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ANALISIS PERFORMANCE PERANCANGAN JARINGAN FIBER OPTIC PADA RSUD WANGAYA KOTA DENPASAR DENGAN OPTISYSTEM I Nyoman Putra Maharddhika; Nyoman Putra Sastra; Dewa Made Wiharta
Jurnal SPEKTRUM Vol 9 No 2 (2022): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (606.139 KB) | DOI: 10.24843/SPEKTRUM.2022.v09.i02.p18

Abstract

The hospital information system has been regulated in Law Number 44 of 2009 concerning Hospitals. The law states that every hospital is required to record and report all hospital operations in the form of a hospital management system. In this regard, the research conducted at Wangaya Regional General Hospital, Denpasar City, aims to determine the performance calculation of the fiber optic network design at the hospital so that SIMRS implementation can be carried out optimally. This research uses Optisystem 7.0 simulation to determine the performance of network design at Wangaya Regional General Hospital, Denpasar City. Optisystem simulation with MMF OM4 cable produce a power receive value greater than allowable minimum receiver sensitivity, that is -11.1 dBm. The BER value obtained from the Optisystem simulation is less than 1x10-9 which indicates that the value has met the adequacy of the standard BER value in fiber optic networks. However, the Q-factor value obtained in the simulation is greater than the optical communication standard, that is 6. This design is feasible to implement using MMF OM4 cable from the results of testing with Optisystem simulations.
Analisis Sentimen Kata Anjay pada Media Sosial Twitter Dalam Kajian Linguistik Komputasi Yusuf Parri Akbar; Made Sri Satyawati; Nyoman Putra Sastra
Stilistika : Journal of Indonesian Language and Literature Vol 1 No 2 (2022): Volume 1 No. 2. April 2022
Publisher : Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (894.666 KB) | DOI: 10.24843/STIL.2022.v01.i02.p06

Abstract

Language serves as a means of supporting activities, ideas, and human behavior. Every form of human life can be expressed in language. Language in everyday use depends on the user and the situation of use. Because of these two things, various variations of language are used in communication. In mid-2020, Indonesia was shocked by the ban on the use of the word anjay. The purpose of this study was to determine the classification of text mining methods in filtering the word anjay, to find out how the sentence structure is in each tweet, to find out how the nuances of the meaning of the word anjay in each tweet. From the k-fold cross validation process, the average accuracy result is 50%, the precision result is 59.2%, the recall result is 47.3%, and the f-measure result is 41.2%. The word anjay is found in phrases or nouns 252 tweets, verbs 232 tweets, adjectives 187 tweets, pronouns 32 tweets, numerals 16 tweets, prepositions 12 tweets, and adverbs 11 tweets. The word anjay is found in 350 tweets of declarative sentences, 283 exclamative tweets, 78 interrogative tweets, and 31 imperative tweets. The word anjay has various interjections, including; interjection of admiration, interjection of wonder, interjection of gratitude, interjection of surprise, interjection of hope, interjection of anger, interjection of curses, and interjection of hope. In terms of nuances of meaning using redundancy, the word anjay has no influence in a sentence. The word anjay serves as an affirmation of the core of a sentence.
The Implementation of Hybrid Neuro Fuzzy Membership Function Analysis for Predicting Player Emotional Intelligence of Balinese Game Model I Nyoman Putu Suwindra; I Ketut Gede Darma Putra; Made Sudarma; Nyoman Putra Sastra
International Journal of Engineering and Emerging Technology Vol 6 No 2 (2021): July - December 2021
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

