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All Journal Aiti: Jurnal Teknologi Informasi Journal Of Informatics And Busisnes
Kusneti, Leni
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Computer Science & IT Economics, Econometrics & Finance

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Prototype Data Warehouse Kantor Penilai Publik XYZ Dengan Metode Nine-Step Kimball Ratu, Anggitta; Kusneti, Leni; Wijaya, Andri
Journal Of Informatics And Busisnes Vol. 1 No. 2 (2023): Juli - September
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v1i3.372

Abstract

In the era of information technology, data management has become crucial for organizations. The Public Appraisal Office (KJPP) XYZ in Palembang City, despite providing accurate property analysis, is still limited to the use of hard disks, hard copies, email, and Excel. This results in a lack of integration and efficiency in their operations. Therefore, this research proposes a solution in the form of designing a data warehouse prototype using the Nine-Step Kimball method. This method is employed as a systematic approach in designing and building a data warehouse, with the aim of ensuring effective and relevant development for business needs. The design will organize data into table components, creating regularity and centralization of data to facilitate search and analysis. The inspiration for this research comes from similar implementations in online market transactions and television editorial decisions using the snowflake schema and the successful Nine-Step Kimball method. It is hoped that through this approach, KJPP XYZ can optimize access, analysis, and use of the data.
Using the Support Vector Machine method with the HOG feature for classification of orchid types Andayani, Sri; Kusneti, Leni
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.82-95

Abstract

Orchids are the most species-rich flowering plants, with approximately 750 genera and 43,000 types of orchids in the world, of which about 5,000 species have been recorded in several provinces in Indonesia. Orchids have beautiful flowers with attractive colors, making them ornamental plants that many people like. From plant morphology, orchid plants can be differentiated based on the morphology of flowers, leaves, fruit, stems, and roots. The leaves of orchid plants have their characteristics for each type of orchid, such as long, round, or lanceolate. All orchids have veins that run parallel to their leaves. The individual shapes of orchid leaves can be classified using a Support Vector Machine (SVM) and Histogram of Gradient (HOG). In this research, five types of orchids that are popular among orchid lovers were used, namely Dendrobium, Cattleya, Oncidium, Phalaenopsis, and Vanda orchids, which were taken from public data. The accuracy of this method in classifying orchid species based on leaf morphology can be measured using a confusion matrix that measures precision, recall, and accuracy. From five tests, the Oncidium orchid had the highest average accuracy with a value of 98%, the Vanda orchid had the highest average precision of 99.80%, and the Cattleya orchid had the highest average recall of 100%.
Co-Authors Andri Wijaya Ratu, Anggitta Sri Andayani