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All Journal Jurnal Kolaboratif Sains Jurnal Sistim Informasi dan Teknologi
Suluh Sri Wahyuningsih
Universitas Muhammadiyah Palu
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Other

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Identifikasi Atribut Tingkat Lebih Tinggi untuk Prediksi Umur Bug: Identify Higher Level Attributes for Bug Age Prediction Suluh Sri Wahyuningsih; Nursalim
Jurnal Kolaboratif Sains Vol. 6 No. 3: MARET 2023
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jks.v6i3.3378

Abstract

Sebuah perangkat lunak yang berkualitas dapat diartikan sebagai suatu produk yang memiliki jumlah kesalahan atau bug yang sedikit. Berbagai cara dilakukan untuk menggurangi jumlah bug, seperti sistem pelacak bugzilla informasi yang disimpan dapat digunakan untuk menyelidiki fenomena yang berbeda. Manajemen proyek perlu memperkirakan waktu yang dibutuhkan untuk menangani suatu bug agar dapat membuat perencanaan proyek yang baik. Penelitian sebelumnya menggunakan atribut primitif (Low Level Attribute) untuk prediksi umur bug, merekomendasikan penggunaan atribut bug tingkat yang lebih tinggi. Oleh karena itu, atribut tingkat lebih tinggi diprediksi keberhasilan dengan akurasi umur bug. Dalam penelitian ini, identifikasi atribut tingkat lebih tinggi digunakan untuk meningkatkan akurasi prediksi umur sebuah bug. Untuk mengidentifikasi atribut mana yang signifikan pengaruhnya terhadap prediksi umur bug digunakan pencarian nilai informasi (infogain). Langkah kedua, yaitu mengukur akurasi klasifikasi berdasarkan atribut-atribut yang ditemukan, oleh karena itu menggunakan sejumlah metode, yaitu Zerro_R, One_R , Decision Tree, dan Naive Bayes. Metode-metode ini baik digunakan untuk dataset yang memiliki korelasi, melibatkan 24 buah atribut, 7 kelas bug_lifetime dan data set sebesar 1000 bug. Hasil penelitian mengidentifikasi 6 atribut tingkat tinggi, dimana 2 diantaranya (summary, dan last change time) dianggap memiliki pengaruh yang signifikan dalam memprediksi umur bug. Kombinasi atribut tingkat tinggi (2 atribut), tingkat rendah (3 atribut) dan seleksi (1 atribut) menghasilkan indeks kappa tingkat substantial (0,81). Hal tersebut menunjukkan dengan penambahan atribut tingkat lebih tinggi untuk prediksi umur bug dapat bekerja lebih baik dari penelitian sebelumnya yang menghasilkan indek kappa moderate (0,60).
The Influence of Electronic Service Quality and Electronic Recovery on Online Re-Purchase Intention: Role of E-Loyalty as Intervening Variable Erwin Dhaniswara; Suluh Sri Wahyuningsih; Handry Eldo; Asri Ady Bakri; Agus Junaidi
Jurnal Sistim Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jsisfotek.v5i3.271

Abstract

This study intends to examine how online service quality and online recovery affect online loyalty and how they affect consumers' willingness to repurchase online. In this study, a non-probability sampling strategy with a purposeful sampling procedure was applied. A sample of 100 respondents who had purchased products from the marketplace were given questionnaires in order to obtain the data. The data in this study are analyzed using the Partial Least Square (PLS) method. The findings of this study demonstrate that online repurchase intention and electronic service quality have an impact on online loyalty. This study also discovered that electronic service quality has an impact on online repurchase intention via electronic loyalty. Through electronic loyalty, electronic recovery also has an impact on online repurchase intention.
Application of The Speed-Up Robust Features Method To Identify Signature Image Patterns On Single Board Computer Nursalim; Cut Susan Octiva; Suluh Sri Wahyuningsih; Muhammad Lukman Hakim; Novrini Hasti
Jurnal Sistim Informasi dan Teknologi 2023, Vol. 5, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jsisfotek.v5i4.312

Abstract

Through the development of a signature pattern recognition program on SBC Beagle-bone Black, this research seeks to determine how to differentiate between real and false signatures. Three techniques of gathering data were employed in this study: interviews, observations, and a review of the literature. The quick application development method is the approach that is applied. The rapid, efficient, and brief development cycle (RAD) is emphasized. This study uses a use-case diagram to illustrate the application's logic and data flow. In this study, OpenCV is used as a digital image processing library along with the C++ programming language and QT creator as an integrated development environment (IDE). This application was subjected to both accuracy and functional testing. The following conclusions are drawn from the findings of the investigation and testing that was done: Using the fast library approach for approximate nearest neighbors (FLANN) and the speeded-up robust features (SURF) feature extraction method, the signature pattern recognition program on the Beagle-bone black SBC can differentiate between real and fraudulent signatures. Through the processes of generating image scale space, feature localization, and feature description, the SURF approach extracts feature from signature images. This signature pattern recognition application is one of the digital image processing apps that can be run on the Beagle-bone Black single board computer. This indicates that the specifications of the SBC Beagle-bone Black for digital image processing are good.
Co-Authors Agus Junaidi Asri Ady Bakri Cut Susan Octiva Dhaniswara, Erwin Handry Eldo Muhammad Lukman Hakim Novrini Hasti Nursalim