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

Abstract

This paper aims to examine the application of Neuro fuzzy membership function analysis to predict the emotions of children who like to play games. The game that has been developed is a type of game based on Balinese local wisdom, which innovates the Balinese culture-based legend I Rajapala. Rajapala who married an angel had a son named Durma. Rajapala and Durma are used as game characters that can be played on behalf of game players. Game-factor and emotional variable data were collected using a questionnaire integrated into the game system, as well as motivational data from points achieved and the use of time recorded in the game system. The data were analyzed by Sugeno Neuro Fuzzy system with hybrid and backpropagation methods. The results obtained are as follows: (1) Emotional Balinese game players can be predicted from game-factors and motivations of game players. This was shown from the FIS output (Eo) of the neuro fuzzy training analysis and the RMSE (Eo=36.8; RMSE=4.6610), the testing analysis was (Eo=33.0; RMSE=4.4528), and the checking analysis was (Eo=37.8; RMSE=4.7479) with a difference of less than 13% (training=2.72%; testing=3.0%, and checking=12.77%). In other words, if it is analyzed descriptively was (M=37.83; SD=5.3573), the output of neuro fuzzy is obtained more than 87.23%. (2) The emotional level of the child was categorized as a positive, the child's motivation was moderate and the response to the game was positive. These findings can be taken into consideration in choosing the type of game to be played in order to increase motivation and control children's emotions. Besides that, innovating games based on local wisdom is expected to preserve local Balinese culture.
LECTURERS ADMISSIONS SELECTIONS MODEL USING FUZZY K-NEAREST NEIGHBOR METHOD Lely Meilina; Nyoman Putra Sastra; Dewa Made Wiharta
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.2.740

Abstract

Higher Education, or tertiary education, is the final stage which is optional in formal education. It is usually organized in the form of a university, academy, seminary, high school, or institute. Every tertiary institution needs qualified and professional educators because they have an important role in the process of implementing the Tri Dharma of Higher Education. Recruitment for teaching staff usually has several stages and standardization of assessment in selection proces. In order for the process of selecting educators to be carried out objectively, a support system is need to carry out the assessment process. This study applies the Fuzzy K-Nearest Neighbor (FK-NN) method for the classification process in determining prospective educators who pass or not. Data classification is a new data or object grouping into classes or labels based on certain attributes. The application of the FK-NN method has several stages, namely weighting the criteria, then calculating the closeness of the test data and training data, finding the value of k-nearest neighbors between the training data and testing data and determining the membership of each data. Tests were carried out using the Confusion matrix method on several variations of the k value where the highest percentage was obtained from the value of k = 5. The test results for all k values obtained an average accuracy rate of 89.22%, 89.22% precision and 82.45% recall with 114 training data and 50 test data. Based on the average value of the test results, it can be concluded that the FK-NN method is feasible and good to use for the selection of educators with the classification of pass or not.
Domain Analysis and Audit of IT Governance Based On COBIT 5 at Denpasar Industrial Training Center I Made Artana; Nyoman Putra Sastra; Dewa Made Wiharta
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 1 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i1.55989

Abstract

Information technology has become a key element of organizations and one of institutions’ added value and competitive advantages. Therefore, IT must be properly managed and measured. Denpasar Industrial Training Center (BDI) has implemented the IT Governance Education and Training Information System, SISDIKLAT. These applications have never been evaluated from an IT governance perspective. This study aimed to determine domains and assess SISDIKLAT using methods relevant to COBIT 5. To assist the organization in focusing on its main objectives and strategies, a tailored governance system based on the specificities of SISDIKLAT is required. This research assist BDI Denpasar in establishing healthy governance and IT management by utilizing the COBIT 5 framework. Both qualitative and quantitative approaches are used to select relevant governance/management objectives. Four domains and nine subdomains were chosen based on the domain analysis. According to the assessment results, the capability value of each subdomain was 2--3, with a gap value of 0.2--0.8. To reach the target level, the nine subdomains were advised.
Spatial-temporal data imputation for predictive modeling in intelligent transportation systems Widi Prasetyo, Yohanes Pracoyo; Linawati, Linawati; Wiharta, Dewa Made; Sastra, Nyoman Putra
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 2: May 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i2.pp794-807

