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All Journal Jurnal TIMES JURTEKSI Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Purba, Yuegilion Pranayama
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Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Penerapan Data Mining pada Tata Letak Buku Di Perpustakaan Sintong Bingei Pematangsiantar dengan Metode Apriori Andini, Yulia; Hardinata, Jaya Tata; Purba, Yuegilion Pranayama
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 7, No 1 (2022): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v7i1.410

Abstract

The library is a place that has a large collection of knowledge books, magazines and other media that are arranged or arranged in a certain way so that it is easy for users to use properly and well. In placing books in the library, books are placed according to the book category given the numbering. However, the placement of books has not been regulated by looking at the level of books that are often borrowed and many visitors find it difficult to find books that are often borrowed. So it is necessary to create a system using a priori data mining method to determine the pattern of book layout arrangement in the library, this system can help to make it easier to determine the layout of the book as needed. Based on the results of the implementation of RapidMiner, the highest combination pattern of library book layout is Pure Science and Social Sciences with 50% support and 86% confidence. General Works and Pure Science were obtained with 41% support and 83% confidence. Furthermore, Public Works and Social Sciences with 41% support and 83% confidence.
PENERAPAN DATA MINING TERHADAP TATA LETAK BUKU DI PERPUSTAKAAN SINTONG BINGEI PEMATANGSIANTAR MENGGUNAKAN METODE APRIORI Andini, Yulia; Hardinata, Jaya Tata; Purba, Yuegilion Pranayama
Jurnal TIMES Vol 11 No 1 (2022): Jurnal TIMES
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51351/jtm.11.1.2022661

Abstract

Perpustakaan adalah tempat yang memiliki banyak koleksi buku pengetahuan, majalah dan media lainnya yang ditata atau diatur dengan cara tertentu agar mudah dimanfaatkan oleh para pengguna secara tepat dan baik. Dalam melakukan  penempatan buku diperpustakaan, buku yang diletakkan sesuai kategori buku yang diberikan penomoran. Namun penempatan buku-buku belum diatur dengan melihat tingkat buku mana yang sering dipinjam dan para pengunjung banyak yang merasa kesulitan dalam mencari kembali buku yang sering dipinjam. Maka perlu dibuat sebuah sistem menggunakan data mining metode apriori untuk menentukan pola penataan tata letak buku diperpustakaan, sistem ini dapat membantu untuk mempermudah dalam menentukan tata letak buku yang sesuai kebutuhan. Berdasarkan hasil implementasi dari RapidMiner, maka diperoleh pola kombinasi tata letak buku perpustakaan paling tinggi adalah Ilmu Murni dan Ilmu Sosial dengan support 50% dan confidence 86%. Kemudian selanjutnya diperoleh Karya Umum dan Ilmu Murni dengan support 41% dan confidence 83%. Selanjutnya Karya Umum dan Ilmu Sosial dengan support 41% dan confidence 83%.
Application of the C5.0 Algorithm to Determine the Level of Public Satisfaction with the E-KTP Recording Service at the Bandar Sub-District Office Hardani, Dini Fadila; Poningsih; Purba, Yuegilion Pranayama
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (677.344 KB) | DOI: 10.59934/jaiea.v1i1.49

Abstract

Community satisfaction at the Bandar Sub-district Office is one of the most important things in assessing the level of e-KTP recording services provided by the agency to the community. The purpose of this study was to determine the quality of the e-KTP recording service at the Bandar Sub-district Office in terms of the Service Procedure, Time, Behavior and Facilities aspects of the Bandar sub-district community. At the Bandar Camat Office these four aspects have not been measured with certainty, so the agency finds it difficult to determine which aspects must be improved. The method used in this study is the C5.0 Algorithm, where the data source used is a questionnaire/questionnaire technique given to the people of Bandar sub-district. The research test process uses Rapid Miner software to create a decision tree. The results of the study obtained 12 rules for classifying the level of community satisfaction with e-KTP recording services. The C5.0 algorithm can be used in cases of community satisfaction with an accuracy rate of 100%. From these results, it is expected to improve the quality of service for the e-KTP recording of the Bandar Sub-District Office to be even better.
Application Of The C4.5 Algorithm To Determining Student's Level Of Understanding Adeita A. Ndraha; Hardinata, Jaya Tata; Purba, Yuegilion Pranayama
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 2 (2022): February 2022
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (939.638 KB) | DOI: 10.59934/jaiea.v1i2.84

Abstract

This research was conducted to find the rules of the model in measuring the level of students' understanding of the subject. During this pandemic, the learning process is carried out online, so it is difficult to measure students' ability to master the material. This measurement needs to be done so that the evaluation process can be carried out so that the ability of students in one group to achieve the target level of understanding. Currently, evaluation activities have never been carried out because they do not have a model so that evaluation can only be done by giving quizzes and exercises. This problem can be solved by using data mining algorithm C4.5. Attributes used as parameters for assessing student understanding of lessons such as Teaching Method (C1), Learning Media (C2), Communication (C3), Experience (C4), Teaching Materials/Modules/Assignments (C5), Learning Duration (C6). The six attributes are used to find the relationship between each other that influence each other to get the highest root so that a decision tree will be obtained that produces the rules of the relationship between each attribute in determining student understanding of the subject. This rule or rule will be used as the basis for making an information system so that it can be applied to end users, namely schools.
BACKPROPAGATION ALGORITHM IN PREDICTING THE AMOUNT OF WEST SIANTAR POPULATION GROWTH Setiana, Rika; Purba, Yuegilion Pranayama; Safii, Muhammad
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 1 (2023): Desember 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i1.2890

