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PENERAPAN ALGORTIMA ADJACENCY LIST UNTUK MENGHITUNG TOTAL BELANJA PADA MULTI LEVEL MARKETING

Authors: ., Afriyudi; Hartati, Sri;

PENERAPAN ALGORTIMA ADJACENCY LIST UNTUK MENGHITUNG TOTAL BELANJA PADA MULTI LEVEL MARKETING

Abstract

Data multilevel marketing merupakan data yang bersifat hierarki yaitu dimana datanya bersifat seperti pohon, satu parent memiliki banyak children, dan satu child hanya memiliki satu parent. Pada relational model, model yang dapat digunakan adalah one to many. Dalam Permasalahan relational model, permasalahan hierarchical data merupakan permasalahan yang umumnya sulit dipecahkan. Pada dasarnya data yang dimiliki bersifat relational sehingga kita harus mencari metode untuk mentransfer data yang bersifat relational menjadi hierarchy. Ada beberapa metode yang dapat digunakan untuk menyelesaikan permasalahan ini, tetapi dalam penelitian ini akan dibahas satu metode saja yang dapat digunakan dalam menyimpan dan mengambil data yang bersifat Hierarchical yaitu adjacency list model dan untuk menghitung total jumlah belanja downline digunakan metode non rekusif karena metode rekursif yang biasa digunakan untuk metode Adjacency list tidak dapat digunakan pada database Mysql dikarenakan keterbatasan Database ini.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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