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All Journal AdMathEdu : Jurnal Ilmiah Pendidikan Matematika, Ilmu Matematika dan Matematika Terapan Jurnal Sains Matematika dan Statistika JUTEI (Jurnal Terapan Teknologi Informasi) Jambura Journal of Mathematics Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Jurnal Ilmiah Matematika Bulletin of Applied Mathematics and Mathematics Education
Purwadi, Joko
Program Studi Matematika, Fakultas Sains Dan Teknologi Terapan, Universitas Ahmad Dahlan Yogyakarta
Arts Humanities Computer Science & IT Education Environmental Science Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Face pattern recognition using Expectation-Maximization (EM) algorithm Purwadi, Joko; Hernadi, Julan; Suryantoro, M. Danang
Bulletin of Applied Mathematics and Mathematics Education Vol. 2 No. 1 (2022)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (824.735 KB) | DOI: 10.12928/bamme.v2i1.5520

Abstract

This paper discuss about the use face patteren recognition which is now days become popular especialy on smartphone lock screen system. The method used in this research are the Expectation – Maximization (EM) Algorithm. EM Algorithm is an iterative optimization method for the estimation of Maximum Likelihood (ML) which is used in incomplete data problems. there are 2 stages, namely the Expectation stage E (E-step) and the Maximization stage M (M-step). These two stages will continue to be carried out until they reach a convergent value. The result of the research shows that EM Algorthm produce high accuracy, it’s about 95% on the data training and 83% accuracy on the data testing.
Support Vector Regression optimization with Particle Swam Optimization algorithm for predicting the gold prices Selviani, Novi; Purwadi, Joko
Bulletin of Applied Mathematics and Mathematics Education Vol. 3 No. 2 (2023)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/bamme.v3i2.9561

Abstract

This paper discusses about how to predict the gold prices from 1 January 2021 to 31 January 2023. The method used in this study is the Support Vector Regression (SVR) technique, method that was developed from the support vector machine which is used as regression approach to predict future event. From the past study already know that SVR had limitation in achieving good performance because of its sensitivity to parameters. To overcome the SVR performance problems, an optimization algorithm is proposed in this study. The PSO algorithm is applied in this study to optimize the parameters of the SVR method. The results showed that the prediction of the SVR model obtained an MSE value of 0.0035744. While in the SVR model with the PSO algorithm, the MSE value is 0.0033058.
Pembuatan Sistem Penerimaan Peserta Didik Baru SMP Maria Immaculata Berbasis Website F. Yogiswara Adinugraha P; Yuan Lukito; Joko Purwadi
Jurnal Terapan Teknologi Informasi Vol 9 No 1 (2025): Jurnal Terapan Teknologi Informasi
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21460/jutei.2025.91.386

Abstract

The research aims to develop a student admission system for Maria Immaculata Junior High School to improve the current inefficient process relying on Google Forms and manual document submission. In This Article, The waterfall methodology will be employed for system development, while questionnaires and usability testing will be used for user evaluation then using through questionnaires and usability testing. The research will involve PPDB (Penerimaan Peserta Didik Baru) staff and parents as respondents. Initial requirements will be gathered through observation and interviews with PPDB committee members. After analysis, the system's database and user interface will be designed and implemented. Testing will be conducted with PPDB staff to obtain feedback and make necessary improvements who can impacted to School or programs. Finally, the system will be deployed for public use. The system's usability was evaluated through questionnaires and usability testing. The results indicate high levels of ease of use, ease of learning, usefulness, and satisfaction, with an overall usability score of 83%. This suggests that the developed system is effective and well-received by users.
Optimasi Parameter Support Vector Regression (SVR) Menggunakan Algoritma Grey Wolf Optimizer (GWO) Yulia Candra Dewi; Joko Purwadi
Jurnal Ilmiah Matematika Vol. 10 No. 1 (2023)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jim.v10i1.30867

Abstract

Prediksi harga bawang merah merupakan hal penting bagi petani dan pemerintah untuk mengurangi risiko ekonomi dan membuat keputusan yang lebih baik. Penelitian ini bertujuan untuk mengembangkan model prediksi harga bawang merah di Indonesia menggunakan Support Vector Regression (SVR) yang dioptimalkan dengan algoritma Grey Wolf Optimizer (GWO). SVR adalah teknik pembelajaran mesin yang efektif untuk regresi, tetapi mempunyai kesulitan dalam menetapkan parameter optimalnya. Untuk itu, algoritma GWO, yang terinspirasi dari strategi berburu serigala, digunakan untuk mengoptimalkan parameter SVR. Dalam penelitian ini, data harga bawang merah sejak tanggal 1 Januari 2022 sampai 31 Desember 2023 yang diperoleh dari website resmi Pusat Informasi Harga Pangan Strategis Nasional (PIHPS) dikumpulkan dan dianalisis. Hasil penelitian menunjukkan bahwa tingkat eror yang diukur dengan RMSE (Root Mean Square Error) untuk model GWO-SVR diperoleh sebesar 0.062561 sedangkan model SVR sebesar 0.078579. Dapat dilihat bahwa terjadi penurunan nilai RMSE, sehingga dapat dikatakan bahwa algoritma optimasi GWO dapat meningkatkan kinerja dari model SVR.
Implementasi Metode SVM-PSO Dengan Fitur Selection Variance Threshold Pada Klasifikasi Penyakit Diabetes Mellitus Pratiwi Kistiya Ningrum; Joko Purwadi
Jurnal Ilmiah Matematika Vol. 10 No. 2 (2023)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jim.v10i2.30877

