamental challenges, such as limited availability of bee feed and insufficient knowledge about honey harvesting techniques, have resulted in low quality and quantity of production. To address these issues, a community service program was conducted from February to May 2025, involving 20 participants from the management and members of the Pokdarwis group. The solutions offered include knowledge and technology transfer through training on Trigona bee feed plant species and demonstration planting on demonstration plots (demplots). The program aims to enrich bee forage sources with sustainable nectar and pollen-producing plant species while enhancing partners' understanding of better honey production strategies. Bukit Jangkrik Village itself possesses ideal ecological potential for Trigona bee development, thereby strongly supporting the program's success. Following the activities, a significant increase in participants' knowledge was observed, with 100% of participants understanding the types of Trigona bee forage plants. This achievement demonstrates that the program has had a tangible impact in enhancing partners' capacity toward productive economic development. Moving forward, this progress is expected to serve as a strong foundation for promoting the sustainability of Trigona honey-based ecotourism and improving community well-being through the utilization of locally available, competitive resources.
WORKSHOP PENGUATAN KOMPETENSI GURU DALAM PEMBELAJARAN CODING DAN KECERDASAN ARTIFISIAL UNTUK PENGEMBANGAN KETERAMPILAN ABAD KE-21 DI SD NEGERI 1 SANGSIT, BULELENG I Putu Eka Indrawan; Ayu Aprilyana Kusuma Dewi; Ni Nyoman Parmithi; Luh Putu Risma Noviana; I Kadek Juni Arta
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.v4i2.5520

Abstract

This community service program was carried out at SD Negeri 1 Sangsit, Buleleng, with the aim of strengthening teachers’ competencies in coding and artificial intelligence (AI)-based learning to support the development of 21st-century skills. The activity was motivated by the challenges faced by teachers who had not yet implemented assessments aligned with the learning steps, such as developing test blueprints and conducting detailed item analyses. In the context of modern education, 21st-century-oriented assessment plays a crucial role as it emphasizes authentic evaluation that integrates critical thinking, collaboration, creativity, and communication skills. Through this workshop, teachers were guided to understand the concepts of coding and AI-based learning while designing assessments relevant to real-world contexts. The program was successfully implemented with 100% realization, resulting in a significant improvement in teachers’ knowledge and skills. This was evidenced by an increase of 73% between the pretest and posttest scores. Overall, the workshop has made a tangible contribution to enhancing teachers’ digital literacy and preparedness in facing the challenges of 21st-century education.
TRANSFORMASI KOMPETENSI GURU MELALUI PENGENALAN KONSEP KODING DAN KECERDASAN ARTIFISIAL PADA PEMBELAJARAN LINTAS DISIPLIN Ida Ayu Putu Febri Imawati; Ni Ketut Erawati; Luh Putu Risma Noviana; Ni Kadek Rini Purwati; I Wayan Dika
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.v4i2.5927

Abstract

A workshop was conducted to enhance digital literacy and foundational knowledge of coding and artificial intelligence (AI) among subject teachers at Denpasar 4 Public High School. The initiative addressed the need to strengthen educators' competence in integrating digital technology and AI into interdisciplinary instruction. The workshop featured interactive, hands-on sessions. Training materials included introductions to plugged-in, unplugged, and internet-based coding, fundamental AI concepts, prompt engineering for content creation, and the use of Teachable Machine for simple AI exploration. Teachers engaged in discussions and applied these concepts within their respective disciplines, including mathematics, language, and social studies. The outcomes indicated a substantial improvement in teachers' understanding of basic coding principles and the potential of AI as a creative instructional tool. The workshop also enhanced teachers' capacity to address educational challenges and advance digital transformation.
Co-Authors Ayu Aprilyana Kusuma Dewi Gde Indra Ananta Wijaya I Kadek Juni Arta I Nyoman Bagus Suweta Nugraha I Putu Eka Indrawan I Putu Eka Indrawan Eka I Wayan Dika Ida Ayu Putu Febri Imawati NI KADEK RINI PURWATI Ni Ketut Erawati Ni Made Asri Sasmita Ni Nyoman Parmithi