Abstract

Abstract: Indonesia is included in the category of developing countries and is a country with a relatively large population. According to data from the Pematang Siantar City Population and Civil Registration Service, West Siantar District is one of the sub-districts in Pematang Siantar City whose population continues to increase and this will lead to an increase in poverty and unemployment rates. To overcome the above problems, a method is needed to analyze the population growth of West Siantar, one of which is using the Backpropagation method. This research will use training data starting from 2017-2021 and test data from 2018-2022. The results carried out using MATLAB R2011a software show the best architecture 4-19-1 with an accuracy of 100 with an MSE number of 0.00010031375 and an epoch value of 124777. Based on the research carried out, the population of West Siantar in the next year is 86067 people. It is concluded that backpropagation can be used as a method that makes it easier to search for predictions and the level of accuracy obtained depends on the architecture used.            Keywords: Birth; Growth; Matlab; Predictions; Resident Abstrak: Indonesia termasuk dalam kategori negara berkembang dan merupakan negara dengan jumlah penduduk yang relatif besar. Menurut data Dinas Kependudukan dan Catatan Sipil Kota Pematang Siantar, Kecamatan Siantar Barat merupakan salah satu kecamatan di Kota Pematang Siantar yang jumlah penduduknya terus meningkat dan hal ini akan berdampak pada peningkatan angka kemiskinan dan pengangguran. Untuk mengatasi permasalahan diatas diperlukan suatu metode untuk menganalisis pertumbuhan penduduk Siantar Barat, salah satunya adalah dengan menggunakan metode Backpropagation. Penelitian ini akan menggunakan data latih mulai tahun 2017-2021 dan data uji 2018-2022. Hasil yang dilakukan dengan menggunakan software MATLAB R2011a menunjukkan arsitektur terbaik 4-19-1 dengan akurasi 100 dengan angka MSE 0.00010031375 dan nilai epoch 124777. Berdasarkan penelitian yang dilakukan, populasi Siantar Barat di tahun berikutnya sebanyak 86067 orang. Disimpulkan bahwa backpropagation dapat digunakan sebagai metode yang memudahkan pencarian prediksi dan tingkat akurasi yang diperoleh tergantung pada arsitektur yang digunakan. Keywords: Kelahiran; Matlab; Pertumbuhan; Penduduk; Prediksi
BACKPROPAGATION ANALYSIS IN SELECTING THE BEST ARCHITECTURE TO PREDICTION THE NUMBER OF POPULATION OF SIANTAR MARTOBA Afatandio, Arril; Purba, Yuegilion Pranayama; Safii, Muhammad
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 3 (2024): Juni 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i3.2891

Abstract

Abstract: Basically, this region experiences growth every year. The negative impact of uncontrolled population growth will cause social inequality and poverty and affect the progress and prosperity of the region. Judging from the number of residents registered with the Population and Civil Registration Service, Siantar Martoba District has a fairly high population growth rate, so it is necessary to predict the future population. In making a prediction, a good method is needed to solve a problem. In this research, a backpropagation algorithm was used using five architectures, namely architecture 4-71-1, 4-31-1, 4-16-1, 4-72-1, 4-83-1. From the results of tests carried out using data on the population of Siantar Martoba, the best architecture was obtained, namely architecture 4-31-1 with a mean squared error for training of 0.00009960 and a mean squared error for testing of 0.000099957 and obtained an epoch of 14012 iterations with a time of 01 minutes 40 seconds. It was concluded that this method can predict the population of Siantar Martoba in the future using Matlab R2011a, thus obtaining a population of Siantar Martoba of 36470 people.            Keywords: architecture; backpropagation; pematangsiantar; population; welfare  Abstrak: Pada dasarnya, wilayah ini mengalami pertumbuhan setiap tahunnya. Dampak negatif pertumbuhan penduduk yang tidak terkendali akan menyebabkan kesenjangan sosial dan kemiskinan dan mempengaruhi kemajuan, kesejahteraan daerah tersebut. Dilihat dari jumlah penduduk yang terdaftar pada Dinas Kependudukan dan Pencatatan Sipil Kecamatan siantar martoba mempunyai laju pertumbuhan penduduk yang cukup tinggi, sehingga perlu dilakukan prediksi jumlah penduduk masa depan. Dalam melakukan sebuah prediksi dibutuhkan sebuah metode yang baik dalam menyelesaikan sebuah permasalahan, dalam penelitian ini digunakan algoritma backpropagation dengan menggunakan lima arsitektur yaitu arsitektur 4-71-1, 4-31-1, 4-16-1, 4-72-1, 4-83-1. Dari hasil pengujian yang telah dilakukan dengan menggunakan data jumlah penduduk siantar martoba diperoleh arsitektur terbaik yaitu arsitektur 4-31-1 dengan nilai mean squared error pelatihan 0.00009960 dan mean squared error pengujian 0.000099957 dan memperoleh epoch 14012 iterations dengan waktu 01 menit 40 detik. Disimpulkan bahwa metode ini dapat memprediksi jumlah penduduk Siantar Martoba di masa depan dengan menggunakan Matlab R2011a, sehingga memperoleh jumlah penduduk siantar martoba sebanyak 36470 Jiwa. Kata kunci: arsitektur; backpropagation; pematangsiantar; kependudukan; kesejahteraan 
Co-Authors Adeita A. Ndraha Afatandio, Arril Andini, Yulia Hardani, Dini Fadila Jaya Tata Hardinata Muhammad Safii Poningsih Setiana, Rika