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Analisis Rekomendasi Penggunaan Provider Telekomunikasi Seluler Berdasarkan Pengukuran Bandwdith pada Masa Pandemi Hadryan Eddy; Kusrini Kusrini; Asro Nasiri
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol 11, No 1 (2021): Jurnal Inspiration Volume 11 Issue 1
Publisher : STMIK AKBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v11i1.2624

Abstract

This study aims to provide recommendations for the use of cellular telecommunicationsproviders for use in online learning during a pandemic. This study used an experimental studyin which the researcher collected data manually by comparing the download and uploadbandwidth usage of each available cellular telecommunications provider in the Mamujudistrict. This research was conducted during the COVID-19 pandemic to impact the teachingĀ and learning process, which must do online or remotely, which certainly requires good internetconnectivity. This research uses quantitative methods and comparative analysis by collectingdata download bandwidth and upload bandwidth using NetLimiter from three cellulartelecommunications providers, namely Telkomsel, XL, and Indosat in Mamuju district. Thenthe data is processed by calculating the bandwidth. The results of data analysis obtained areTelkomsel with a download bandwidth of 0.0136 MBps, upload 0.0147 MBps, XL downloadbandwidth 0.0116 MBps, upload 0.0129 MBps, Indosat download bandwidth 0.0066 MBps,upload 0.0162 MBps. The results of this study show that among the three providers, Telkomselis superior in the use of download bandwidth with a size of 0.0136 MBps. In contrast, forupload bandwidth usage, it is recommended to use Indosat with a size of 0.0162 MBps. Still,an overall analysis of the provider, Telkomsel is a recommended provider for using videoconferencing applications due to gaps Between the download bandwidth usage with a size of0.0136 MBps and upload with a size of 0.0147 MBps is not too significant and more stablethan other providers. Suggestions for further research are re-measurement by looking at thedistribution factor or the number of BTS in the area
Analisa data transaksi penjualan barang menggunakan algoritme Apriori dan FP-Growth Harianto Harianto; Hadryan Eddy
JNANALOKA Vol. 01 No. 01 Maret Tahun 2020
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2020.v1-no1-35-43

Abstract

Transaksi penjualan barang pada sebuah perusahaan terjadi setiap hari mengakibatkan semakin bertambah banyaknya catatan transaksi penjualan. Tidak banyak dari perusahaan menjadikan transaksi penjualan itu hanya sebagai arsip belaka. Yang pada akhirnya mengakibatkan sebuah perusahaan mengalami kekurangan stok barang. Tentunya hal demikian terjadi karena transaksi penjualan barang tidak dianalisa dan dipelajari polanya. Ada beberapa banyak metode data mining yang digunakan untuk menganalisa pola pembelian barang secara bersamaan oleh pembeli. Diantara metode yang sering sekali digunakan adalah Apriori dan FP-Growth. Pada penelitian ini, bertujuan untuk menemukan pola pembelian barang secara bersamaan berdasarkan bulan selama satu tahun. Untuk menemukan pola pembelian tersebut digunakan Algoritma Apriori dan FP-Growth kemudian membandingkan hasil dalam menemukan pola kombinasi yang dihasilkan dalam dataset. Hasil dari penelitian ini algoritma Apriori membutuhkan waktu yang lebih sedikit dalam memperoses dan menampilkan hasil tapi rules yang didapatkan lebih sedikit dibandinkan algoritma FP-Growth. Sedangkan algoritma FP- Growth membutuhkan waktu yang lebih lama dbandingkan algoritma Apriori tapi menghasilkan rules yang lebih banyak dibandingkan algoritma Apriori.
Implementation of K-means and Weight Product (WP) Methods in Determining Work From Home (WFH) Priorities in the New Normal Period in Indonesia Eddy, Hadryan
Jurnal Ilmiah Multidisiplin Amsir Vol 3 No 1 (2024): Desember
Publisher : AhInstitute of Research and Community Service (LP2M) Institute of Social Sciences and Business Andi Sapada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62861/jimat amsir.v3i1.595

Abstract

Covid-19 (SARS-CoV-2) is a new type of virus that began in the city of Wuhan, China in late 2019. Over time, the development of the Covid -19 Virus has greatly increased so that it has an overall impact on an organization. Currently, there are various methods in organizations that have been carried out to reduce the development of COVID-19, one of which is working from home during the New Normal period. This research aims to apply the K-Means and Weight Product (WP) methods in determining the priority of giving WFH schedules to all employees depending on the conditions of each employee. The K-Means method is used to group a number of covid-19 patient case data based on age and disease history. The output results of the process will be used as input criteria and criteria importance in the WP method. The use of the Elbow method makes it easy to determine the value of K in the clustering process on various data used. In this study, the best K value is 3 based on the evaluation results using the elbow method. The use of 2 criteria from the results of clustering covid-19 patient data in making decision models with the WP method provides more objective and precise decision results based on data / facts that have occurred. The functionality aspect of the system is very good after going through the process of testing the calculation results manually and using the system, both have the same results.