Article Per Year (5 Year)
p-Index From 2017 - 2022
0.751
P-Index
This Author published in this journals
All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Jurnal Komtekinfo
Liga Mayola
Universitas Putra Indonesia YPTK Padang
Arts Computer Science & IT Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Analisis Hybrid Decision Support System dalam Penentuan Status Kelulusan Mahasiswa Dodi Guswandi; Musli Yanto; M. Hafizh; Liga Mayola
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 6 (2021): Desember 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (542.458 KB) | DOI: 10.29207/resti.v5i6.3587

Abstract

Determination of graduation status is often faced by lecturers in every university. The facts show that many of the decisions still have a fairly high error rate in determining graduation status. This study aims to develop an analytical model in the process of determining student graduation using the Hybrid Decision Support System (DSS). The methods used in the analysis process are Analytical Hierarchy Process (AHP) and Technique for Others Preference by Similarity to Ideal Solution (TOPSIS). The performance of AHP can determine the value of the weight criteria and TOPSIS performs rankings to produce solutions in determining. The criteria indicators used to consist of Depth (C1), Material Breadth (C2), Answer Accuracy (C3), Fluency of Answers (C4), Scientific Attitude (C5), Logical Consistency of Content (C6), Authenticity (C7), Scientific Quality ( C8), Language (C9), and Writing (C10). The results of this study indicate that the Analytical Hierarchy Process (AHP) method provides a weighting value for each criterion with a fairly good accuracy rate of 85,86%. These results conclude that each criterion has a consistent level of relationship in determining student graduation. Based on the output of the TOPSIS analysis, the results presented can determine the student's graduation status correctly and accurately.
Implementasi E-Commerce Untuk Memperluas Pangsa Pasar Hasil Kerajinan UMKM Komunitas Hobi Kayu Padang Febri Hadi; Yuhandri Yuhandri; Liga Mayola
JDISTIRA Vol. 1 No. 1 (2021)
Publisher : JDISTIRA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1022.177 KB)

Abstract

Setiap UMKM sebenarnya sudah mempunyai ciri khas dari masing-masing produknya, terlebih lagi cara pengolahan kerajinan kayu. Tetapi yang perlu dilakukan disini adalah bagaimana produk milik UMKM tersebut dapat dipasarkan secara nasional maupun internasional dengan memanfaatkan E-Commerce. Selain itu dengan sosialisasi strategi pemasaran produk ini, tentunya juga bisa membantu meningkatkan penjualan UMKM tersebut. Terlebih Kota Padang merupakan Ibukota Sumatera Barat yang mana banyak dikunjungi oleh para wisatawan dari berbagai daerah di Indonesia.
Clustering Tingkat Penjualan Menu (Food and Beverage) Menggunakan Algoritma K-Means Hadi Syahputra; Liga Mayola; Dodi Guswandi
Jurnal KomtekInfo Vol. 9 No. 1 (2022): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (409.485 KB) | DOI: 10.35134/komtekinfo.v9i1.274

Abstract

Menu planning in a restaurant is part of the sales strategy. Each menu has a different level of sales. To determine the effectiveness of sales and raw materials, restaurants need knowledge of what menus need to be maintained and vice versa. An analysis that can determine the sales level menu is the analysis of the k-means algorithm data mining clustering method. The source of research data is from the history of menu sales transactions for 1 year, then analyzed by the k-means algorithm. The information found is in the form of popular F&B menus and sales level menus. The purpose of this study is to group the data menu on the level of sales (Food and Beverage). The method used is the Clustering method with the performance of the K-Means algorithm. The results showed that the clustering method with the K-Means algorithm gave a significant output in grouping sales data. The research contribution provides knowledge in the form of information in conducting sales data management
Co-Authors Dodi Guswandi Febri Hadi Guswandi, Dodi Hadi Syahputra M. Hafizh Muhammad Hafizh Musli Yanto Yuhandri Yuhandri, Yuhandri