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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Register: Jurnal Ilmiah Teknologi Sistem Informasi JOIV : International Journal on Informatics Visualization Knowledge Engineering and Data Science WIDYA LAKSANA Logic : Jurnal Rancang Bangun dan Teknologi Jurnal Praksis dan Dedikasi Sosial Journal of Applied Data Sciences Pusaka : Journal of Tourism, Hospitality, Travel and Business Event Dharma: Jurnal Pengabdian Masyarakat
I Nyoman Gede Arya Astawa
Politeknik Negeri Bali
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Environmental Science Languange, Linguistic, Communication & Media Social Sciences Other

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APLIKASI DIGITALISASI LAYANAN SURAT-MENYURAT UNTUK MENINGKATAN LAYANAN ADMINISTRASI KANTOR DESA Astawa, I Nyoman Gede Arya; Manuaba, Ida Bagus Putra; Atmaja, I Made Ari Dwi Suta Atmaja; Sukarata, I Putu Gde
JURNAL WIDYA LAKSANA Vol 12 No 2 (2023)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jwl.v12i2.61871

Abstract

Pelayanan surat-menyurat merupakan bagian dari kualitas kinerja pemerintah desa, dengan memberikan pelayanan surat-menyurat yang efektif dan efisien mampu meningkatkan kepuasan masyarakat terhadap administrasi desa. Saat ini pengelolaan pengajuan pembuatan surat-menyurat khususnya surat keterangan di Kantor Desa Adat Sibetan masih dilakukan dengan cara konvensional, sehingga menyebabkan beberapa permasalahan yang muncul. antara lain: proses pengajuan yang memerlukan waktu relatif lama, pengecekan status surat yang tidak efektif, data penduduk yang tidak terdokumentasi dengan baik. Untuk mengatasi permasalahan tersebut kegiatan pengabdian difokuskan pada pembuatan aplikasi digitalisasi surat-menyurat pada Kantor Desa Sibetan. Setelah aplikasi siap dan dihosting pada website maka dilakukan sosialisasi kepada warga Desa Sibetan. Evaluasi dari pengabdian masyarakat ini dilakukan dengan dua cara, pertama adalah mengevaluasi website menggunakan aplikasi tool yaitu Pagespeed Insights dan evaluasi kedua adalah evaluasi kebermanfaatan dan output hasil surat-menyurat menggunakan kuisioner. Hasil evaluasi pertama menunjukkan nilai diagnosa kinerja bila dijalankan pada dekstop rata-rata sebesar 92,25 dan pada perangkat mobile/smartphone adalah rata sebesar 81,5. Evaluasi kedua menggunakan kuisioner yang diisi oleh peserta dalam sosialisasi menunjukkan bahwa aplikasi layanan surat-menyurat sangat bermanfaat dan bila diimplementasikan sangat mudah digunakan dan sangat efesien dalam mengurus surat-surat di Kantor Desa Sibetan.
Green Accounting Practice Model for Tourism Villages in Support of Sustainable Tourism in Bali Astawa, I Putu; Arya Astawa, I Nyoman Gede; Ardina, Cening; Novandra Asta, Ngr. Putu Raka
Pusaka : Journal of Tourism, Hospitality, Travel and Business Event Vol. 7 No. 1 (2025): February-Juli
Publisher : Politeknik Pariwisata Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33649/padaidi.v1i2.344

Abstract

Tourism is currently in the spotlight because the massive use of natural resources is rumored to damage the order of life in the future. Various efforts are made for tourism business actors to maintain sustainability so that this nature remains sustainable. Information on sustainability activities is very important to be known by all parties to legitimize the implementation of sustainability. This research provides information on the implementation of sustainability practices in tourist villages with the main objective of designing a financial transaction model based on green accounting practices that have not been widely practiced in a tourist destination in the village. A qualitative approach was used to dig deeper into the data from five informants of tourist village managers who have implemented sustainability. The results of the study explain that transactions related to the environment are recorded, recognition of costs incurred, measurement, recording to accounts, then presented and detailed disclosure of environmental costs. In addition, it was found that environmental prevention costs, environmental detection costs and internal failure costs in strengthening sustainable tourism. The results of the study contribute to accounting science in revealing an environmental cost aimed at supporting sustainable tourism. This condition is a new way of maintaining sustainability oriented on financial transactions. This research can be developed quantitatively in strengthening the green accounting model associated with sustainable tourism.
Ontology Modeling for Subak Knowledge Management System Hariyanti, Ni Kadek Dessy; Linawati, Linawati; Oka Widyantara, I Made; Sukadarmika, Gede; Arya Astawa, I Nyoman Gede; Kamarudin, Nur Diyana
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.3386

