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All Journal Sistemasi: Jurnal Sistem Informasi Journal of Electrical, Electronics and Informatics
Theresia Hendrawati
STMIK STIKOM Indonesia
Computer Science & IT Electrical & Electronics Engineering

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EVALUASI PENGARUH TEKNOLOGI, PENGGUNA DAN ORGANISASI TERHADAP MANFAAT DARI PENERAPAN E-PROCUREMENT I Gusti Ayu Agung Mas Aristamy; Theresia Hendrawati
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 (708.244 KB) | DOI: 10.32520/stmsi.v9i2.667

Abstract

Pemerintah tengah berupaya mewujudkan pemerintahan yang terbuka dan demokratis dengan cara meningkatkan dan mengoptimalkan layanan publik melalui dibentuknya E-procurement atau pengadaan barang/jasa berbasis elektronik. Tujuan dari dibentuknya E-procurement adalah untuk mewujudkan pengadaan barang/jasa pemerintah yang efektif, efisien, transparan, adil, tidak diskriminatif dan akuntabel. Namun, dalam penerapannya masih banyak kendala yang ditemukan pada penerapan E-procurement. Melihat dari banyaknya kendala yang ditemui, penelitian ini bertujuan untuk melakukan evaluasi sistem E-procurement yang mengambil studi kasus pada E-procurement milik Pemerintah Provinsi Bali. Evaluasi dilakukan untuk mengetahui faktor yang menjadi pendukung serta penghambat dari penerapan sistem E-Procurement di Pemerintah Provinsi Bali. Metode evaluasi sistem yang dipilih untuk penelitian ini adalah metode HOT-Fit. Metode ini dipilih karena mencakup aspek Human (Pengguna), Organization (Instansi/Organisasi) dan Technology (Teknologi/Sistem). Hasil dari penelitian ini menyatakan bahwa faktor Teknologi, Pengguna dan Organisasi memiliki pengaruh yang positif dan signifikan terhadap penerapan sistem E-Procurement, sehingga pengguna sistem merasakan manfaat yang diberikan oleh adanya sistem E-Procurement. Faktor yang menjadi penghambat sejauh ini adalah masih adanya beberapa tahapan dalam proses pengadaan barang dan jasa yang masih manual atau belum sepenuhnya dilaksanakan by sistem.
Analysis of Twitter Users Sentiment against the Covid-19 Outbreak Using the Backpropagation Method with Adam Optimization Theresia Hendrawati; Christina Purnama Yanti
Journal of Electrical, Electronics and Informatics Vol 5 No 1 (2021): JEEI (February 2021)
Publisher : Institute for Research and Community Services Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JEEI.2021.v05.i01.p01

Abstract

This research tries to take advantage of Twitter by analyzing Indonesian-language tweets that discuss the Covid-19 virus outbreak to find out what Twitter users think about the Covid-19 virus outbreak. This study tries to analyze sentiment to see opinions on Covid-19 tweets that contains Posittive, Negative or Neutral sentiments using Multi-layer Perceptron (MLP) using Backprogragation with Adam optimization. We collected 200 documents (tweets) in Indonesian about Covid-19 that were tweeted since November 2019 and then trained them to get our MLP Backpropagation model. Our model managed to get an accuracy of up to 70% with f1-scores for positive, negative, and neutral classes respectively 0.77, 0.75, and 0.5 from a maximum value of 1. This shows that our model is quite successful in carrying out the sentiment classification process for Indonesian tweets with the Covid-19 theme.
ASALTAG : Automatic Image Annotation Through Salient Object Detection and Improved k-Nearest Neighbor Feature Matching Theresia Hendrawati; Duman Care Khrisne
Journal of Electrical, Electronics and Informatics Vol 2 No 1 (2018): JEEI (February 2018)
Publisher : Institute for Research and Community Services Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JEEI.2018.v02.i01.p02

Abstract

Image databases are becoming very large nowadays, and there is an increasing need for automatic image annotation, for assiting on finding the desired specific image. In this paper, we present a new approach of automatic image annotation using salient object detection and improved k-Nearest Neigbor classifier named ASALTAG. ASALTAG is consist of three major part, the segmentation using Minimum Barirer Salienct Region Segmentation, feature extraction using Block Truncation Algorithm, Gray Level Co-occurrence Matrix and Hu’ Moments, the last part is classification using improved k-Nearest Neigbor. As the result we get maximum accuracy of 79.56% with k=5, better than earlier research. It is because the saliency object detection we do before the feature extraction proccess give us more focused object in image to annotate. Normalization of the feature vector and the distance measure that we use in ASALTAG also improve the kNN classifier accuracy for labeling image.
Indonesian Alphabet Speech Recognition for Early Literacy using Convolutional Neural Network Approach Duman Care Khrisne; Theresia Hendrawati
Journal of Electrical, Electronics and Informatics Vol 4 No 1 (2020): JEEI (February 2020)
Publisher : Institute for Research and Community Services Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JEEI.2020.v04.i01.p06

Abstract

Games are considered capable of being used as a learning medium that can help teachers to teach children how to pronounce the Indonesian alphabet in early literacy, we try to build one aspect of the game in this study. The approach we use is a speech recognition approach that uses the convolutional neural network method. The results of this study indicate that CNN can recognize speech, with input data is in the form of sound. We use the MFCC feature vector sound feature to make a 3-dimensional matrix of input sound into CNN input. We also use the Sequential CNN architecture made from a simple 10 layer neural network, which produces a model with a small size, approximately only about 6 MB, with high accuracy (84%) and an F-Measure of 0.91.
Implementation and Evaluation of Accounting Information Systems in Manufacturing Company Using System Usability Scale I Made Subrata Sandhiyasa; Christina Purnama Yanti; Theresia Hendrawati
Journal of Electrical, Electronics and Informatics Vol 5 No 2 (2021): JEEI (September 2021)
Publisher : Institute for Research and Community Services Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JEEI.2021.v05.i02.p05

Abstract

Information systems can facilitate business actors to control and evaluate business reporting effectively and efficiently. Anugrah Sri Jaya is a business engaged in manufacturing. This company still uses a manual recording system which causes several problems, namely frequent errors in calculations and mismatch of inventory stock records with actual conditions. Therefore, the researcher proposes to implement an information system in the accounting process at Anugrah Sri Jaya. From the results of the study, researchers have succeeded in building a web-based accounting information system at Anugrah Srijaya. Information system testing uses the System Usability Scale (SUS) method where the test uses a questionnaire as an assessor and the number of responses is 5 respondents where the respondents from this study are business owners and several employees who will later use this system. From the results of the tests carried out, it can be seen that the average score obtained from the calculation of the System Usability Scale (SUS) is 74.5. Based on the results of the average score, this system can be said to be in the category of acceptance (Acceptable) and on the adjective rating scale, the information system built is rated as excellent.
Co-Authors Aristamy, I Gusti Ayu Agung Mas Christina Purnama Yanti Duman Care Khrisne Sandhiyasa, I Made Subrata