Abstract

Pada penelitian ini membahas tentang kasus klasifikasi pada data penyakit diabetes. Metode yang digunakan dalam penelitian ini adalah metode Support Vector Machine yang dioptimalkan dengan algoritma Particle Swarm Optimization guna memperoleh parameter terbaik dengan kombinasi seleksi fitur menggunakan Variance Threshold. Penelitian ini bertujuan untuk mengetahui cara kerja dan hasil akurasi dari metode Support Vector Machine dengan optimasi Particle Swarm Optimization menggunakan seleksi fitur Variance Threshold. Hasil penelitian menggunakan kombinasi metode tersebut menunjukkan hasil akurasi sebesar 80%. Hasil akurasi tersebut lebih tinggi jika dibandingkan dengan metode Support Vector Machine tunggal tanpa optimasi dan seleksi fitur dengan akurasi sebesar 76%. Meningkatkan akurasi sebesar 4% dari 76% menjadi 80%.
ANALISIS PENGENDALIAN KUALITAS PRODUKSI BERAS DENGAN METODE STATISTICAL PROCESS CONTROL (SPC) Luthfi Alleyda Fadhlullah; Joko Purwadi
Jurnal Ilmiah Matematika Vol. 11 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jim.v11i2.30893

Abstract

Perkembangan industri meningkat dikarenakan kebutuhan manusia yang beranekaragam seperti bahan pangan, papan, sandang, dan kendaraan. Perkembangan ini mendorong perusahaan yang bergeras dibidang industrialisasi untuk terus menjaga bahkan meningkatkan kualitas produk yang mereka hasilkan untuk menjaga kepercayaan pelanggan. UD. Penggilingan X merupakan bidang usaha yang bergerak dibidang industri pangan yang memproduksi Beras. Beras merupakan salah satu produk makanan pokok paling penting di dunia, termasuk di Indonesia. Pada penggilingan diperlukan penjagaan kualitas agar nantinya beras yang dihasilkan akan selalu terjaga bahkan meningkat setiap harinya. Kualitas ini dapat dijaga dengan ilmu matematis yaitu pengendalian kualitas yakni menggunakan tujuh alat Statistical Process Control (SPC).
Perancangan Website TMLESS Studio dengan Metode Design Thinking Yohanes Tennary Rinto Pradhana; Joko Purwadi; Raden Gunawan Santosa
Jurnal Terapan Teknologi Informasi Vol 9 No 2 (2025): Jurnal Terapan Teknologi Informasi
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21460/jutei.2025.92.378

Abstract

TMLESS Studio is an entertainment company based in Yogyakarta, Indonesia, which is engaged in content creation ranging from films and music videos to series and documentation. The documentation service offerings provided by TMLESS Studio are still carried out by introducing themselves directly to prospective customers or with the help of old customers who recommend their services to prospective customers. TMLESS Studio has tried to use social media as a marketing medium, but this is still considered to have no impact on service sales. The solution that will be carried out to help solve this problem is to design a website to display complete information on TMLESS Studio's work and documentation service offerings in one area. The TMLESS Studio website will be designed using the Design Thinking method which includes 5 stages, namely empathize, define, ideate, prototype, and test. At the test stage, testing will be carried out using the Single Ease Question (SEQ) using the help of Google Sites and Google Form to find out whether the tested website can overcome the initial problem. The results of the SEQ respondent data average test show that the website being tested is in the very easy category (average = 6.19). The results of the average test of Tasks 5, 6, 7, and 8 regarding information on works and services offered by TMLESS Studio are in the very easy category. The results of this test show that the application of the stages of the Design Thinking method and the implementation of SEQ in the design of the TMLESS Studio website being tested has succeeded in overcoming the problems and can be used as a permanent TMLESS Studio website.
Co-Authors Agnes Ona Bliti Puka Aldila Dinanti Aris Thobirin Dini Purwanti Dita Fadma Ristianti F. Yogiswara Adinugraha P Julan Hernadi Luthfi Alleyda Fadhlullah Pratiwi Kistiya Ningrum Raden Gunawan Santosa Rara Sandhy Winanda Reskika Hasmayuni Rosiana Aprilia Selviani, Novi Sugiyarto Sugiyarto Suryantoro, M. Danang Vinsensius Crispinus Lemba Yohanes Tennary Rinto Pradhana Yuan Lukito Yulia Candra Dewi