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All Journal Jurnal Amplifier: Jurnal Ilmiah Bidang Teknik Elektro dan Komputer Jurnal Komputer, Informasi dan Teknologi
Eko Prasetiyo Rohmawan
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Computer Science & IT Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media

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The Implementation of Load Balancing Using Per Connection Classifier Method Using Mikrotik RB1100 Siagian, Pedro Maldini; Hari Aspriyono; Eko Prasetiyo Rohmawan
JURNAL AMPLIFIER : JURNAL ILMIAH BIDANG TEKNIK ELEKTRO DAN KOMPUTER Vol. 13 No. 2 (2023): Amplifier November Vol. 13, No. 2 2023
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jamplifier.v13i2.29799

Abstract

The Implementation of Load Balancing Using Per Connection Classifier Method Using Mikrotik RB1100 By : Pedro Maldini Siagian 1) Hari Aspriyono 2) Eko Prasetiyo Rohmawan 2) Poltekkes Kemenkes Bengkulu as a university which has 2.000 students and 250 employees, has internet access through 2 providers, namely Icon Dedicated and Icon Broadband. Even though it has 2 internet lines, the distribution of internet line that is evenly distributed still cannot be implemented. Load Balancing carried out on Mikrotik RB1100 at Poltekkes Kemenkes Bengkulu can help distribute internet traffic evenly, and can overcome lost connections due to backing up broken connections with available connections. Load Balancing used Per Connection Classifier is a method that will send a set of packets over several existing links, taking into original account of packets. In this method, packets coming from one communication session will be routed through only one link. Through QoS (Quality of Service) testing that the result was that load balancing carried out was running well and as expected Poltekkes Kemenkes Bengkulu which can evenly distribute the connection traffic used. Keywords : Load Balancing, Per Connection Classifier, Mikrotik RB1100, Poltekkes Kemenkes Bengkulu Infomation: 1) Student 2) Supervisors
Application of K-Means Clustering Algorithm in Grouping Inventory Data at Putra Shop Deki Hari Nusti; indra kanedi; Eko Prasetiyo Rohmawan
Jurnal Komputer, Informasi dan Teknologi Vol. 1 No. 1 (2021): Juni
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v1i1.104

Abstract

Putra Mart store is one of the supermarkets in Bintuhan City., on Jl. South Kaur Cold Water. Putra shop is one of the shops engaged in supplying goods to small shops in Bengkulu City. The goods supply system at Toko Putra still uses a manual system in recording data, both data on availability of goods, data for store partners, and data on supply of goods to store partners. To help increase the supply of goods at Toko Putra, there needs to be an application that can determine what items should be in Toko Putra by looking at transaction data for supply of goods to store partners. Determination of stock of goods is done by grouping data on supply of goods through 2 groups, namely large groups and small groups. The application for grouping supply data at Toko Putra was created using the Visual Basic .Net programming language and SQL Server 2008 database by applying the K-Means Clustering Method. The grouping is done based on data on supply of goods per year obtained from Toko Putra. The application is able to analyze goods supply data by producing 2 clusters, namely Many and Few through the K-Means Clustering method approach. In addition, the results of this grouping can help the Putra Shop in managing inventory at the Putra Shop by looking at the results of the clustering that has been done. Based on the results of the tests that have been carried out, the application for grouping data on supply of goods at Toko Putra can provide information based on 2 groups, namely many and few. From the supply data in 2020, the results obtained are Cluster C1 as many as 4 and Cluster C2 as many as 13
Co-Authors Deki Hari nusti Hari Aspriyono Kanedi, Indra Kanedi Siagian, Pedro Maldini