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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Ilmiah Sistem Informasi
Elfanza, Vellyn Chalista
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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ANALISIS FAKTOR KEBERHASILAN PERANGKAT LUNAK LIVIN BY MANDIRI PADA PT BANK MANDIRI Utami, Vita Dwi; Elfanza, Vellyn Chalista; Kusuma, Rahayu Linda; Albana, Ilham
Jurnal Ilmiah Sistem Informasi Vol. 4 No. 1 (2024): Jurnal Ilmiah Sistem Informasi
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/sm.v4i1.84

Abstract

In the modern era like now, many human needs can be met with a supporting technology. This is because of a demand of circumstances and needs. One form of meeting technological needs by humans is software in the banking sector. Supporting technology used in a banking includes software that is designed simply with the hope that users will be able to understand the use of the software. This refers to the assessment of success factors in a software in a company where its function is considered very important in various aspects. As in the company PT. Bank Mandiri (Persero). Tbk which until now has mobile banking software that is widely used or accessed by users. This research took place at Bank Mandiri Banyumas KC Purwokerto. Software that is already available then requires management actions for processes in a project. Livin by Mandiri is one of the software applications that are in great demand by users/customers. To test success by using statistical validity tests using materials / results from questionnaires and interviews to later measure how many customers / users use the Livin by Mandiri application. The target used as data collection material is 5 people with specific application users. From the results of the validity test calculation, it will be seen that the calculation is valid and not
Prediksi Potensi Suatu Wilayah Menggunakan Machine Learning Tarwoto; Ismayanti, Ratri; Utami, Vita Dwi; Elfanza, Vellyn Chalista
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3480

Abstract

Electricity has become a basic need for some human beings because all activities are almost related to electricity. Indonesia has several power plant projects and the largest power plant is generated from PLTU which can have an impact that we feel is greenhouse gas emissions and bad air pollution and also relies heavily on coal while the natural resources are not renewable with this fact if we reduce the use of coal it will be a boomerang for Indonesia itself. This research aims to predict areas that can potentially become Solar Power Plants with a machine learning regression model approach. So hopefully this research can be a reference in the development of Solar Power Plants in Indonesia. The methods used are Linear Regression (LR), Lasso Regression (LR), Ridge Regression (RR), and Support Vector Regression (SVR). The R2 coefficients for solar radiation were 0.924; 0.910; 0.917; 0.949; and 0.987, respectively.
Co-Authors Albana, Ilham Ismayanti, Ratri Kusuma, Rahayu Linda Tarwoto Utami, Vita Dwi