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All Journal Jurnal Ilmu Fisika SOROT: Jurnal Pengabdian Kepada Masyarakat
Kurniawan, Muhammad Aziz
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Astronomy Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Other

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Building Productive Students, Program Pelatihan Komunikasi Dasar bagi SMK Telesandi Bekasi Ramadhan, Yumna Zahran; Solehuddin, Muhammad; Muttaqin, Widang; Kurniawan, Muhammad Aziz; Yudiansyah; Yafie, Haddad Alwi; Azzahra , Nabil Marsya; Raditya, Ananda Alif; Fadani, Muhammad Raihan; Sausanindra, Sherly Nur
SOROT : Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 1 (2026): Januari
Publisher : Fakultas Teknik dan Ilmu Komputer (FASTIKOM) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/t1yyqs48

Abstract

Program pengabdian masyarakat ini bertujuan memperkuat keterampilan komunikasi interpersonal dan intrapersonal siswa SMK Telesandi Bekasi sebagai bekal menghadapi tuntutan akademik dan dunia kerja. Kegiatan dirancang untuk menjawab kebutuhan sekolah dalam membangun soft skills yang melengkapi kompetensi teknis siswa di era digital. Metode pelaksanaan meliputi workshop komunikasi, penerapan gamifikasi, serta pendampingan mentor yang melibatkan guru, alumni, dan praktisi. Tahapan program diawali dengan survei kebutuhan melalui kuesioner, wawancara, dan observasi untuk memetakan kemampuan awal siswa. Berdasarkan hasil tersebut, materi pelatihan disusun secara terstruktur mencakup refleksi diri, pengelolaan emosi, public speaking, diskusi kelompok, dan simulasi komunikasi dunia kerja. Implementasi gamifikasi seperti kuis interaktif, leaderboard, dan sistem badge digunakan untuk meningkatkan motivasi dan partisipasi siswa. Evaluasi dilakukan melalui penilaian keterampilan, observasi keaktifan, dan kuesioner kepuasan peserta. Hasilnya menunjukkan peningkatan kepercayaan diri, kemampuan menyampaikan gagasan. Secara keseluruhan, kegiatan ini memberikan dampak positif dan relevan bagi peningkatan mutu pembelajaran serta penguatan budaya komunikasi produktif di sekolah.
A Computational Physics–Based Machine Learning Modelling of Multiphase Flow Dynamics for Crude Oil Percentage Prediction Using Water Cut and Sediment Indicators Pebralia, Jesi; Amri, Iful; Amanda, Dwi Rahmah; Kurniawan, Muhammad Aziz
Jurnal Ilmu Fisika Vol 18 No 1 (2026): March 2026
Publisher : Jurusan Fisika FMIPA Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jif.18.1.80-92.2026

Abstract

Existing crude oil percentage prediction methods often rely on direct measurements and historical data, neglecting the coupled multiphase characteristics of oil–water–sediment systems, which limits predictive accuracy. This study develops a computational physics–based machine learning model integrating key multiphase production parameters, including water cut, basic sediment, and BS&W, using samples from PT. Pertamina Puspa Field Jambi. Data were split into two sets: one for model development and one for validation to prevent overfitting. Linear Regression, Support Vector Machine (SVM), and Random Forest algorithms were applied, with Linear Regression achieving the best performance. For the test dataset, the model yielded a Mean Absolute Error of 0.022168, a Mean Squared Error of 0.001227, and an accuracy of 0.99877, demonstrating precise capture of multiphase interactions. The proposed computational physics–based modelling framework provided improved predictive reliability and consistency. Correlation analyses indicated a coefficient of determination (R²) of 0.99 and a perfect negative correlation (r = −1) between BS&W and oil content, showing that higher BS&W corresponds to lower oil percentage. This framework offers improved predictive reliability and consistency for crude oil quality assessment.
Co-Authors Amanda, Dwi Rahmah Azzahra , Nabil Marsya Fadani, Muhammad Raihan Haddad Alwi Yafie Iful Amri Jesi Pebralia M. Solehuddin Muttaqin, Widang Raditya, Ananda Alif Ramadhan, Yumna Zahran Sausanindra, Sherly Nur Yudiansyah