Article Per Year (5 Year)
p-Index From 2021 - 2026
1.066
P-Index
This Author published in this journals
All Journal Informatika Al-MIKRAJ: Jurnal studi Islam dan Humaniora Jurnal Sistem Informasi Dan E-Bisnis Dikdimas : Jurnal Pengabdian Kepada Masyarakat Riau Jurnal Teknik Informatika
Yuliansyah, Chandra
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Nursing Social Sciences Other

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search

 1 
Mengoptimalkan Penjualan Online Melalui Teknik Data Mining (Studi Kasus E-Commerce) Apriana, Diwi; Yuliansyah, Chandra
AL-MIKRAJ Jurnal Studi Islam dan Humaniora (E-ISSN 2745-4584) Vol 4 No 02 (2024): Al-Mikraj, Jurnal Studi Islam dan Humaniora
Publisher : Pascasarjana Institut Agama Islam Sunan Giri Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/almikraj.v4i02.4774

Abstract

The aim of this research is to optimize online sales through data mining techniques (e-commerce case study). This type of research is a literature review. Data collection with documentation. Data analysis with SLR. Research result. Research results The use of data mining techniques in optimizing online sales, especially in the context of e-commerce, can provide significant benefits for companies. By analyzing purchasing patterns and consumer behavior using data mining algorithms, companies can identify customer trends and preferences, improve promotional targeting, and optimize marketing strategies. This not only improves operational efficiency, but also results in a significant increase in sales. Thus, the integration of data mining techniques becomes a necessity for e-commerce companies that want to remain competitive and successful in an increasingly competitive market
Implementasi Data Mining Untuk Menentukan Kelayakan Penerimaan Bedah Rumah Menggunakan Algoritma K-Means Fakultas Ilmu Komputer Universitas Pasir Pengaraian Dona, Dona; Sabri, Khairul; Yasdomi, Kiki; Rifqi, Mi’rajul; Yuliansyah, Chandra; Susmita, Afnes
Jurnal Informatika Vol 12, No 3 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.7828

Abstract

The house renovation program is a government program, namely the Public Housing and Settlement Area Office, which is shown to rehabilitate or repair community houses that are not habitabel. This program is often a problem in Bangun Purba Village because when determining house renovation assistance, it is still by looking or relying on thoughts and predictions for people who will get assistance, so that the assistance that will be distributed is not on target. This house renovation program aims to provide welfare for the poor to build or renovate houses that are not habitabel. Therefore, the author created a Data Mining system to determine the feasibility of receiving home renovation using the K-Means algorithm using the PHP programming language and MySQL database. The K-Means method utilizes training data to generate probabilities such as each grouping for different classes, so that the probability values of the grouping can be optimized to determine the eligibility for receiving home surgery assistance based on the grouping process carried out by the K-Means method.
Mengoptimalkan Penjualan Online Melalui Teknik Data Mining (Studi Kasus E-Commerce) Apriana, Diwi; Yuliansyah, Chandra
AL-MIKRAJ Jurnal Studi Islam dan Humaniora Vol. 4 No. 02 (2024): Al-Mikraj, Jurnal Studi Islam dan Humaniora
Publisher : Pascasarjana Institut Agama Islam Sunan Giri Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/almikraj.v4i02.4774

Abstract

The aim of this research is to optimize online sales through data mining techniques (e-commerce case study). This type of research is a literature review. Data collection with documentation. Data analysis with SLR. Research result. Research results The use of data mining techniques in optimizing online sales, especially in the context of e-commerce, can provide significant benefits for companies. By analyzing purchasing patterns and consumer behavior using data mining algorithms, companies can identify customer trends and preferences, improve promotional targeting, and optimize marketing strategies. This not only improves operational efficiency, but also results in a significant increase in sales. Thus, the integration of data mining techniques becomes a necessity for e-commerce companies that want to remain competitive and successful in an increasingly competitive market
Socialization of Digital Innovation Strategies to Enhance SME Sales and Community Self-Sufficiency in Kayu Manis Village Murlena, Murlena; Andayani, Nurfitri; Yuliansyah, Chandra; Andiani, Lia; Hidayat, Rachmat; Bainamus, Putri Milanda; Susanto, Edy; Aprilyanti, Cindy; Ramadana, Radiyah; Maslukin, Maslukin
DIKDIMAS : Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 3 (2024): DIKDIMAS : JURNAL PENGABDIAN KEPADA MASYARAKAT  VOL 3 NO 3 DECEMBER 2024
Publisher : Asosiasi Profesi Multimedia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/dikdimas.v3i3.309

