Implementasi Neural Network Menggunakan Rapidminer Pada Prediksi Anggaran Operasional Teknisi Di Witel Semarang Sto Majapahit

Wiwit, Annisa Puspaningsari (2021) Implementasi Neural Network Menggunakan Rapidminer Pada Prediksi Anggaran Operasional Teknisi Di Witel Semarang Sto Majapahit. Technical Report. Pustakawan, Perpustakaan Institut Teknologi Telkom Purwokerto. (Unpublished)

	Text Cover .pdf Download (149kB)
	Text Abstract.pdf Download (71kB)
	Text Abstrak.pdf Download (70kB)
	Text BAB I.pdf Download (239kB)
	Text BAB II.pdf Download (92kB)
	Text BAB III.pdf Restricted to Registered users only Download (426kB) | Request a copy
	Text BAB IV.pdf Download (91kB)
	Text Daftar Pustaka.pdf Download (39kB)
	Text Lampiran.pdf Restricted to Registered users only Download (279kB) | Request a copy

Abstract

Data is important in everything. There are various terms related to data, one of which is data mining. Sera, forecasting is the right tool used to make decisions in the future. In the data recording of gasoline money and operational technicians at WITEL Telkom Semarang (STO Majapahit) it is necessary to forecast future budgets. The purpose of this report is to help predict the technician's operating budget in November 2021. So that the company can make the most of these funds. The author collects data by asking for data directly from the person in charge and field supervisor in the practical workplace. In data processing, the author utilizes data mining by using neural network algorithms or artificial neural networks. The author does general work, namely helping to input tangible data, financial recapitulation, looking for unspecified data, and updating the schedule of working hours. The data processing in this report contains several tables, namely: selection data, sample data, training and testing data. From this report, it is concluded that processing this data obtained a visualization of the neural network and also predictions for the upcoming recap period on 15 and 30 November 2021, namely Rp. 3,863,635,301 and Rp. 5,113,230,740. The author's suggestion for the author's place of practice, when working on financial data recapitulation is still manual and less efficient. Keywords: Data Mining, Neural Network, Operational Budget

Actions (login required)

View Item