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Universitas Potensi Utama
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Implementation of Artifical Neural Networks with Multilayer Perceptron for Analysis of Acceptance of Permanent Lecturers Hartono Hartono; Muhammad Sadikin; Dian Maya Sari; Nur Anzelina; Silvia Lestari; Wulan Dari
Jurnal Mantik Vol. 4 No. 2 (2020): Augustus: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2020.954.pp1389-1396

Abstract

Lecturer acceptance selection is the first step in building an education. The Multilayer Perceptron method can be applied in the case of permanent lecturer admissions. The problem faced in the admission of permanent lecturers is that reception is still subjective. This research will prove the ability of the Multilayer Perceptron algorithm to classify eligibility as a lecturer or not. Inputs from this study were prospective applicants' data, namely age, grade point average (GPA), written test score, interview value, and home base status. Sample data amounted to 100 data. 75% of the data is used as training data, and 25% as test data. The test results of the accuracy of the data are known that the multilayer perceptron neural network method has an accuracy rate of 98.7% and with a ROC Area value of 0.989. This proves that the application of the model used belongs to the classification category very well because it has a ROC value between 0.90-1.00.
Implementasi Algoritma K-Means Untuk Penerimaan Siswa Baru Di SMANPAS Berdasarkan Nilai Rapot dan Hasil Tes Efani Desi; Siti Aliyah; Silvia Lestari; Wulan Dari
IT (INFORMATIC TECHNIQUE) JOURNAL Vol 10, No 1 (2022): IT JOURNAL APRIL 2022
Publisher : Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/it.10.1.2022.01-10

Abstract

SMANPAS atau dikenal dengan SMA Negri Pasirian merupakan lembaga pendidikan yang cukup populer dikalangan lembaga pendidikan lainnya, selain prestasi yang telah didapatkan di SMANPAS, rata rata lulusan dari SMANPAS akan mendapatkan kemudahan untuk masuk Universitas. Sehingga tidak sedikit para pelajaran lulusan smp berlomba agar bisa diterima di SMANPAS. Melihat banyaknya pelajar yang ingin diterima di SMANPAS membuat SMA ini kesulitan dalam menyeleksi para pelajar yang mendaftar sehingga SMANPAS mulai menerapkan Algoritma K-Means guna menyeleksi para pelajar.  Metode K-Means merupakan salah satu alternatif yang cukup efektif, dimana  Metode K-Means ini merupakan sebuah metode yang berfungsi untuk mengelompokan data yang ada ke dalam Cluster berdasarkan data yang telah ditetapkan atau data yang sama[1,2,3]. Dipenelitian ini diambil 8 Pelajar baru yang memiliki 2 nilai , yaitu nilai raport dan nilai tes ujian  dimana dari hasil penelitian ini akan  menghasilkanan 4 orang pelajar baru akan diterima berdasarkan perhitungan K-Means dengan titik acuan atau Cluster dengan nilai 91 untuk nilai raport dan 88 untuk hasil tes ujian, 2 Orang pelajar baru  sebagai cadangan dengan Cluster nilai 70 untuk raport dan 70 untuk hasil tes ujian, dan 2 Orang pelajar yang tidak diteriman di SMANPAS dengan Cluster nilai 60 untuk raport dan 70 untuk hasil tes ujian..
Analisis Metode Apriori Untuk Memprediksi Persediaan Barang Pada Warung Wulan Dari
INSOLOGI: Jurnal Sains dan Teknologi Vol. 1 No. 4 (2022): Agustus 2022
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v1i4.807

Abstract

The data processing system in the shop is still manual. Previously, the shop had not been able to predict the stock or inventory of goods. Therefore, this system predicts the inventory of goods in the shop. so that the data processing system at the shop can be handled by problems that occur and can form information quickly, precisely, and well. The use of the a priori method which will be used to calculate the prediction of the supply of goods in stock that is still there. And this a priori method will later be used to calculate odds. Data storage using SQL Server database. With the development of technology, the ability to collect and process data is also growing. Data processing has become the advantage of computers, computers have also penetrated various aspects, both in the field of education and in the business world. Competition in the global business has built tight competition between one stall and another. This algorithm is used to analyze when purchasing goods that have run out of stock by classifying which goods have been added to stock or not, as a result, the availability of goods remains stable and maintained. The author is currently making inventory predictions at the stalls to develop an existing system with the a priori method.
Analisis Tingkat Kepuasan Pengguna Aplikasi Ojek Online Dengan Metode Naive Bayes Wulan Dari; Elen Tania Hanayah
INSOLOGI: Jurnal Sains dan Teknologi Vol. 2 No. 1 (2023): Februari 2023
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v2i1.1693

Abstract

In today's digital era, activities in various transportation service processes are increasingly sophisticated, which of course makes the implementation process easier. One example of the impact that can be felt is the presence of an online-based motorcycle taxi service which is the latest breakthrough in the development of technology and information in the field of transformation which is currently being increasingly used and favored by the public. Analyzing the level of satisfaction of online motorcycle taxi users also needs to be carried out, in order to find out how the public views the quality of services that have been provided by drivers. This study uses survey methods, literature studies and the application of the Naive Bayes algorithm. The results of this study are able to provide detailed explanations and elaborations regarding how the level of satisfaction is from the point of view of online motorcycle taxi service users and related to the indicators used using the Naive Bayes algorithm. From the results of this study, it is hoped that it can become a source of reference on how important it is to understand and implement the use of naive bates in making decisions from a number of data, one of which is in terms of determining the level of user satisfaction with what is provided by online motorcycle taxi drivers.
Co-Authors Dian Maya Sari Efani Desi Elen Tania Hanayah Hartono Hartono Muhammad Sadikin Nur Anzelina Silvia Lestari Siti Aliyah