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Syafrianto Syafrianto
STMIK Nusa Mandirii
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Journal : Jurnal Teknika

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Rancangan Migrasi Dan Analisa Sistem Jaringan Komputer Dengan Studi Kasus Di PT. Panasonic Semiconductor Indonesia Syafrianto Syafrianto
Jurnal Teknika Vol 13, No 1 (2021): Jurnal Teknika
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/jt.v13i1.522

Abstract

Permasalahan umum pada sistem jaringan komputer adalah masalah keterlambatan (delay) dan kecepatan (throughput) yang rendah, tentu hal ini sangat menganggu pengguna komputer pada sebuah sistem jaringan komputer. Untuk mengatasi hal itu, diperlukan analisa, rancangan serta tindakan perbaikan sistem jaringan agar permasalahan diatas dapat dipecahkan. Pada Tugas Akhir ini, penulis melakukan sebuah rancangan dan analisa serta proses migrasi pada jaringan komputer di PT. Panasonic Semiconductor Indonesia. Metodologi yang digunakan adalah melakukan pengujian secara langsung pada komputer di lokasi bagian pengeluaran barang. Parameter yang dianalisa pada pengujian ini adalah keterlambatan (delay) dan kecepatan (throughput). Berdasarkan hasil pengujian dan pengukuran serta pengumpulan data, didapatkan keterlambatan (delay) sebesar 0.120370156 detik dan kecepatan (throughput) sebesar 25784.71475 bps (bit per second).
Implementasi Data Mining Menggunakan Metode Algoritma Apriori Pada Toko Dhurroh Elektronik Syafrianto Syafrianto; Durotun Ayniyah
Jurnal Teknika Vol 13, No 2 (2021): Jurnal Teknika
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/jt.v13i2.624

Abstract

In the business world, every store must of course be able to compete and think about how the store can continue to grow and be able to expand its business scale. In order to increase sales of products sold, business actors must have various strategies. One way is by utilizing all sales transaction data that has occurred in the store itself. Dhurroh Elektronik store is a store that sells various kinds of goods such as cellphone accessories. Management of sales data in this store is still done manually, namely by recording sales data in the sales book or sometimes when serving purchases just remembering it. The obstacle faced is that it is difficult to find out where the goods are not in accordance with the behavior of consumers' habits in buying goods at the same time. Based on the above problems, it is necessary to have a calculation to group data items based on their tendencies that appear together in a transaction with Data Mining calculations using the Apriori Algorithm method. The results of the calculation of the items that are most in-demand are if you buy a headset, you will buy a lamp with a 100% confidence value and 19% support, if you buy a radio you will buy a lamp with a 71% confidence value and 16% support, if you buy a data cable, you will buy a flashlight. with a 71% Confidence value and 16% Support, If you buy a battery, you will buy a Flashlight with a 71% Confidence value and 16% Support. Keywords: Data Mining, Apriori Algorithm..
Rancangan Migrasi Dan Analisa Sistem Jaringan Komputer Dengan Studi Kasus Di PT. Panasonic Semiconductor Indonesia Syafrianto Syafrianto
Jurnal Teknika Vol 13 No 1 (2021): Jurnal Teknika
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/jt.v13i1.522

Abstract

Permasalahan umum pada sistem jaringan komputer adalah masalah keterlambatan (delay) dan kecepatan (throughput) yang rendah, tentu hal ini sangat menganggu pengguna komputer pada sebuah sistem jaringan komputer. Untuk mengatasi hal itu, diperlukan analisa, rancangan serta tindakan perbaikan sistem jaringan agar permasalahan diatas dapat dipecahkan. Pada Tugas Akhir ini, penulis melakukan sebuah rancangan dan analisa serta proses migrasi pada jaringan komputer di PT. Panasonic Semiconductor Indonesia. Metodologi yang digunakan adalah melakukan pengujian secara langsung pada komputer di lokasi bagian pengeluaran barang. Parameter yang dianalisa pada pengujian ini adalah keterlambatan (delay) dan kecepatan (throughput). Berdasarkan hasil pengujian dan pengukuran serta pengumpulan data, didapatkan keterlambatan (delay) sebesar 0.120370156 detik dan kecepatan (throughput) sebesar 25784.71475 bps (bit per second).
Implementasi Data Mining Menggunakan Metode Algoritma Apriori Pada Toko Dhurroh Elektronik Syafrianto Syafrianto; Durotun Ayniyah
Jurnal Teknika Vol 13 No 2 (2021): Jurnal Teknika
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/jt.v13i2.624

Abstract

In the business world, every store must of course be able to compete and think about how the store can continue to grow and be able to expand its business scale. In order to increase sales of products sold, business actors must have various strategies. One way is by utilizing all sales transaction data that has occurred in the store itself. Dhurroh Elektronik store is a store that sells various kinds of goods such as cellphone accessories. Management of sales data in this store is still done manually, namely by recording sales data in the sales book or sometimes when serving purchases just remembering it. The obstacle faced is that it is difficult to find out where the goods are not in accordance with the behavior of consumers' habits in buying goods at the same time. Based on the above problems, it is necessary to have a calculation to group data items based on their tendencies that appear together in a transaction with Data Mining calculations using the Apriori Algorithm method. The results of the calculation of the items that are most in-demand are if you buy a headset, you will buy a lamp with a 100% confidence value and 19% support, if you buy a radio you will buy a lamp with a 71% confidence value and 16% support, if you buy a data cable, you will buy a flashlight. with a 71% Confidence value and 16% Support, If you buy a battery, you will buy a Flashlight with a 71% Confidence value and 16% Support. Keywords: Data Mining, Apriori Algorithm..
Co-Authors Durotun Ayniyah