Article Per Year (5 Year)
p-Index From 2021 - 2026
4.612
P-Index
This Author published in this journals
All Journal Jurnal Pendidikan Teknologi dan Kejuruan KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) ISSN: 2252-9063 E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Elkom: Jurnal Elektronika dan Komputer JUTIK : Jurnal Teknologi Informasi dan Komputer WIDYABHAKTI Jurnal Ilmiah Populer Journal on Education Jurnal Review Pendidikan dan Pengajaran (JRPP) Journal of Computer System and Informatics (JoSYC) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Riset dan Inovasi Pembelajaran ARRUS Journal of Engineering and Technology Jurnal Mandiri IT Naratif : Jurnal Nasional Riset, Aplikasi dan Teknik Informatika Brilliance: Research of Artificial Intelligence KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Jurnal Ilmiah Manajemen, Bisnis dan Kewirausahaan Prosiding University Research Colloquium Smart Techno (Smart Technology, Informatic and Technopreneurship) Journal of Artificial Intelligence and Digital Business Jurnal Ilmiah Teknik Informatika dan Komunikasi Innovative: Journal Of Social Science Research Rechtsnormen Journal of Law GEMBIRA (Pengabdian Kepada Masyarakat) Jurnal SUTASOMA Journal of Engineering and Science Application JIS Siwirabuda (Jurnal Ilmiah Sains Sosial, Kewirausahaan dan Kebudayaan) KOMTEKS: Komputer dan Teknologi Sains
ABDI SUDIATMIKA, I PUTU GEDE
Institut Teknologi Dan Bisnis STIKOM Bali
Religion Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences Other

Published : 41 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 41 Documents
Search

 1   2   3   4   5 
Sistem Informasi Manajemen Komunitas Berbasis Web (Studi Kasus: Itb Stikom Bali Kampus Jimbaran) Saputra, I Gede Seri Dharma Bobby; Setiawan, I Made Oka Adi; Sudiatmika, I Putu Gede Abdi; Pramartha, Nyoman Bagus; Artana, Wayan Widya
Jurnal SUTASOMA (Science Teknologi Sosial Humaniora) Vol 2 No 2 (2024): Juni 2024
Publisher : Universitas Tabanan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58878/sutasoma.v2i2.288

Abstract

ITB STIKOM Bali Community Jimbaran Campus is a forum for students to channel their talents and interests. Each Community has one coordinator who functions to manage members from each community. To facilitate the work of each coordinator in managing member data, activities and events, good management is needed. Management is a process in which a person can manage everything that is done by individuals or groups. The purpose of this research is to build a Web-Based Community Management Information System that can manage member data, activities and events from each community and make it easier for students to find information about the communities they participate in. In designing and building this system, the author uses the PHP programming language with the CodeIgniter framework. The design method used is the waterfall method starting from the system analysis stage and system design. The results obtained after doing blackbox testing on the system that has been made show that the functional system is running well. The results of the questionnaire from the user side of the Web-Based Community Management Information System get a percentage of a total of 86% which is categorized as "Very Good" with a total average value of 4.3 which means very good in implementing the system from 36 respondents' answers, while in terms of The admin on the Web-Based Community Management Information System gets a percentage of 79% in total which is categorized as "Good" with a total average value of 3.95 which means good in implementing the system from 10 respondents' answers.  
The Influence of Blockchain Technology on Civil Law Enforcement in the Digital Era Wiratama, Febri; Fakhriah, Syahriati; Palit, Silvester Magnus Loogman; Sudiatmika, I Putu Gede Abdi; Tanjung, Rona
Rechtsnormen: Journal of Law Vol. 2 No. 3 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/rjl.v2i3.1410