Abstract

Subak, as a Balinese traditional agricultural organization, has knowledge of cultural heritage, including both explicit and tacit elements. This research aimed to develop ontology knowledge model for the digital preservation of Subak culture in the form of Knowledge Management System (KMS). The development of model was based on three main stages, including requirement analysis, ontology development, and ontology assessments. Requirement analysis included data collection through field observations, in-depth interviews, and document analysis, while ontology development consisted of hierarchical classes, object and data properties, as well as individual entities. Furthermore, ontology assessments were the stage of evaluating and testing the resulting ontology. Protégé software was used to apply ontology model, generating Ontograph visualizations and producing Ontology Web Language (OWL). Validation was carried out using both Ontology Quality Analysis (OntoQA) and expert comments. The evaluation results showed a Relationship Richness (RR) value of 0.8, an Inheritance Richness (IR) value of 0.78, and an Attribute Richness (AR) value of 3.89, showing that ontology captured a comprehensive and representative body of knowledge. Expert comments stated that ontology model created was worthy of being used to represent Subak knowledge as a form of cultural preservation. The developed Subak ontology could serve as a foundational knowledge base for further research in related fields such as agricultural management, social organization, and cultural preservation.
Multilingual Parallel Corpus for Indonesian Low-Resource Languages Sulistyo, Danang Arbian; Wibawa, Aji Prasetya; Prasetya, Didik Dwi; Ahda, Fadhli Almu’iini; Arya Astawa, I Nyoman Gede; Andika Dwiyanto, Felix
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.3412

Abstract

Indonesia has an extraordinary number of languages, with more than 700 regional languages such as Javanese, Madurese, Balinese, Sundanese, and Bugis. Despite the wealth of languages, digital resources for these languages remain scarce, making the preservation and accessibility of digital languages a significant challenge. Research was conducted to address this gap by building a multilingual parallel corpus consisting of more than 150,000 phrase pairs extracted from Bible translations in five regional languages in Indonesia. Rigorous preprocessing, normalization, and Unicode tokenization were performed to improve data quality and consistency. The encoder-decoder architecture was a key focus in the development of the NMT model. Evaluation focused on forward and backward translation directions, which were measured using BLEU scores. The results show that forward translation consistently outperforms backward translation. The Indonesian Javanese model produced a score of 0.9939 for BLEU-1 and 0.9844 for BLEU-4, indicating a high level of translation quality. In contrast, reverse translation tasks, such as translating from Sundanese to Indonesian, presented significant challenges, with BLEU-4 scores as low as 0.3173. This illustrates the complexity of the translation system from Indonesian to local languages. If future research focuses on transformer-based models and incorporates additional linguistic parameters to enhance the accuracy of natural language processing (NLP) models for Indonesia's underrepresented regional languages, this work provides a dataset that can be utilized for that purpose.
Facemask Detection using the YOLO-v5 Algorithm: Assessing Dataset Variation and R esolutions Kurniawan, Fachrul; Astawa, I Nyoman Gede Arya; Atmaja, I Made Ari Dwi Suta; Wibawa, Aji Prasetya
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 2 (2023): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i2.3249

