Heny Pratiwi
STMIK Widya Cipta Dharma, Samarinda, Indonesia

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Penerapan Metode Single Moving Average Dalam Peramalan Persediaan Bahan Pangan Kukuh Rizqi Liyadi; Heny Pratiwi; Pitrasacha Aditya; Muhammad Ibnu Sa’ad
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 4, No 1 (2022): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v4i1.136

Abstract

Forecasting is a technique that is quite widely used today and has been developed since the 19th century. In line with the development of increasingly sophisticated forecasting techniques accompanied by developments in the use of computers. Forecasting can predict or estimate what will happen in the future using certain techniques so that forecasting has received increasing attention in recent years. Web-based applications are one of the systems that support the development of computer use, therefore in this study, researchers develop web-based applications for forecasting using the Single Moving Average method. In this study, forecasting was carried out using the Single Moving Average method to find out how much food is needed in the following month based on actual data from the previous months. Based on forecasting which was carried out using actual data from December 2021 to June 2022, the results obtained in the following month, namely July 2022, were 2,901 kg.
The Impact of Artificial Intelligence (AI) on the Future of Jobs in Computer Science and Information Systems: A Systematic Literature Review Heny Pratiwi; Muhammad Ibnu Sa'ad
Information Technology Studies Journal (ITECH) Vol. 1 No. 1 (2024): Information Technology Studies Journal (ITECH)
Publisher : Penelitian dan Pengembangan Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62207/vdebmf42

Abstract

The evolution of artificial intelligence (AI) in the fields of Computer Science and Information Systems has become a major research focus in recent decades. This research aims to investigate the impact of AI on job distribution and employment inequality in the context of Computer Science and Information Systems. The research method used is a systematic literature review, by collecting and analyzing relevant articles from reputable international databases. The results of the discussion show that the evolution of AI has brought significant changes in various aspects of work and influenced the division of tasks between humans and machines. The implication of this research is the importance of paying attention to the impact of AI in designing policies, training programs, and initiatives to minimize employment gaps and ensure fair access to employment opportunities in the AI ​​era.