Abstract

Background: Blockchain technology has emerged as a revolutionary tool with the potential to transform various sectors, including civil law enforcement. Its decentralized, transparent, and immutable nature offers new possibilities for enhancing legal processes, ensuring data integrity, and reducing fraud. Objective: This study aims to evaluate the influence of blockchain technology on civil law enforcement. The research focuses on understanding how blockchain can enhance legal processes, improve data security, and foster transparency within the civil law system. Methods: A mixed-methods approach was employed, combining quantitative surveys and qualitative interviews. Quantitative data were collected from 200 legal professionals and law enforcement officers, measuring their perceptions of blockchain's impact on various legal processes. Qualitative interviews with 30 key stakeholders provided deeper insights into blockchain's practical applications and challenges in civil law enforcement.. Results: Findings indicate that blockchain technology can significantly enhance data security, transparency, and efficiency in civil law enforcement. Best practices identified include the use of smart contracts for automated enforcement and blockchain for secure evidence management. Challenges such as technical complexity, cost, and legal interoperability were also highlighted. Conclusion: Blockchain technology holds significant promise for improving civil law enforcement by enhancing transparency, security, and efficiency. Implementing best practices can optimize these benefits, although challenges remain.
ANALISIS VISUAL TENTANG POLA KEBAKARAN HUTAN: STUDI KASUS MENGGUNAKAN DATA INDEKS CUACA DAN AREA TERBAKAR Putu Satya Saputra; I Putu Gede Abdi Sudiatmika; I Putu Astya Prayudha
Jurnal Teknologi Informasi dan Komputer Vol. 10 No. 3 (2024): Jurnal Teknologi Informasi dan Komputer
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v10i3.3458

Abstract

Kebakaran hutan menyebabkan kerugian yang signifikan dalam bentuk kerusakan habitat, emisi gasrumah kaca, hilangnya kehidupan satwa liar, dan bahkan hilangnya nyawa manusia. Untuk mengurangirisiko kebakaran hutan, sangat penting untuk memahami faktor-faktor yang mempengaruhinya. Kondisicuaca, seperti kelembaban, suhu, kekeringan, dan kecepatan angin, dikenal sebagai faktor utama yangmemengaruhi kebakaran hutan. Oleh karena itu, analisis visual terhadap pola kebakaran hutanmenggunakan data indeks cuaca dapat memberikan wawasan yang berharga. Indeks kebakaran hutan,seperti FFMC, DMC, DC, dan ISI, telah dikembangkan untuk memprediksi risiko kebakaran hutan.Indeks-indeks ini mengukur kelembaban bahan bakar, kekeringan, dan penyebaran awal kebakaran.Namun, ada kebutuhan untuk memahami lebih dalam bagaimana indeks-indeks ini berkorelasi denganpola kebakaran hutan sebenarnya. Data tentang kebakaran hutan, termasuk lokasi, waktu, dan luas areaterbakar, tersedia dalam berbagai dataset. Analisis visual terhadap data ini dapat membantu dalammengidentifikasi pola-pola spasial dan temporal dari kebakaran hutan, serta korelasinya dengan faktorfaktor cuaca. Visualisasi data memainkan peran kunci dalam memahami pola-pola yang kompleks dalamdataset besar. Dengan menggunakan teknik visualisasi yang tepat dapat mengidentifikasi tren, anomali,dan pola-pola yang tidak terlihat secara langsung melalui analisis statistik. Penelitian ini bertujuan untukmenganalisis visual pola kebakaran hutan dengan menggunakan data indeks cuaca dan area terbakar.Hasil penelitian ini diharapkan dapat memberikan pemahaman yang lebih dalam tentang hubunganantara kondisi cuaca dan kebakaran hutan. Informasi yang diperoleh dapat digunakan untukmeningkatkan pemahaman tentang risiko kebakaran hutan serta mengembangkan strategi yang lebihefektif dalam mitigasi bencana kebakaran hutan.
The Implementation of Gated Recurrent Unit (GRU) for Gold Price Prediction Using Yahoo Finance Data: A Case Study and Analysis Sudiatmika, I Putu Gede Abdi; Putra , I Made Agus Widiana; Artana, Wayan Widya
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.3865

