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All Journal Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer Scine and Information Technology
Muhammad Hafizh
Universitas Putra Indonesia YPTK Padang
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology

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Utilization of IT Business Management for Marketing Development with the Analytical Hierarchy Process Method Andreas Malau; Sumijan; Muhammad Hafizh
Journal of Computer Scine and Information Technology Volume 9 Issue 3 (2023): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v9i3.75

Abstract

Marketing development is an important factor in a business that must be considered to increase market share. Choosing the right marketing strategy greatly influences the smooth running of sales. This study aims to determine a decision on the right marketing method so that it can be applied by Rozi Bike Shop in expanding its market share. Determination of the marketing strategy at the Rozi bicycle shop is determined based on four criteria, namely organization, product, place and distribution channel. The four criteria are analyzed and processed using the Analytical Hierarchy Process (AHP) method in order to obtain an appropriate marketing decision to implement. method The Analytical Hierarchy Process (AHP) is a multicriteria decision method for solving complex or complex problems, in unstructured situations into parts (variables) which are then formed into functional hierarchies or network structures. The results of calculations using the AHP method show that Strategy A (Technological Innovation) gets the highest value, namely 0.46984 . The results obtained from this study are a decision-making system designed using the AHP method and the application of IT business management in developing the store's marketing.
A hybrid data mining for predicting scholarship recipient students by combining K-means and C4.5 methods Halifia Hendri; Harkamsyah Andrianof; Riska Robianto; Hasri Awal; Okta Andrica Putra; Romi Wijaya; Aggy Pramana Gusman; Muhammad Hafizh; Muhammad Pondrinal
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 3: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i3.pp1726-1735

Abstract

This scholarly investigation delves into the strong desire for academic scholarships within the student body, especially prominent among socioeconomically disadvantaged individuals. The study aims to formulate a hybrid data mining paradigm by synergizing the K-means and C4.5 methodologies. K-means is applied for clusterization, while C4.5 facilitates prediction and decision tree instantiation. The research unfolds in sequential phases, commencing with data input and progressing through meticulous pre-processing, encompassing data selection, cleaning, and transformation. The novelty lies in successfully integrating the K-means and C4.5 methodologies, culminating in the hybrid data mining method. The dataset comprises 200 students seeking scholarships, revealing effective stratification into three clusters—cluster 0, cluster 1, and cluster 2—with 119, 48, and 33 students, respectively. The K-means method proves highly suitable, especially when combined with C4.5, for predicting scholarship recipients. A subset of 81 students from clusters 1 and 2 undergoes predictive modeling using C4.5, resulting in a commendable 85% accuracy, with 17 accurate forecasts and 3 minor inaccuracies. This research significantly enhances scholarship selection efficiency, particularly benefiting socioeconomically disadvantaged students.
Co-Authors Aggy Pramana Gusman Andreas Malau Halifia Hendri Harkamsyah Andrianof Hasri Awal Muhammad Pondrinal Okta Andrica Putra Riska Robianto Romi Wijaya Sumijan