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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Majalah Ilmiah Teknologi Elektro Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
I Made Suwija Putra
Program Studi Teknologi Informasi, Fakultas Teknik, Universitas Udayana
Computer Science & IT Electrical & Electronics Engineering Engineering

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IMPLEMENTASI ETL DATA WAREHOUSE DENGAN KONSEP FITUR METADATA DAN CLEANSING DATA PADA TOKO KUE I Gusti Ngurah Agung Trisna Putra; I Nyoman Aditya Mahendra; I Made Suwija Putra
Sistemasi: Jurnal Sistem Informasi Vol 9, No 2 (2020): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1738.726 KB) | DOI: 10.32520/stmsi.v9i2.732

Abstract

Perkembangan teknologi yang semakin pesat membuat permintaan atas kebutuhan pengolahan dan penyajian data yang lebih baik. Pada toko kue udayana merupakan jenis toko yang menjual berbagai jenis kue yang diproduksi sendiri dan memiliki beberapa cabang yang tersebar di Bali. Toko kue udayana kesulitan dalam menganalisis proses traksaksi dikarenakan banyaknya data yang dikirim dari masing-masing cabang setiap bulannya. Hasil proses analisa ini digunakan untuk acuan pendukung dalam pengambilan keputusan oleh pihak manajemen toko. Metode pengumpulan data massive yang tepat digunakan dalam menganalisis suatu proses transaksi adalah pendekatan teknologi data warehouse. Data warehouse mendukung kemampuan melakukan query untuk mendukung pengambilan keputusan, melihat keadaan finansial, stok produk, dan layanan dengan mudah. Pengembangan data warehouse ini menggunakan pemodelan star skema dan dalam penerapan pengumpulan data ada tahapan ETL (extract, transform, dan load) untuk dapat membaca data dari sistem OLTP (Online TransactionProcessing). Perancangan pada sistem menggunakan OLAP (Online Analytical Processing) untuk mendesain aplikasi yang bisa mengumpulkan, menyimpan, serta memanipulasi data multidimensi sebagai tujuan analisis.
Rancang Bangun Engine ETL Data Warehouse dengan Menggunakan Bahasa Python I Made Suwija Putra; Dewa Komang Tri Adhitya Putra
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 2 (2019): Agustus 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (833.425 KB) | DOI: 10.29207/resti.v3i2.872

Abstract

Big companies that have many branches in different locations often have difficulty with analyzing transaction processes from each branch. The problem experienced by the company management is the rapid delivery of massive data provided by the branch to the head office so that the analysis process of the company's performance becomes slow and inaccurate. The results of this process used as a consideration in decision making which produce the right information if the data is complete and relevant. The right method of massive data collection is using the data warehouse approach. Data warehouse is a relational database designed to optimize queries in Online Analytical Processing (OLAP) from the transaction process of various data sources that can record any changes in data that occur so that the data becomes more structured. In applying the data collection, data warehouse has extracted, transform, and load (ETL) steps to read data from the Online Transaction Processing (OLTP) system, change the form of data through uniform data structures, and save to the final location in the data warehouse. This study provides an overview of the solution for implementing ETL that can work automatically or manually according to needs using the Python programming language so that it can facilitate the ETL process and can adjust to the conditions of the database in the company system.
Deteksi Kesamaan Teks Jawaban pada Sistem Test Essay Online dengan Pendekatan Neural Network I Made Suwija Putra; Putu Jhonarendra; Ni Kadek Dwi Rusjayanthi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 6 (2021): Desember 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (690.554 KB) | DOI: 10.29207/resti.v5i6.3544

Abstract

E-learning is an online learning system that applies information technology in the teaching process. E-learning used to facilitate information delivery, learning materials and online test or assignments. The online test in evaluating students’ abilities can be multiple choice or essay. Online test with essay answers is considered the most appropriate method for assessing the results of complex learning activities. However, there are some challenges in evaluating students essay answers. One of the challenges is how to make sure the answers given by students are not the same as other students answers or 'copy-paste'. This study makes a similarity detection system (Similarity Checking) for students' essay answers that are automatically embedded in the e-learning system to prevent plagiarism between students. In this paper, we use Artificial Neural Network (ANN), Latent Semantic Index (LSI), and Jaccard methods to calculate the percentage of similarity between students’ essays. The essay text is converted into array that represents the frequency of words that have been preprocessed data. In this study, we evaluate the result with mean absolute percentage error (MAPE) approach, where the Jaccard method is the actual value. The experimental results show that the ANN method in detecting text similarity has closer performance to the Jaccard method than the LSI method and this shows that the ANN method has the potential to be developed in further research.
Kekarangan Balinese Carving Classification Using Gabor Convolutional Neural Network I Putu Bagus Gede Prasetyo Raharja; I Made Suwija Putra; Tony Le
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 13 No 1 (2022): Vol. 13, No. 1 April 2022
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2022.v13.i01.p01

Abstract

Balinese traditional carvings are Balinese culture that can easily be found on the island of Bali, starting from the decoration of Hindu temples and traditional Balinese houses. One of the types of Balinese traditional carving ornaments is Kekarangan ornament carving. Apart from the many traditional Balinese carvings, Balinese people only know the shape of the carving without knowing the name and characteristics of the carving itself. Lack of understanding in traditional Balinese carving is caused by the difficulty of finding sources of materials to study traditional Balinese carvings. A traditional Kekarangan Balinese carving classification system can help Balinese people to identify classes of traditional Balinese carving. This study used the Gabor CNN method. The Multi Orientation Gabor Filter is used in feature extraction and image augmentation, coupled with the Convolutional Neural Network method for image classification. The usage of the Gabor CNN method can produce the highest image classification accuracy of 89%.
Co-Authors Anak Agung Kompiang Oka Sudana Angga Pratama Nugraha Dewa Komang Tri Adhitya Putra Dwi Rusjayanthi, Dwi Geyge Andika Lesmana I G A A Diah Indrayani I Gusti Ngurah Agung Trisna Putra I ketut Gede Darma Putra I Made Sukarsa I Nyoman Aditya Mahendra I Nyoman Piarsa I Putu Agung Bayupati I Putu Bagus Gede Prasetyo Raharja I Wayan Gunaya Kadek Novar Setiawan Ni Kadek Giofanni Chandra Devi Ni Putu Ayu Widiari Ni Putu Ratindia Apriyanti Putu Andre Mahaputra Putu Jhonarendra Tony Le