Abstract

Data imputation is necessary to overcome data loss in intelligent transportation systems (ITS) due to the many sensors used to monitor traffic conditions. Sensor malfunction, hardware limitations, and technical glitches can lead to incomplete data, potentially leading to errors in traffic data analysis. This analysis investigated spatial-temporal data imputation approaches applied for predictive modeling in ITS. Each approach's strengths, weaknesses, and applicability in the context of ITS are evaluated. We analyzed various imputation approaches involving statistical, machine learning, and combined methods. Statistical methods are more straightforward but could effectively handle modern traffic's complexity. On the other hand, machine learning and combined approaches, such as hybrid convolutional neural network (CNN)- long short-term memory (LSTM), offer more robust capabilities in capturing non-linear patterns present in spatio-temporal data. This research aims to investigate the effectiveness of each approach in overcoming data incompleteness and the accuracy of predicting future traffic conditions with the widespread adoption of IoT, electric vehicles, and autonomous vehicles. The results of this investigation provide an understanding of the most suitable approaches to address the challenges of spatio-temporal data imputation and provide practical guidance for predictive modeling in ITS.
KLASIFIKASI JUDUL BERITA BAHASA INDONESIA MENGGUNAKAN SUPPORT VECTOR MACHINE DAN SELEKSI FITUR MUTUAL INFORMATION I Putu Gede Hendra Suputra; Linawati; Sukadarmika, I Gede; Sastra, Nyoman Putra
Jurnal Pendidikan Teknologi dan Kejuruan Vol. 22 No. 1 (2025): Edisi Januari 2025
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jptkundiksha.v22i1.89158

Abstract

Current information and communication technology has changed the way information is shared, affecting the way people get and deliver news. The number of digital news that continues to increase every day by several news portals poses a challenge, where news is often related to more than one category. From the existing problems, a study was conducted on the classification of online news titles. This study uses the SVM method with mutual information feature selection to classify online news titles. The dataset used is the news title from detik.com using 6 categories, namely finance, travel, health, auto, food, and sport with the number of data per category being 2000 data. The classification process starts from text preprocessing, term weighting using TF-IDF, then feature selection with mutual information, and finally classification with SVM. The results of the study showed that testing various SVM kernels and mutual information (MI) thresholds with a threshold of 85% provided the highest level of F1-score on the SVM machine with the RBF kernel and a C value = 10, which was 86,15%.
Monitoring Systems for Counting People Based on Wireless Multimedia Sensor Network Rantelobo, Kalvein; Sampeallo, Agusthinus; Mandala, J. F.; Lami, H. F. J.; Bernandus, B.; Rantelinggi, P. H.; Sastra, N. P.
Jurnal Media Elektro Vol 14 No 1 (2025): April 2025
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jme.v13i2.10214

Abstract

The visual sensor used in the Wireless Sensor Multimedia Networks (WSMN) in this work aims to monitor and calculate the number of people passing through a room. The contribution of this paper is the use of Raspberry Pi 3 devices that are connected to the internet using Internet-of-Thing (IoT) technology. The proposed scheme can be implemented in the actual environment. From the test results, the system has distinguished people entering and leaving the room by doing image processing using background subtraction, morphological transformation method, and calculating the contour area of the image. The results of image processing can calculate the number of people in the room, and the system can send it to the web server. Subsequently, this paper discussed the energy consumption used by the WSMN and explained test parameters.
Monitoring Systems for Counting People Based on Wireless Multimedia Sensor Network Rantelobo, Kalvein; Sampeallo, Agusthinus; Mandala, J. F.; Lami, H. F. J.; Bernandus, B.; Rantelinggi, P. H.; Sastra, N. P.
Jurnal Media Elektro Vol 14 No 1 (2025): April 2025
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jme.v13i2.10214

Abstract

The visual sensor used in the Wireless Sensor Multimedia Networks (WSMN) in this work aims to monitor and calculate the number of people passing through a room. The contribution of this paper is the use of Raspberry Pi 3 devices that are connected to the internet using Internet-of-Thing (IoT) technology. The proposed scheme can be implemented in the actual environment. From the test results, the system has distinguished people entering and leaving the room by doing image processing using background subtraction, morphological transformation method, and calculating the contour area of the image. The results of image processing can calculate the number of people in the room, and the system can send it to the web server. Subsequently, this paper discussed the energy consumption used by the WSMN and explained test parameters.
Multi-Document Summarization Using Tuna Swarm Optimization and Markov Clustering Widiartha, I Made; Hartati, Rukmi Sari; Wiharta, Dewa Made; Sastra, Nyoman Putra; Astuti, Luh Gede
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.3365

