Claim Missing Document
Check
Articles

Found 19 Documents
Search

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.
Comparative Performance Analysis of Modified VGG16 and Slim-CNN for Arabica Coffee Bean Defect Classification Ardian, Yusriel; Astawa, I Nyoman gede Arya; Irawan, Novta Danyel; Pradnyana, I Putu Bagus Arya; Sulistyo, Agung
ILKOM Jurnal Ilmiah Vol 18, No 1 (2026)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v18i1.3244.85-96

Abstract

Defect detection in Arabica coffee beans is a critical aspect of quality control, particularly for export-oriented commodities that require consistent visual standards and uniform quality across production batches. Black and partial-black defects are known to significantly affect market value, quality perception, and sensory characteristics. Meanwhile, manual inspection processes remain vulnerable to evaluator subjectivity and inter-operator inconsistency.This study aims to conduct a comparative analysis between a Modified VGG16 architecture and Slim-CNN for detecting these two defect categories using a deep learning-based Convolutional Neural Network (CNN) approach. The dataset consists of 4,080 high-resolution images of Arabica green coffee beans captured using a 24.2 MP macro camera under controlled lighting conditions to minimize shadows and visual distortion. To preserve the natural characteristics of the defects, minimal data augmentation was applied using cropping and 15-degree rotation techniques. The Modified VGG16 architecture was simplified by reducing the complexity of the fully connected layers, integrating batch normalization, and applying dropout to enhance training stability and computational efficiency. Slim-CNN was employed as a lightweight comparative model with fewer parameters and lower memory requirements, making it suitable for resource-constrained deployment scenarios. Four training schemes were evaluated using variations in learning rate and epoch number to assess configuration impacts on performance. Experimental results show that Modified VGG16 achieved the highest test accuracy of 86.7% at a learning rate of 0.001 with 3 epochs, demonstrating a strong balance between training and validation accuracy. Slim-CNN exhibited shorter training time and lower computational complexity, although with slightly lower classification accuracy compared to Modified VGG16. These findings highlight a trade-off between classification performance and computational efficiency in selecting CNN architectures for coffee bean defect detection. Although the results demonstrate potential for industrial automatic classification systems, further validation using larger datasets and more comprehensive evaluation schemes is required to improve model generalization. This study contributes to the development of a more measurable, adaptive, and efficient deep learning-based coffee quality inspection system to support agro-export industry requirements.
IMPLEMENTASI CCTV ONLINE UNTUK MENINGKATKAN PEMANTAUAN FASILITAS WARGA BANJAR SAMPALAN Rudiastari, Elina; Ari Dwi Suta Atmaja, I Made; Bagus Catur Bawa, I Gusti Ngurah; Triana Indah, Komang Ayu; Ayu Sukerti, Gusti Nyoman; Arya Astawa, I Nyoman Gede
Jurnal Praksis dan Dedikasi Sosial Vol. 7 No. 1 (2024)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

IMPLEMENTATION OF ONLINE CCTV TO IMPROVE MONITORING OFBANJAR SAMPALAN RESIDENTS' FACILITIES Sampalan Hamlet is a tourist destination where many facilities and infrastructure have begun to be built. The problems faced by the Sampalan Traditional Banjar are that there is no supervision of the routes around the Banjar area, there is no documentary evidence that can be used to analyze accidents that occur around the Banjar, there is no supervision to avoid acts of theft at the temple and there is no supervision of the social activities of residents which was carried out in Banjar. The solution offered in this community service activity for the problems experienced is the installation of CCTV. This service activity aims to help access monitoring and supervision of the Banjar area to increase the security and comfort of residents and visiting tourists. This method of implementing community service activities is implemented into three main stages, namely preparation, implementation and evaluation. The results of the evaluation through a questionnaire resulted in 71.4 percent of residents stating that the installed CCTV was very useful, and 50 percent of residents stated that the presence of CCTV greatly facilitated monitoring and supervision around the Banjar. Dusun Sampalan merupakan destinasi wisata dimana fasilitas serta infrastruktur sudah mulai banyak dibangun. Permasalahan yang dihadapi Banjar Adat Sampalan yaitu belum adanya pengawasan terhadap jalur disekitar areal Banjar, tidak adanya bukti dokumentasi yang dapat digunakan untuk menganalisa peristiwa kecelakaan yang terjadi di sekitar Banjar, tidak adanya pengawasan untuk menghindari tindakan pencurian di pura serta tidak adanya pengawasan terhadap aktivitas sosial warga yang dilakukan di Banjar. Solusi yang ditawarkan dalam kegiatan pengabdian kepada masyarakat ini untuk permasalahan yang dialami adalah pemasangan CCTV. Tujuan dari kegiatan pengabdian ini adalah membantu akses monitoring dan pengawasan areal Banjar sehingga meningkatkan keamanan dan kenyamanan warga serta wisatawan yang berkunjung. Metode pelaksanaan kegiatan pengabdian kepada masyarakat ini diimplementasikan menjadi tiga tahapan utama yaitu persiapan, pelaksanaan dan evaluasi. Hasil evaluasi melalui kuisioner menghasilkan 71,4 persen warga menyatakan CCTV yang terpasang tersebut sangat bermanfaat serta 50 persen warga menyatakan bahwa adanya CCTV sangat mempermudah monitoring dan pengawasan di sekitar Banjar.
Peningkatan jalur komunikasi perangkat desa dalam bentuk perluasan akses hotspot pada kantor Desa Sibetan, Kecamatan Bebandem, Kabupaten Karangasem Sukerti, Gusti Nyoman Ayu; Atmaja, I Made Ari Dwi Suta; Bawa, I Gusti Ngurah Bagus Catur; Indah, Komang Ayu Triana; Rudiastari, Elina; Astawa, I Nyoman Gede Arya
Jurnal Praksis dan Dedikasi Sosial Vol. 8 No. 1 (2025)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um022v8i12025p97-106

