Academic Decision Support System for Choosing Information Systems Sub Majors Programs using Decision Tree Algorithm

Fiarni, Cut; Sipayung, Evasaria Magdalena; Tumundo, Prischilia B.T.

doi:10.20473/jisebi.5.1.57-66

Cited by 17 publications

(15 citation statements)

References 10 publications

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“…Yaacob et al propose the supervised data mining approach for predicting student performance, which concludes complex decision tree classifier in their experiments [9]. Fiarni et al designed an academic decision support system for choosing information systems submajors programs using decision tree algorithm [10]. e influencing factors of the research can affect the academic performance of students, but some key factors that ignore the current online learning affect learning, such as the completion of the video point to complete the task and the length and quantity of the video to watch the partial test completion.…”

Section: Related Workmentioning

confidence: 99%

The Evaluation of Online Education Course Performance Using Decision Tree Mining Algorithm

Yang

2021

Complexity

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With the continuous development of “Internet + Education”, online learning has become a hot topic of concern. Decision tree is an important technique for solving classification problems from a set of random and unordered data sets. Decision tree is not only an effective method to generate classifier from data set, but also an active research field in data mining technology. The decision tree mining algorithm can classify the data, grasp the teaching process of the teacher, and analyze the overall performance of the students, so as to realize the dynamic management of the educational administration and help the educational administration personnel to make the right decision, with more reasonable allocation of resources. This paper evaluates students’ academic performance based on the learning behavior data of online learning, so as to intervene in students’ learning in advance, which is the key problem that needs to be solved at present. Taking students’ learning attitude, completion of homework, and attendance as factors, the paper uses decision tree technology to analyze the factors affecting students’ performance, and evaluates students’ performance. Firstly, this paper collects the high-dimensional behavioral characteristic data of students’ online learning and conducts correlation analysis after preprocessing the behavioral characteristic data. Then, the decision tree C4.5 algorithm is used to construct a performance evaluation model. Students’ performance is evaluated by the model, and the evaluation accuracy is about 88% compared with actual performance. Finally, through the model analysis, it is concluded that the video task point completion is the most influential in students’ achievement, followed by chapter test completion and chapter test average score, and the course interaction amount and homework average score are the least influential in students’ achievement, which has a practical reference value for effectively serving online learning and teachers’ teaching.

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Section: Related Workmentioning

confidence: 99%

The Evaluation of Online Education Course Performance Using Decision Tree Mining Algorithm

Yang

2021

Complexity

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“…Hasil perhitungan dari nilai preferensi akan dihitung kembali untuk memperoleh nilai indeks preferensi dengan rumus pada persamaan (7).…”

Section: B) Menghitung Indeks Preferensiunclassified

Pemilihan Transportasi Bus Antar Kota Antar Provinsi (AKAP) Dengan Metode Simple Additive Weighting (SAW), Weighted Product (WP), dan Promethee Berbasis Android

Riyadi¹,

Andryana

Winarsih

2021

jtik

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The migrants who have increased every year made bus transportation be one of the most widely used transportation for the Wonogiri’s people to go home to their hometowns. In Wonogiri district, bus transportation is available from various companies, ranging from local companies and non local who have primacy facilities, services, and a diverse bus fleet. The application of a decision support system is to make it easier for prospective passengers to make choices according to the desired criteria can be done using the Simple Additive Weighting, Weighted Product, and Promethee methods. The methods calculates the value of each criteria, weight criteria, criteria type, and is easy to apply to solve problems related to multi-criteria. There are 5 criteria used and 17 different bus companies as alternatives. The existence of this system is expected to make it easier for prospective passengers to decide the bus according to the desired criteria.Keywords:Promethee; Simple Additive Weighting; Weighted Product.

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“…Sistem pendukung keputusan adalah teknologi dan aplikasi yang dapat membantu pembuat keputusan dalam menyusun informasi yang berguna dari data mentah terkait untuk mengidentifikasi dan menyelesaikan masalah. Komponen utama DSS cocok data, model, pengetahuan yang diperoleh dari pemodelan data, dan antarmuka pengguna [5]. Pada penelitian ini akan menggunakan metode weighted product .…”

Section: Iunclassified

Sistem Pendukung Keputusan Menggunakan Metode Weighted Product untuk Pemilihan Karyawan Terbaik UMKM ZainToppas

Yudistira

Sari

2020

SISFOKOM

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Every company needs employees as a force that runs every activity in the corporate organization. In order to achieve the targets that have been compiled by the management, all employees should show maximum performance, therefore to improve the performance of employees so that the targets that have been drafted can be achieved, UMKM ZainToppas will give reward to the best employees that have been chosen, but in the selection of best employees ZainToppas has to implement the right decision support Based on this, it will be built a decision support system by using method weighted product to solve problems that occur in UMKM ZainToppas for the selection of the best employees who are entitled to receive reward in accordance with criteria-criteria that have been determined and more objective. The development of the system using waterfall method and scanning method of weighted product, the output of this system is an alternative that has the highest v vector value, the intended alternative is the employee, then the employee is entitled to receive the reward as the best employee.

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Academic Decision Support System for Choosing Information Systems Sub Majors Programs using Decision Tree Algorithm

Cited by 17 publications

References 10 publications

The Evaluation of Online Education Course Performance Using Decision Tree Mining Algorithm

The Evaluation of Online Education Course Performance Using Decision Tree Mining Algorithm

Pemilihan Transportasi Bus Antar Kota Antar Provinsi (AKAP) Dengan Metode Simple Additive Weighting (SAW), Weighted Product (WP), dan Promethee Berbasis Android

Sistem Pendukung Keputusan Menggunakan Metode Weighted Product untuk Pemilihan Karyawan Terbaik UMKM ZainToppas

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