Garuda - Garba Rujukan Digital

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

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 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

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.

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

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.

Twitter vs. Threads: Bagaimana Media Sosial Mempengaruhi Pandangan Politik di Kalangan Pengguna Aktif Jayaningsih, A.A. Raka; Abdi Sudiatmika, I Putu Gede; artana, Wayan Widya
Innovative: Journal Of Social Science Research Vol. 4 No. 4 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i4.13794

Dalam era digital, media sosial menjadi platform utama bagi masyarakat untuk mengakses informasi dan membentuk pandangan politik. Penelitian ini bertujuan untuk mengeksplorasi bagaimana Twitter dan Threads memengaruhi pandangan politik di kalangan pengguna aktif. Dengan menggunakan metode campuran, survei dilakukan terhadap 500 pengguna aktif Twitter dan Threads, serta wawancara mendalam dengan 20 pengguna untuk memperoleh wawasan lebih mendalam. Hasil penelitian menunjukkan bahwa Twitter cenderung menyebarkan informasi politik dengan cepat dan luas, tetapi sering kali kurang diverifikasi. Sementara itu, Threads menawarkan diskusi yang lebih mendalam dan analitis, yang dianggap lebih terpercaya oleh pengguna. Kesimpulannya, Twitter dan Threads memiliki peran berbeda dalam membentuk pandangan politik; Twitter efektif dalam penyebaran informasi cepat, sedangkan Threads lebih unggul dalam menyediakan diskusi berkualitas. Kedua platform ini memainkan peran penting dalam dinamika pembentukan opini publik di era digital.

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