Abstract

Gold is a precious metal resistant to corrosion and oxidation, highly valued in investment and trade. Currently, the demand for gold is increasing as it is considered a safe haven. This is evidenced by 48% of respondents out of 2,333 respondents choosing gold as the most preferred investment, based on a survey conducted by Jakpat. However, gold actually has a fluctuating price. The fluctuating price of gold worldwide is influenced by many factors such as economic conditions, inflation rate, supply and demand of gold, and the US dollar exchange rate. Therefore, there is a need for a prediction that can estimate the price of gold based on the movement of gold prices in previous periods. In this study, an evaluation of the performance of GRU for predicting the price of gold will be conducted.. The research methodology includes data collection and processing of gold prices, application of the GRU model, and evaluation of model performance with evaluation metrics such as Mean Squared Error (MSE) and Mean Absolute Error (MAE). Gold price data is taken from Yahoo Finance from December 14, 2017, to March 14, 2024, and processed through normalization and data splitting into training and testing sets. The results of the study show that the GRU model is able to predict gold prices with an adequate level of accuracy. Based on the MSE and MAE values, the combination that provides the best performance is a batch size of 64 with 100 epochs, as it yields the lowest MSE and MAE.
AI-Based Tourist Guide Application in Bali Using Supervised Learning Method I Gusti Ngurah, Putra Arimbawa; I Made Dwi Darma Artanaya; Komang Ayu Krisna Dewi; I Putu Gede Abdi Sudiatmika
ARRUS Journal of Engineering and Technology Vol. 4 No. 2 (2024)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/jetech3262

Abstract

Penelitian ini berfokus pada pengembangan aplikasi panduan wisata berbasis Kecerdasan Buatan (AI) dengan metode Supervised Learning untuk wisatawan di Bali. Urgensi penelitian ini didasari oleh kebutuhan akan panduan yang terstruktur dan kontekstual bagi wisatawan untuk menghindari pelanggaran norma dan adat istiadat setempat, yang sering terjadi karena kurangnya informasi. Tujuan penelitian adalah untuk menciptakan aplikasi yang dapat memberikan rekomendasi aktivitas "to do" dan "not to do" berdasarkan lokasi, preferensi, dan norma setempat di Bali. Metode yang digunakan meliputi pengumpulan data teks dan gambar terkait budaya, tradisi, dan aturan adat di Bali, yang kemudian digunakan untuk melatih model AI menggunakan Supervised Learning. Model ini akan dikembangkan dan diintegrasikan ke dalam aplikasi mobile. Aplikasi ini diharapkan mampu memberikan informasi dan rekomendasi wisata yang tepat, serta panduan terkait norma dan adat istiadat Bali, untuk meningkatkan pengalaman wisatawan dan menjaga kehormatan budaya lokal.
Pengembangan Aplikasi E-Tourism Pada Museum Berbasis Android Studi Kasus Museum Subak Tabanan Pradipta, I Made; I Putu Gede Abdi Sudiatmika; Komang Hari Santhi Dewi
Elkom: Jurnal Elektronika dan Komputer Vol. 17 No. 2 (2024): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v17i2.2265

Abstract

One of the museums found in Bali is Subak museum in Tabanan Regency. The establishment of this Museum aims to preserve the traditional institution called Subak as a noble national cultural heritage, and to introduce to the younger generation and foreign tourists about the unique traditional irrigation system in Bali. Lack of supporting facilities in delivering information, making tourists who visit Subak Museum have minimal information. The solution needed in Subak museum is an Android-based E-Tourism application that is supported by Qr-Code technology so as to provide an interesting presentation of data. In making this application using the development of the Waterfall method and designed using the Unified Modeling Language (UML) with the Java programming language for Android and PHP for web services, and MySQL as a database. So that produced an android-based system in Subak museum Tabanan Regency. Based on the results of the tests carried out it can be concluded that the black box testing system functions have been running according to the planning. Then the result of the testing of users using questionnaires generated Application Benefits scores 90.8%, Ease of 86.93%, Interface 82% and Content 90.2%.
Implementasi E-Asessment Higher Order Thinking Skills (HOTS) Pada Model Problem Possing Pada Mata Kuliah Matematika Diskrit Pramartha, I Nyoman Bagus; Kusumawati, Ni Made Refa; Dewi, Ni Putu Thasya Tania; Sudiatmika, I Putu Gede Abdi; Jayanti, Ni Wayan Sri
Jurnal Riset dan Inovasi Pembelajaran Vol. 4 No. 3 (2024): September-December 2024
Publisher : Education and Talent Development Center Indonesia (ETDC Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51574/jrip.v4i3.2060