Abstract

The Covid-19 pandemic has made it imperative to prioritize health standards in companies and public areas with a large number of people. Typically, officers oversee the usage of masks in public spaces; however, computer vision can be employed to facilitate this process. This study focuses on the detection of facemask usage utilizing the YOLO-v5 algorithm across various datasets and resolutions. Three datasets were employed: the face with mask dataset (M dataset), the synthetic dataset (S dataset), and the combined dataset (G dataset), with image resolutions of 320 pixels and 640 pixels, respectively. The objective of this study is to assess the accuracy of the YOLO-v5 algorithm in detecting whether an individual is wearing a mask or not. In addition, the algorithm was tested on a dataset comprising individuals wearing masks and a synthetic dataset. The training results indicate that higher resolutions lead to longer training times, but yield excellent prediction outcomes. The system test results demonstrate that face image detection using the YOLO-v5 method performs exceptionally well at a resolution of 640 pixels, achieving a detection rate of 99.2 percent for the G dataset, 98.5 percent for the S dataset, and 98.9 percent for the M dataset. These test results provide evidence that the YOLO-v5 algorithm is highly recommended for accurate detection of facemask usage.
Combination of Feature Extractions for Classification of Coral Reef Fish Types Using Backpropagation Neural Network Latumakulita, Luther Alexander; Arya Astawa, I Nyoman Gede; Mairi, Vitrail Gloria; Purnama, Fajar; Wibawa, Aji Prasetya; Jabari, Nida; Islam, Noorul
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.3.1082

Abstract

Feature extraction is important to obtain information in digital images, where feature extraction results are used in the classification process. The success of a study to classify digital images is highly dependent on the selection of the feature extraction method used, from several studies providing a combination of feature extraction solutions to produce a more accurate classification.  Classifying the types of marine fish is done by identifying fish based on special characteristics, and it can be through a description of the shape, fish body pattern, color, or other characteristics. This study aimed to classify coral reef fish species based on the characteristics contained in fish images using Backpropagation Neural Network (BPNN) method. Data used in this research was collected directly from Bunaken National Marine Park (BNMP) in Indonesia. The first stage was to extract shape features using the Geometric Invariant Moment (GIM) method, texture features using Gray Level Co-occurrence Matrix (GLCM) method, and color feature extraction using Hue Saturation Value (HSV) method. The third value of feature extraction was used as input for the next stage, namely the classification process using the BPNN method. The test results using 5-fold cross-validation found that the lowest test accuracy was 85%, the highest was 100%, and the average was 96%. This means that the intelligent model derived from the combination of the three feature extraction methods implemented in the BPNN training algorithm is very good for classifying coral reef fish.
Co-Authors Aji Prasetya Wibawa Andika Dwiyanto, Felix Ardina, Cening Atmaja, I Made Ari Dwi Suta Atmaja, I Made Ari Dwi Suta Atmaja Bawa, I Gusti Ngurah Bagus Catur Dessy Hariyanti, NK Didik Dwi Prasetya Dwiyanto, Felix Andika Fachrul Kurniawan Fadhli Almu’iini Ahda Fajar Purnama Felipe P. Vista IV Felix Andika Dwiyanto Frangky J. Paat Gede Sukadarmika Gusti Nyoman Ayu Sukerti Gusti Nyoman Ayu Sukerti, Gusti Nyoman Ayu I Dewa Gede Ary Subagia I ketut Gede Darma Putra I Made Oka Widyantara I MADE SUDARMA I Putu Astawa I Putu Bagus Arya Pradnaya I Putu Bagus Arya Pradnyana I Putu Sutawinaya I Wayan Budi Sentana I Wayan Raka Ardana I Wayan Suasnawa I Wayan Suasnawa Ida Bagus Putra Manuaba IGAK Cathur Adhi Irawan, Novta Danyel Islam, Noorul Jabari, Nida Kamarudin, Nur Diyana Karim, Irwan Komang Ayu Triana Indah Linawati Linawati Luther Latumakulita Mairi, Vitrail Gloria Ngr. Putu Raka Novandra Asta Purnama, Ida Bagus Irawan Putu Gde Sukarata Radhitya, Made Leo Rudiastari, Elina Rukmi Sari Hartati Saroyo Saroyo Sirait, Hasanuddin Sukarata, I Putu Gde Sulistyo, Danang Arbian Sutoko, Sutoko Triadi, Wilfridus Bambang Yusriel Ardian