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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) JUITA : Jurnal Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jusikom : Jurnal Sistem Komputer Musirawas JURNAL ILMU KOMPUTER INDONESIA Journal of Electrical, Electronics and Informatics Indonesian Journal of Data and Science Jurnal Scientia Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) TECHNOVATE Galaksi KOMET
Sandhiyasa, I Made Subrata
STMIK STIKOM Indonesia
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Mathematics Public Health Social Sciences Other

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Journal : Galaksi

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Financial Data Warehousing at Village Credit Institution xyz Using a Star Schema Sandhiyasa, I Made Subrata; Nopianti, Ni Kadek Winda; Nugraha, Putu Gede Surya Cipta
Jurnal Galaksi Vol. 2 No. 1 (2025): Galaksi – May 2025
Publisher : Yayasan Sraddha Panca Widya Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70103/galaksi.v2i1.54

Abstract

The role of information technology is the main focus in financial management, especially in supporting the data analysis process for effective decision making.  Village Credit Institution xyz, as a financial institution owned by Pekraman Villages in Bali, faces obstacles in presenting financial data that is still in the form of tables. The presentation is not effective in providing a clear and adequate picture to support management decision-making. Makes it difficult to identify customers with bad or current credit. This research aims to build a financial data visualization system at  Village Credit Institution  xyz using Looker Studio, with a data warehouse design implemented using Kimball's Nine Steps method. The ETL process is carried out using Pentaho Data Integration (PDI) to compile data from various sources. The final result of this research is data visualization in the form of 9 main menus. This system allows the presentation of data in the form of interactive graphs, thus facilitating data analysis, accelerating the decision-making process, and increasing the efficiency of financial data management in  Village Credit Institution. System testing was conducted using the User Acceptance Testing (UAT) method with a result of 92.48% or strongly agree, indicating that the developed system has met the needs of users.
Optimising Double Exponential Smoothing for Sales Forecasting Using The Golden Section Method Pradnyani, Kadek Dian; Sandhiyasa, I Made Subrata; Gunawan, I Made Agus Oka
Jurnal Galaksi Vol. 1 No. 2 (2024): Galaksi - August 2024
Publisher : Yayasan Sraddha Panca Widya Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70103/galaksi.v1i2.21

Abstract

To achieve maximum profits and a satisfying impression on consumers, companies are required to have the right strategy in selling their products. In determining the right strategy, it requires the availability of accurate information that can be analyzed to determine a sales strategy so that it can increase the number of sales and generate large profits, namely by forecasting. In the Double Exponential Smoothing method, the problem that arises is determining the optimum α parameter value to provide the smallest size of forecasting error, which is sought using the trial and error method, so it requires quite a lot of time. To overcome this problem, a non-linear optimization algorithm using the Golden Section algorithm is used. The Golden Section algorithm is an algorithm that uses the principle of reducing the boundary area α which might produce a minimum objective function value. It is hoped that this forecasting design will be able to provide information that will help the company take decisions or steps in providing stock of goods for sale so that there will be no overstock in the warehouse and can increase Dewaayu Shop's profits.  based on the test results, the value of  MAPE value is obtained of 21.59579369% and RMSE value of 2.42465034.
A Structured Decision Intelligence Framework for Context-Aware Decision Making Sudipa, I Gede Iwan; Pandawana, I Dewa Gede Agung; Sandhiyasa, I Made Subrata
Jurnal Galaksi Vol. 2 No. 2 (2025): Galaksi - August 2025
Publisher : Yayasan Sraddha Panca Widya Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70103/galaksi.v2i2.96

Abstract

Decision Intelligence (DI) has emerged as an integrative paradigm that combines data, analytics, and artificial intelligence to enhance organizational decision-making. Despite this growing interest, many existing DI approaches place disproportionate emphasis on predictive intelligence while providing limited methodological guidance on how predictions are transformed into actionable and accountable decisions. Machine learning models are highly effective at forecasting and classification; however, they do not inherently incorporate organizational constraints, human preferences, or decision trade-offs. This study proposes a structured, end-to-end Decision Intelligence framework that explicitly integrates machine learning–based prediction with Decision Support System (DSS) modelling. The framework positions DSS as the core decision logic by employing the Analytic Hierarchy Process (AHP) to formalize contextual and human preferences and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to execute alternative ranking. Furthermore, contextual intelligence and outcome intelligence are embedded to ensure decision relevance, transparency, and continuous improvement. Using a Design Science Research approach, this study develops and demonstrates the proposed framework as a systematic solution for bridging the gap between predictive analytics and decision execution. The framework contributes to Decision Intelligence research by clarifying the role of DSS in AI-driven decision environments and by providing a replicable structure for integrating prediction, decision modelling, and outcome evaluation.
Co-Authors Anandita, Ida Bagus Gede Arditya, I Kadek Dito Aristana, Made Dona Wahyu Asana, I Made Dwi Putra Atmaja, Ketut Jaya Christina Purnama Yanti Desak Made Dwi Utami Putra Fibriyanthini, Luh Gede Indrawan Hendrawati, Theresia I Dewa Gede Agung Pandawana I Gede Aris Gunadi I Gede Iwan Sudipa I Gusti Made Ngurah Desnanjaya I Kadek Dwi Gandika Supartha I Made Agus Oka Gunawan I Made Oka Widyantara I Nyoman Tri Anindia Putra I Nyoman Widhi Adnyana I Putu Agus Eka Darma Udayana, I Putu Agus Eka I Putu Yoga Indrawan I Wayan Agus Surya Darma Indrayuni, Ni Komang Purnama Ketut Sepdyana Kartini MADE WAHYU ADHIPUTRA Meinarni, Ni Putu Suci Muni, Gede Dharma Sahasra Ni K. N Noviani Pande Ni Made Mila Rosa Desmayani, Ni Made Mila Rosa Ni Putu Widantari Suandana Nirwana, Ni Kade Ayu Nopianti, Ni Kadek Winda Oka, I Dewa Gede Ari Pande, Ni Kadek Nita Noviani Pangestu, Ni Made Diah Nandita Parniti, I Gusti Agung Ayu Pira Prabhawa , I Kadek Angga Surya Pradnyani, Kadek Dian Pramawati, I.D.A Tantri Pramest, Ni Luh Gede Sintia Pranata, I Made Dicky Putu Gede Surya Cipta Nugraha Putu Wirayudi Aditama Radhitya, Made Leo Sarasvananda , Ida Bagus Gde Saraswati, Ni Wayan Sumartini Satya, I Wayan Wira Savitri, Ni Kadek Wiliya Widiartha, Komang Kurniawan Wiguna, I Komang Arya Ganda Wijaya, Bagus Kusuma Yuri Prima Fittryani, Yuri Prima