Abstract

Penelitian ini didasari atas penggunaan asesmen hasil belajar mahasiswa yang selama ini menggunakan penilaian dalam bentuk tes tertulis untuk mengukur hasil belajar mahasiswa. Oleh sebab itu, tujuan utama dalam penelitian ini adalah untuk mengetahui efektivitas implementasi E-Asessment Higher Order Thinking Skills (HOTS) pada model problem possing dalam meningkatkan hasil belajar mahasiswa pada mata kuliah matematika diskrit di ITB STIKOM Bali kampus Jimbaran. Penelitian ini merupakan penelitian pre-eksperimen, dengan menggunakan one group pretest-posttest design. Penelitian ini melibatkan 38 mahasiswa semester satu yang terdiri dari program studi sistem informasi, sistem komputer dan teknologi informasi, yang dipilih menggunakan metode purposive sampling. E-assesment Higher Order Thinking Skills (HOTS) yang diterapkan berbentuk asesmen proyek sebagai metode pengumpulan data dengan komponen penilaian mencangkup aspek pengetahuan, sikap, dan keterampilan mahasiswa dalam menyelesaikan studi kasus. Teknik analisis yang digunakan dalam penelitian ini adalah analisis uji- t dan n-gain. Hasil analisis data menunjukkan nilai n-gain sebesar 0,73 dan uji t-test (paired sample t-test) menunjukkan nilai t-hitung sebesar 10,517 (sig. 0.00<0.005), yang menunjukkan bahwa penggunaan E-Asessment Higher Order Thinking Skills (HOTS) pada model problem possing efektif dan signifikan dalam meningkatkan hasil belajar mahasiswa pada mata kuliah matematika diskrit.
Comparison of LSTM and GRU Models Performance in Forecasting Gold Prices: A Case Study Using Historical Data from Yahoo Finance Sudiatmika, I Putu Gede Abdi; Putra, I Made Agus Wirahadi
ARRUS Journal of Engineering and Technology Vol. 4 No. 1 (2024)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/jetech2760

Abstract

This research aims to compare the performance of two types of recurrent neural network models, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), in forecasting gold prices based on historical closing price data. Historical gold price data from December 14, 2017, to March 14, 2024, was downloaded using the yfinance library. The data was normalized using MinMaxScaler and split into training and testing sets with an 80:20 ratio. LSTM and GRU models were constructed with two recurrent layers followed by a Dense layer for output. Both models were trained using the training data and evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), and R-squared (R²) metrics. The experimental results indicate that the GRU model outperformed the LSTM model in predicting gold prices. GRU achieved an MSE of 337.70, MAE of 14.05, and R² of 0.933, whereas LSTM achieved an MSE of 808.98, MAE of 22.71, and R² of 0.839. Based on the model performance evaluation, it can be concluded that GRU consistently produced more accurate predictions closer to the actual values of gold prices compared to LSTM. This finding suggests that GRU may be a preferable choice in applications for forecasting gold prices using historical data.
Manajemen Program Teaching Factory Berbasis Link and Match di SMK TI Global Jimbaran Santhi Dewi, Komang Hari; Novita, Ni Kadek Tasya; Jayanti, Ni Wayan Sri; Sudiatmika, I Putu Gede Abdi
Jurnal Ilmiah Manajemen, Bisnis dan Kewirausahaan Vol. 5 No. 2 (2025): Juni : Jurnal Ilmiah Manajemen, Bisnis dan Kewirausahaan
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurimbik.v5i2.1457

Abstract

This study aims to examine the effectiveness of the Teaching Factory (TeFa) program management based on the link and match principle at SMK TI Global Jimbaran in enhancing students’ job readiness and entrepreneurial mindset. The research adopts a mixed-methods approach with a sequential explanatory design, starting with quantitative data collection through questionnaires distributed to50 students from grades XI and XII, as well as 10 vocational teachers and industry partners. Subsequently, in-depth interviews and observations were conducted to enrich the findings qualitatively. Quantitative analysis reveals that 82.7% of students stated that the TeFa program improved their understanding of industrial work processes, while 76% expressed interest in developing their own business after participating in TeFa activities. Furthermore, 90% of teacher respondents reported that the Teaching Factory supports contextual implementation of the Merdeka Curriculum. The qualitative analysis reinforces these findings by identifying active collaborative practices between the school and industry stakeholders, including the development of teaching modules, use of industrial-standard equipment, and student internships at partner companies. Based on these results, it is concluded that the management of the Teaching Factory at SMK TI Global Jimbaran has proven effective in implementing the link and match principles and in strengthening students’ entrepreneurial capacities..
Sentiment analysis of tourist reviews on google maps for pura besakih using machine learning algorithms Sudiatmika, I Putu Gede Abdi; Saputra, Putu Satya; Rahardian, Rifky Lana; Dewi, Komang hari Santhi
Jurnal Mandiri IT Vol. 14 No. 1 (2025): July: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i1.449

