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All Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Pengabdian Masyarakat
Setianama, Mamur
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Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Public Health Other

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Implementation of Particle Swarm Optimization (PSO) to Improve Neural Network Performance in Univariate Time Series Prediction Tyas, Fitri Ayuning; Setianama, Mamur; Fadilatul Fajriyah, Rizqi; Ilham, Ahmad
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 6, No. 4, November 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i4.1330

Abstract

One of the oldest known predictive analytics techniques is time series prediction. The target in time series prediction is use historical data about a specific quantity to predicts value of the same quantity in the future. Multivariate time series (MTS) data has been widely used in time series prediction research because it is considered better than univariate time series (UTS) data. However, in reality MTS data sets contain various types of information which makes it difficult to extract information to predict the situation. Therefore, UTS data still has a chance to be developed because it is actually simpler than MTS data. UTS prediction treats forecasts as a single variable problem, whereas MTS may employ a large number of time-concurred series to make predictions. Neural Network (NN) model could be built to predict the target variable given the other (predictor) variables. In this study, we used Particle Swarm Optimization (PSO) algorithm to optimize performance of NN on a UTS dataset. Our proposed model is validated using x-validation and and use RMSE to measure its performance. The experimental results show that NN performance after optimization using PSO produces good results compared to classical NN performance. This is evidenced by the value of RMSE = 0.410 which is the smallest RMSE value produced. The smaller the RMSE value, the better the model performance. It can be concluded that the proposed method can improve NN performance on UTS data.
Peran Akademisi dalam Penjurian LKS Web Technologies melalui Kemitraan dengan MGMP di Kabupaten Brebes Fitri Ayuning Tyas; Setianama, Mamur; Faizin, Ahmad; Basir, Azhar
Jurnal Pengabdian Masyarakat - PIMAS Vol. 4 No. 3 (2025): Agustus
Publisher : LPPM Universitas Harapan Bangsa Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/pimas.v4i3.1900

Abstract

Lomba Kompetensi Siswa (LKS) merupakan ajang kompetensi yang bertujuan untuk mendapatkan siswa-siswi SMK terbaik dari seluruh Indonesia serta akan diikutsertakan pada kompetisi keahlian dan keterampilan tingkat internasional seperti Word Skill International Competition. LKS diawali seleksi di tingkat Kabupaten. SMK di Kabupaten Brebes merupakan SMK yang berada di bawah naungan Cabang Dinas Pendidikan Wilayah XI yang rutin berpartisipasi pada ajang LKS setiap tahunnya. Forum MGMP TKJ dan RPL sebagai panitia LKS Kabupaten Brebes membutuhkan dukungan kemitraan pihak eksternal baik akademisi maupun industri dalam melaksanakan ajang LKS seperti sarana prasarana yang sesuai dengan kebutuhan bidang lomba, soal-soal LKS dan proses penilaian hasil yang lebih objektif. Untuk mengatasi permasalahan tersebut tim PkM Universitas Muhammadiyah Brebes (UMBS) berkontribusi dengan memfasilitasi penyelenggaran LKS Kabupaten Brebes baik dalam bentuk sarana prasarana maupun sebagai dewan juri khususnya di bidang lomba web technologies. Penunjukan dewan juri disesuaikan dengan bidang keahlian dosen UMBS. Peran akademisi sebagai dewan juri diharapkan dapat menghasilkan soal LKS yang berkualitas sesuai perkembangan ilmu Information Technology khususnya bidang web technologies serta penilaian yang lebih objektif. Penetapan hasil terbaik akan diambil 3 juara, sedangkan untuk juara 1 dipilih sebagai perwakilan Kabupaten Brebes di ajang LKS tingkat Provinsi Jawa Tengah.
Co-Authors Ahmad Faizin, Ahmad Basir, Azhar Fadilatul Fajriyah, Rizqi Fitri Ayuning Tyas Fitri Ayuning Tyas Ilham, Ahmad