Abstract

This community service focuses on empowering Micro, Small, and Medium Enterprises (MSMEs) in Kayu Manis Village, Rejang Lebong Regency, Bengkulu Province, through digital transformation to improve sales performance and promote community self-sufficiency. The study utilizes a qualitative method with a case study approach, combining direct observation, interviews with MSME owners, and socialization activities conducted during the Community Service Program (KKN). The findings reveal that adopting digital strategies, such as digital marketing, digital transaction recording, and social media platforms, has led to significant improvements in the operational efficiency and revenue of MSMEs in the village. Additionally, the use of digital tools helps minimize risks associated with financial data loss while expanding the market reach of MSMEs. These results highlight the effectiveness of digital transformation in addressing challenges faced by MSMEs, fostering their growth, and enhancing community welfare. This initiative demonstrates the critical role of technology in supporting economic development and sustainability, particularly in rural areas. The outcomes of this program serve as a valuable model for implementing similar efforts in other regions facing comparable challenges.
Penerapan Data Mining Terhadap Penjualan Produk Kosmetik Menggunakan Algoritma K-Means Dona, Dona; Sabri, Khairul; Yasdomi, Kiki; Rifqi, Mi’rajul; Maradona, Hendri; Yuliansyah, Chandra; Rahayu, Dina
Riau Jurnal Teknik Informatika Vol. 4 No. 3 (2025): November 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i3.4275

Abstract

Kehidupan wanita tidak bisa dipisahkan dari kosmetik. Selain untuk mempercantik diri, kosmetik juga digunakan untuk keperluan kesehatan. Kosmetik pada dasarnya adalah salah satu kebutuhan pokok wanita. Oleh karenanya setiap hari data transaksi penjualan pada toko Putri Kosmetik Pasir Pengaraian semakin bertambah dan menyebabkan penyimpanan data menjadi sangat besar, sehingga proses manajemen untuk mengatur ketersediaan barang sangat diperlukan untuk menghindari penumpukan barang yang sama dan kurang diminati oleh pelanggan. Oleh karena itu, penulis membuat sebuah sistem data mining terhadap penjualan produk kosmetik menggunakan algoritma K-Means yang bertujuan untuk mengetahui minat pembeli terhadap suatu produk sehingga bisa dipastikan persediaan produk yang laku terjual atau belum laku terjual. Manfaat penelitian ini adalah mencegah kehabisan stok dan terjadi penumpukan produk yang belum laku terjual. Metode yang digunakan dalam pengelompokan produk adalah menggunakan metode K-Means agar dapat diketahui produk yang terlari dan kurang laris. Data produk dikelompokkan berdasar kemiripan data, sehingga data dengan nilai yang sama akan berada dalam satu cluster. Dengan adanya cluster stok produk dengan masing-masing tingkat pergerakan stok yang dimiliki ini memungkinkan dijadikannya acuan dalam memprediksi persediaan produk sesuai dengan kebutuhannya. Pengujian yang dilakukan dalam penelitian ini adalah dengan menggunakan bahasa pemrograman PHP dan database MySQL.
Implementasi Adguard Home Berbasis Kontainer Pada Mikrotik Routeros Untuk Monitoring Dan Keamanan Jaringan Andini, Lia; Yuliansyah, Chandra
Jurnal Sistem Informasi dan E-Bisnis Vol 8 No 1 (2026): Januari
Publisher : LPPMPP Yayasan Sejahtera Bersama Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54650/jusibi.v8i1.651

Abstract

Monitoring jaringan merupakan kebutuhan krusial dalam pengelolaan infrastruktur teknologi informasi modern seiring meningkatnya kompleksitas lalu lintas data dan ancaman keamanan siber. Penelitian ini bertujuan untuk mengimplementasikan dan menganalisis efektivitas AdGuard Home sebagai sistem monitoring jaringan berbasis DNS yang dijalankan pada kontainer MikroTik RouterOS. Metode penelitian menggunakan pendekatan kuantitatif dengan desain eksperimental melalui pengujian performa, efektivitas pemblokiran DNS, serta analisis pemanfaatan sumber daya sistem. Hasil penelitian menunjukkan bahwa AdGuard Home mampu mendeteksi dan memblokir hingga 97,5% domain berbahaya dengan response time rata-rata 35 ms dan throughput mencapai 12.000 query per second. Overhead kontainerisasi relatif kecil dan tidak mengganggu fungsi inti router. Penelitian ini menyimpulkan bahwa integrasi AdGuard Home pada kontainer MikroTik efektif sebagai solusi monitoring jaringan yang cost-effective, scalable, dan aman.
Co-Authors Andayani, Nurfitri Andiani, Lia Andini, Lia Apriana, Diwi Aprilyanti, Cindy Bainamus, Putri Milanda Dona, Dona edy susanto Hendri Maradona, Hendri Kiki Yasdomi Maslukin, Maslukin Murlena, Murlena RACHMAT HIDAYAT Rahayu, Dina Ramadana, Radiyah Rifqi, Mi’rajul Sabri, Khairul Susmita, Afnes