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All Journal JUITA : Jurnal Informatika Jurnal Pengabdian UntukMu NegeRI RABIT: Jurnal Teknologi dan Sistem Informasi Univrab IT JOURNAL RESEARCH AND DEVELOPMENT INTEK: Informatika dan Teknologi Informasi Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Journal of Artificial Intelligence and Digital Business Journal of Software Engineering and Information System (SEIS)
Desti Mualfah
Program Studi Teknik Informatika, Universitas Muhamadiyah Riau
Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Penerapan Algoritma Electre Sebagai Pendukung Keputusan Kasus Pengangkatan Guru Tetap Fuad, Evans; Lysa Susticha; Desti Mualfah
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 1 No. 1 (2021)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1267.602 KB) | DOI: 10.37859/seis.v1i1.2857

Abstract

Assessment, evaluation and awarding can be carried out aimed at spurring the performance of teachers in the teaching and learning process so as to improve teacher achievement, the assessment is carried out to obtain honorary teachers who excel who will then be appointed as permanent teachers. The mechanism for appointing permanent teachers at the Muhammadiyah 3 Pekanbaru foundation, namely the Principal submits a list of names of teachers who will be recommended to be appointed as permanent teachers for thefoundation to the Head of PDM Education and Culture Pekanbaru City. The evaluation process for the appointment of permanent teachers at the foundation takes a very long time, then when checking and giving a value to the form provided with this process, itis feared that there will be a subjective assessment or the possibility of errors in writing numbers. The assessment criteria applied to the appointment of permanent teachers consist of years of service, PKP value, achievement, age. The author builds a decision support system using the Elimination and Choice Translation Reality method. In an effort to objectively determine to become a permanent teacher, this selection of permanent teachers will be very useful in motivating teachers to work well.
Implementation of Live Forensic Method on Fusion Hard Disk Drive (HDD) and Solid State Drive (SSD) RAID 0 Configuration TRIM Features Desti Mualfah; Rizdqi Akbar Ramadhan; Muhammad Arrafi Arrasyid
JUITA: Jurnal Informatika JUITA Vol. 12 No. 1, May 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i1.19508

Abstract

One of the solutions used for access speeds is to maximize non-volatile storage functions by a conventional Hard Disk Driver with Solid State Drive that has the TRIM architecture using the Redundant Array of Inexpensive Disks 0 configuration or the commonly known RAID 0. RAID 0 is a stripping technique that has the highest speed among other RAID configurations. However, this configuration has a disadvantage in that when there is damage to one of the storage disks all the data will be corrupted and lost. It's becoming one of the challenges in digital forensic investigation when it comes to computer crime. Furthermore, this research uses experimental practices using live forensic methods to perform analysis and examination against the merger of HDD and SSD configuration RAID 0 TRIM features. The expected is an overview of the characteristics of recovery capability to find out the authenticity integrity values of files that have been lost or permanently deleted on both TRIM SSD functions disable and enable. Furthermore, this research is expected to be a solution for the experimental and practical investigation of computer crime especially in Indonesia given the increasing development of technology that is directly compared with the rise in computer crime. 
PENGEMBANGAN SISTEM PEMBAYARAN NON TUNAI MEMANFAATKAN TEKNOLOGI NEAR FIELD COMMUNICATION (NFC) Harun Mukhtar; Efry Hady Nata; Desti Mualfah; Syahril Syahril; Rahmad Firdaus
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 7 No 2 (2022): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v7i2.2212

Abstract

The demands of rapid technology development test the need and necessity for implementation. Coercion of implementation seems to be happening in recent conditions, where the world is being hit by a virus that requires social distancing. Transaction processes that always interact with touch will be replaced by technology. Near-field Communication (NFC) which relies on magnetic technology has been designed on various objects as a means of connecting with financial data, making it easier for users to make transactions
Tinjauan Sistematis Peramalan Beban Listrik Menggunakan Deep Learning dan Hybrid Halim Prasetyo Rieno; Desti Mualfah
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 5 No. 2 (2026): Mei-Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v5i2.11178

Abstract

Peramalan beban listrik memiliki peran yang sangat penting dalam pengelolaan sistem tenaga modern karena hasil prediksi yang akurat berpengaruh langsung terhadap efisiensi operasi, keandalan sistem, perencanaan energi, pengalokasian sumber daya, serta stabilitas smart grid. Seiring meningkatnya kebutuhan listrik dan kompleksitas pola konsumsi energi, metode peramalan berbasis kecerdasan buatan, khususnya deep learning dan hybrid, semakin banyak dikembangkan untuk meningkatkan akurasi prediksi dibandingkan metode konvensional. Penelitian ini bertujuan untuk mengkaji perkembangan metode deep learning dan hybrid dalam peramalan beban listrik dengan fokus pada algoritma yang digunakan, variabel input, serta metrik evaluasi yang diterapkan. Metode penelitian menggunakan Systematic Literature Review (SLR) dengan mengacu pada kerangka PRISMA. Sebanyak 18 artikel ilmiah yang diterbitkan pada periode 2022–2026 dipilih melalui proses identifikasi, penyaringan, dan seleksi dari basis data Google Scholar, MDPI, Frontiers, dan arXiv. Hasil kajian menunjukkan bahwa beban historis, fitur waktu, dan variabel cuaca merupakan variabel input yang paling sering digunakan karena memiliki pengaruh signifikan terhadap pola konsumsi listrik. Dari sisi algoritma, penelitian terbaru menunjukkan pergeseran dari model deep learning tunggal menuju model Transformer dan pendekatan hybrid, seperti CNN-GRU, CNN-LSTM, serta BiLSTM-Transformer, yang terbukti lebih mampu menangkap karakteristik data deret waktu yang kompleks, nonlinier, dan dinamis. Sementara itu, metrik evaluasi yang paling banyak digunakan untuk mengukur performa model adalah Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), dan Mean Absolute Error (MAE). Temuan penelitian ini menunjukkan bahwa integrasi data multivariat dengan model deep learning hybrid berpotensi meningkatkan akurasi peramalan beban listrik serta menjadi arah pengembangan yang menjanjikan dalam mendukung implementasi sistem smart grid yang lebih efisien, adaptif, dan berkelanjutan.
Co-Authors Aminuyati Baidarus Danang Mulyadipa Suratno Diah Angraina Fitri Efry Hady Nata Eka Ramadhan Evans Fuad Febby Apri Wenando Gunawan, Rahmad Halim Prasetyo Rieno Harun Mukhtar Januar Al Amien Julian Silvia Hasanah Lysa Susticha Muhammad Arrafi Arrasyid Rahmad Firdaus Ramadhoni Reny Medikawati Taufik Rizdqi Akbar Ramadhan Setya Nanda Soni Syahril Syahril Unik, Mitra Yoze Rizki