Abstract

Improving communication channels for village officials by expanding hotspot access in the Sibetan Village administration, Bebandem Subdistrict, Karangasem Regency Sibetan Village is one of the villages located in the Bebandem Subdistrict, Karangasem Regency. Based on survey results, Sibetan Village faces limited access to the internet and hotspots, which slows down administrative processes and public services at the village office. The village officials also experience difficulties in accessing fast and accurate information. In response to these issues, the Computer Network Administration Study Program from the Information Technology Department carried out a community service activity on May 28-29, 2024. The activity involved expanding the hotspot network around the village office to cover a wider area and provide stable and fast Internet access. Additionally, the village officials were trained on the management and maintenance of the hotspot network. The purpose of this activity was to improve communication capabilities and information access for village officials and the general public, making public services in Sibetan Village more effective. The activity was evaluated through user satisfaction surveys using questionnaires and interviews. Based on the survey results from 50 respondents, 50 percent stated that the initiative was implemented appropriately, and 60 percent reported that the expansion of the hotspot made it easier for village officials, especially in administrative services. Interviews with the Head of Sibetan Village indicated that the village officials felt supported by the hotspot expansion initiative. Desa Sibetan merupakan salah satu desa yang terletak di Kecamatan Bebandem, Kabupaten Karangasem. Berdasarkan hasil survei yang dilakukan, Desa Sibetan memiliki keterbatasan akses internet dan hospot sehingga memperlambat proses administrasi dan pelayanan publik di kantor desa serta perangkat desa mengalami kesulitan dalam mengakses informasi yang cepat dan akurat. Mengacu pada permasalahan tersebut, Program Studi Administrasi Jaringan Komputer Jurusan Teknologi Informasi melakukan kegiatan pengabdian masyarakat yang dilaksanakan pada pada tanggal 28-29 Mei 2024 dalam bentuk perluasan jaringan hotspot di sekitar kantor desa untuk mencakup area yang lebih luas dan menyediakan akses internet yang stabil dan cepat. Selain itu, perangkat desa diberikan pelatihan terkait pengelolaan dan pemeliharaan jaringan hotspot. Tujuan dari kegiatan ini adalah meningkatkan kemampuan komunikasi dan akses informasi bagi perangkat desa serta masyarakat secara umum serta layanan publik di Desa Sibetan menjadi lebih efektif. Evaluasi kegiatan ini dilakukan dengan survei kepuasan pengguna menggunakan kuisioner serta wawancara. Berdasarkan hasil survei kepuasan pengguna terhadap 50 responden, 50 persen menyatakan kegiatan sudah diimplementasikan secara tepat serta 60 persen menyatakan adanya perluasan hotspot mempermudah kinerja perangkat desa terutama dalam hal pelayanan administrasi. Hasil wawancara terhadap Kepala Desa Sibetan menyatakan bahwa perangkat desa merasa terbantu dengan diadakannya kegiatan perluasan hotspot ini.