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All Journal Scientific Journal of Informatics Jurnal CoreIT
Nazir, Alwis
UIN Sultan Syarif Kasim Riau
Computer Science & IT

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Toddler Nutritional Status Classification Using C4.5 and Particle Swarm Optimization Nazir, Alwis; Akhyar, Amany; Yusra, Yusra; Budianita, Elvia
Scientific Journal of Informatics Vol 9, No 1 (2022): May 2022
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v9i1.33158

Abstract

Abstract. Purpose: This research was conducted to create a classification model in the form of the most optimal decision tree. Optimal in this case is the combination of parameters used that will produce the highest accuracy compared to other parameter combinations. From this best model, it will be used to predict the nutritional status class for the new data.Methods/Study design/approach: The dataset used is from Nutritional Status Monitoring in 2017 in Riau Province, Indonesia. From the dataset, the Knowledge Discovery in Database (KDD) stages were carried out to build several classification models in the form of decision trees. The decision tree that has the highest accuracy will then be selected to predict the class for the new data. Predictions for new data (unclassified data) will be made in a web-based system.Result/Findings: Particle Swarm Optimization is used to find optimal parameters. Before PSO is used, there are 213 parameters in the dataset that can be used to do classification. However, using many such parameters is time-consuming. After PSO is used, the optimal parameters found are the combination of 4 parameters, which can produce the most optimal decision tree. The 4 chosen parameters are gender, age (in months), height, and the way to measure the height (either stand up or lie down). The most optimal decision tree has an accuracy of 94.49%. From the most optimal decision tree, a web-based system was built to predict the class for new data (unclassified data).Novelty/Originality/Value: Particle Swarm Optimization (PSO) is a method that can help to select the most optimal parameters, or in other words produce the highest classification accuracy. The combination of parameters selected has also been confirmed by the nutritionist. The prediction system has been declared feasible to be used by nutritionists through the User Acceptance Test (UAT).
Implementasi Algoritma FP-Growth untuk Menemukan Pola Keterkaitan Antara Matakuliah Pemrograman dan Matakuliah Matematika Putri. P, Zurneli Kurnia; Iskandar, Iwan; Nazir, Alwis
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 7, No 2 (2021): Desember 2021
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (423.192 KB) | DOI: 10.24014/coreit.v7i2.15351

Abstract

The specification of programming skills is one of the focuses of learning in the Informatics Engineering study program which requires students to understand and get good grades in all courses related to programming. The subject that is considered to have a relationship with the programming field is the Mathematics course. Efforts to determine the correlation between programming courses and mathematics courses through one of the association algorithms in data mining, namely the FP-Growth algorithm. FP-Growth was chosen because it has a faster data pattern execution rate than the a priori algorithm. The final stage of KDD produces 1227 data which is then processed using the FPGrowth algorithm. Tests with a minimum support value of 0.5 and minimum confidence of 0.7 show the same number of patterns between applications built with the SPMF application of 52250 patterns. The highest support value of 51% and the highest confidence value of 98% and the highest lift ratio value of 1.1941 in the combination of itemset patterns indicate that if students pass programming courses, then mathematics courses can also pass or vice versa.
Data Warehouse Design For Sales Transactions on CV. Sumber Tirta Anugerah Syaputra, Muhammad Dwiky; Nazir, Alwis; Gusti, Siska Kurnia; Sanjaya, Suwanto; Syafria, Fadhilah
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 8, No 2 (2022): December 2022
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (644.133 KB) | DOI: 10.24014/coreit.v8i2.19800

Abstract

Many data warehouses are implemented in companies engaged in retail, CV. Sumber Tirta Anugerah is one of the paint product retail companies that has not implemented it yet. As time goes by, the sales transaction data is getting more and more difficult to process because it is still stored in Microsoft Excel. This is a serious problem in utilizing historical data to assist in making a decision. It is difficult to store sales data because the data is quite large and a lot. Based on the above problems, a data warehouse design is needed for sales transaction data. This data warehouse design uses Kimball's nine-steps method and star schema. To perform the ETL process (extract, transform, and load) using Pentaho software. In this data warehouse design, Tableau software is used to visualize the processed data into a graph and dashboard report. The result of this research is a data warehouse design using nine steps and a star schema which gets a transformation response time of 4048 MS. 
Co-Authors Akhyar, Amany Elvia Budianita Fadhilah Syafria Gusti, Siska Kurnia Iwan Iskandar Putri. P, Zurneli Kurnia Suwanto Sanjaya Syaputra, Muhammad Dwiky Yusra, Yusra