Abstract

The Internet contains a large number of documents from various sources with similar content. The contents of documents that are almost identical will lead to news redundancy, making it difficult for readers to distinguish between factual information and opinions. Multi-document summarization has been designed to enable readers to easily understand the meaning of news documents without needing to read multiple documents. Multi-document summarization aims to extract information from several texts written about the same topic. The resulting summary report enables users to obtain a single piece of information from multiple similar pieces of information sourced from various locations. Various approaches have been used in creating multi-document summaries. Issues regarding accuracy and redundancy are still a significant focus of research. In this paper, a new multi-document summarization model was built using Tuna Swarm Optimization (TSO) and Markov Clustering (MCL) methods. The dataset of this research is Indonesian language news from various online media sources. Based on hyperparameter tuning using training data, the best TSO model performance was obtained at variable values a = 0.7, z = 0.9, and the optimal number of tuna fish > 80. From the research results, it was found that TSO outperformed other swarm intelligence methods. The use of MCL has proven to be effective, as evidenced by the performance results, where TSO achieved an average ROUGE value 7.95% higher when MCL was applied. In this performance test, four standard evaluation metrics of the ROUGE toolkit were used.
Co-Authors A.A Ngurah Amrita Aceng Sambas Adhitya Bayu Rachman Pratama Afrizal Awlan Suryandaru agung aditya nugraha Agus Riki Gunawan Agus Supranartha Agusthinus Sampeallo, Agusthinus Anak Agung Bagus Rama Windhu Putra Anggreni, Ni Komang Ayu Sri Ari Wijaya I Kadek Ari Wilani, Ni Made Asri Prameshwari Bayu Bimantara Putra Bernandus, B. Cokorda Gde Wahyu Pramana Dewa Made Wiharta dian krisnandari Duman Care Khrisne Dwi Yoga Pratama Fajar Purnama firmansyah maualana sugiartana nursuwars G M Arya Sasmita Gamantyo Hendrantoro Gede Sukadarmika Gusti Ketut Bella I G. A. K. Diafari Djuni Hartawan I Gede Primanata I Gede Wira Darma I Gede Yogi Prawira Putra I Gusti Ayu Garnita Darma Putri I Gusti Ngurah Aditya Dharma I ketut Gede Darma Putra I Ketut Sukawanana Putra I Made Agung Pranata I Made Agus Setiawan I Made Arsa Suyadnya I Made Artana I Made Oka Widyantara I Made Rai Suarimbawa I Made Sastra Dwikiarta I MADE SUDARMA I Made Sukarsa I Made Widiartha I Nyoman Putra Maharddhika I Nyoman Putu Suwindra I Putu Agus Eka Darma Udayana, I Putu Agus Eka I Putu Aldha Rasjman Sayoga I Putu Arie Pratama I Putu Gede Hendra Suputra I Putu Suryadharma I Wayan Adi Juliawan Pawana I Wayan Krisna Saputra I Wayan Manik Suhartanta Ida Bagus Adisimakrisna Peling Ida Bagus Vidananda Agastya IGN. Agung Dwi Jaya Putra K.O. Saputra Kessawa Adnyana Gede Oka Anak Agung Ketut Adi Kurniawan Kheri Arionadi Shobirin Komang Oka Saputra Komang Sri Utami Komang Tania Paramecwari Komang Yuda Krisnawan Lami, H. F. J. Lely Meilina Lie Jasa Linawati Linawati . Linawati Linawati Luh Ayu Diah Fernita Sari Luh Gede Astuti M Sudarma M. A. Suyadnya M. Azman Maricar Made Pasek Agus Ariawan Made Sri Satyawati Made Sudarma Made Sutha Yadnya Mandala, J. F. Michael Angelo Vincensio Simon Muhammad Anshari Muhammad Anshari Naufal Muhajir Abidin Negara, I Putu Bayu Negara, I Putu Bayu Ni Komang Ayu Sri Anggreni Ni Komang Utari Yulianingsih Ni Made Ary Esta Dewi Wirastuti Ni Putu Diah Arista Ningsih Nicko Satrio Pambudi Nurulita Aini Nyoman Pramaita Putra, A.A.B. Rama Windhu Putra, Rio Juniyantara Putu Andhika Kurniawijaya Putu Dhiko Pradnyana Rantelinggi, P. H. Rifky Lana Rahardian Rio Juniyantara Putra Rukmi Sari Hartati Rukmi Sari Hartati Sari, Luh Ayu Diah Fernita Sukadarmika, I Gede Widyadi Setiawan Wirawan Wirawan Yohanes Hendra Nugroho Yohanes Pracoyo Widi Prasetyo Yusuf Parri Akbar