Abstract

Tourist reviews on digital platforms have become a valuable source of information for understanding visitor experiences. This study applies sentiment analysis to 2,891 Google Maps reviews of Pura Besakih, Bali’s largest and most sacred temple, collected between January 2023 and December 2024. The aim is to assess overall visitor sentiment and identify factors influencing satisfaction and dissatisfaction. Reviews were preprocessed using a standardized pipeline that included translation, cleaning, tokenization, stopword removal, and stemming. Sentiment labeling was conducted using the Indonesian Sentiment Lexicon (InSet), followed by classification using six machine learning models: Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Naive Bayes, Decision Tree, Random Forest, and Neural Network. The SVM model achieved the highest performance with an accuracy of 76.3% and F1-score of 55.68%. Thematic analysis revealed positive feedback highlighting the temple’s spiritual ambiance, architecture, and improved facilities, while negative sentiment was driven by issues such as unauthorized guides, misleading charges, and restricted access. These findings offer valuable insights for tourism stakeholders to improve visitor experience and support sustainable heritage tourism through data-driven decision-making.
Co-Authors , Rifky Lana Rahardian A.A Raka Jayaningsih A.A. Raka Jayaningsi Agus Yudi Wiputra Albert Fernando Albert Fernando Anak Agung Raka Jayaningsih Artana, Wayan Widya Bonanza, Muhammad Jodie Dewi, Ni Putu Thasya Tania Eka Yuliani Fakhriah, Syahriati Fathurriza, Ari Fridayanti, Ni Putu Yulia I Gusti Ayu Sri Melati I Gusti Ayu Sri Melati I Gusti Ayu Sri Melati, I Gusti Ayu I Gusti Ngurah Ketut Purwantha I Gusti Ngurah, Putra Arimbawa I Komang Budi Mas Aryawan I Komang Budi Mas Aryawan I Made Agus Widiana Putra I Made Dwi Darma Artanaya I Made Onky Antara I Made Pradipta I Made Pradipta I Made Wirayudha Jayendra I Putu Agus Bayu Bimantara I Putu Astya Prayudha I Putu Erwin Febriana I Putu Okta Priyana I Putu Yesha Agus Ariwanta Ida Ayu Lalita Rathintara Imama Lavi Insani Jayaningsih, A.A. Raka Jayanti, Ni Wayan Sri Kadek Adi Karismayana Kadek Ray Gangga Jyotika Marchendy Komang Ayu Krisna Dewi Komang Hari Santhi Dewi KOMANG HARI SANTHI DEWI . Komang Yogi Triana Kusumawati, Ni Made Refa Laksmi, Ida Ayu Agung Luh Putu Meyra Anjani Made Meita Puspadewi Melati, I Gusti Ayu Sri Ni Kadek Tasya Novita Devi Ni Wayan Sri Jayanti Ni Wayan Sukarini Novita, Ni Kadek Tasya Nugraha, Dwi Haryadi Nusantari, Dewa Ayu Mas Putriari Nyoman Bagus Paramartha Pradipta, I Made Pramartha, I Nyoman Bagus Pramartha, Nyoman Bagus Putera, Wayan Andrika Putra , I Made Agus Widiana Putra, I Made Agus Wirahadi Putra, Ida Ayu Gde Suwiprabayanti Putu Satya Saputra Rifky Lana Rahardian Santhi Dewi, Komang Hari Santhi, Komang Hari Saputra, I Gede Seri Dharma Bobby Saputra, S.TI., M.Kom., Putu Satya Setiawan, I Made Oka Adi Silvester Magnus Loogman Palit Syam, Riri Nurdina tanjung, rona UTAMI, NI PUTU MEILING Wayan Andrika Putera Wayan Andrika Putera Wayan Widya Artana Wiratama, Febri Yogi Arya Bawana Putra Raspati