Application of the Profile Matching Analysis Method in Decision Support Systems for Study Program Recommendations

Abstract

Currently, many prospective students are still confused about which study program to choose. One of the problematic factors is the lack of references from prospective students about the contents of each study program. This research aims to build a decision support system for study program recommendations using the Profile Matching Analysis method. The benefits of this research can provide final results in the form of recommended study program scores that are most suitable for prospective students. There are 5 assessment criteria used in this research, namely Language Values, Logic/IT Values, Science Values, Practice Values, and Social Values. The methods or stages carried out in this research are: data collection, system flowchart design, application of the Profile Matching Analysis method and system implementation. In this research, the recommendation results were obtained for a student with the name Afni Ruhmini based on the results of system calculations using the Profile Matching Analysis method, obtaining recommendation results for the Public Administration study program with a score = 5.3, the Marine Science study program with a score = 5.9, and the Agribusiness study program with a score = 5.6, the Physics Education study program with a score = 5.7 and the Law study program with a score = 4.8. The Profile Matching Analysis method is very suitable to be applied to solve problems in decision support system research for study program recommendations.

Classification System for Soil Types Suitable for Food Crops using Naïve Bayes Method

“…In addition to this research, there are several studies that have been conducted by researchers related to the application of data mining methods and the creation of application systems, including research on the classification of student scientific papers using the naive bayes classifier method. [21], The implementation of fuzzy c-means to determine the level of student satisfaction in online learning [22], application of data mining to determine recipients of non-cash food assistance using the k-nearest neighbor method [23], decision support system for determining PKH acceptance using the naïve bayes method [24], application of the profile matching analysis method to the decision support system for study program recommendations [25] and implementation of data mining to analyze student competition categories using the apriori algorithm [26]…”

Application of Profile Matching in Determining Employee Annual Bonuses

“…A bonus is an additional remuneration given to certain employees whose performance is above the standard performance. This bonus serves as a tool to support the principle of fairness in compensation distribution [13]. Employees are one of the most important assets a company has to maintain its survival, growth, and competitive ability, as well as to gain profit.…”

Analisa Data Mining Dalam Memprediksi Masyarakat Kurang Mampu Menggunakan Metode K-Nearest Neighbor

“…Disamping penelitian ini ada beberapa penelitian yang telah dilakukan oleh peneliti yang terkait dengan data mining diantaranya, penelitian penerapan data mining untuk menentukan penerima bantuan pangan non tunai menggunakan metode k-nearest neighbor [10], penelitian sistem pendukung keputusan penentuan penerimaan bantuan pkh menggunakan metode naïve bayes [11], dan penelitian penerapan metode Profile Matching Analisis pada sistem pendukung keputusan rekomendasi Program Studi [12].…”