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Alfarisi, Cory Dian
Chemical Engineering Department, Universitas Riau, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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PENINGKATAN PENGETAHUAN MANAJEMEN KEUANGAN DAN MOTIVASI BISNIS UNTUK IBU RUMAH TANGGA DI DESA KUALU KECAMATAN TAMBANG KABUPATEN KAMPAR Nurfatihayati Nurfatihayati; Anisa Mutamima; Panca Setia Utama; Yelmida Azis; Cory Dian Alfarisi
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 6, No 3 (2023): MARTABE : JURNAL PENGABDIAN MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v6i3.889-896

Abstract

Pandemi COVID-19 menyisakan ketidakstabilan ekonomi pada masyarakat. Harga bahan kebutuhan pokok yang masih tinggi, membuat para ibu rumah tangga harus berpikir keras untuk mengelola keuangan keluarga. Hal ini dialami oleh beberapa ibu rumah tangga di lingkungan Perumahan Mutiara Ayu 8 Desa Kualu Kecamatan Tambang Kabupaten Kampar. Kegiatan ini dilakukan untuk meningkatkan pengetahuan para ibu rumah tangga dalam manajemen keuangan keluarga dan memberikan motivasi bisnis untuk menambah pendapatan keluarga. Metode yang dilakukan adalah observasi lapangan, melaksanakan penyuluhan tentang manajemen keuangan dan motivasi bisnis, dan evaluasi hasil kegiatan terhadap 20 orang ibu rumah tangga. Manajemen keuangan keluarga yang efektif dapat dilakukan dengan cara membedakan kebutuhan dengan keinginan, menyusun daftar pengeluaran prioritas per bulan, alokasikan dana untuk tabungan dan dana darurat, dan minimalisir hutang. Untuk menambah pendapatan keluarga, ibu rumah tangga dapat melakukan bisnis sendiri. Hal-hal yang perlu dipersiapkan untuk memulai bisnis adalah adanya dukungan keluarga, sesuaikan dengan kemampuan, dapat memisahkan antara keluarga dan bisnis, menyusun target, dan perluas jaringan. Hasil kegiatan ini menunjukkan adanya peningkatan pengetahuan tentang manajemen keuangan dan bisnis pada para peserta.
Teknologi Modifikasi Fisik Heat Moisture Treatment (HMT) pada Tepung Beras dan Tepung Sorgum: Kajian Sistematis Parameter Proses, Transformasi Struktur Granula Pati dan Prospek Skalabilitas Industri Puji Hastuti, Ririn; Alel, Ariya Eka; Alfarisi, Cory Dian; Legawati, Lisa; Aziz, Yelmida
SURYA TEKNIKA Vol 13 No 1 (2026): JURNAL SURYA TEKNIKA
Publisher : Fakultas Teknik UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jst.v13i1.11604

Abstract

Heat Moisture Treatment (HMT) is a clean-label, residue-free physical starch modification technique that serves as a strategic solution for food diversification, aiming to reduce national reliance on imported wheat, which reached USD 2.2 billion in 2022. This systematic review of 45 selected scientific publications, out of 65 initially screened articles, evaluates the impact of HMT on rice and sorghum flour characteristics. Synthesized results indicate that HMT consistently increases gelatinization temperature (To up by 3 - 8°C), reduces peak viscosity (15 - 30%), and boosts resistant starch content from 3 - 5% to 8 - 15%. In sorghum flour, the interaction between starch and non-starch components, particularly kafirin proteins, significantly modifies the HMT response compared to pure sorghum starch. This study highlights critical research gaps, specifically regarding the need for optimal HMT parameters tailored to Indonesian local varieties and the necessity of comprehensive techno-economic analysis to facilitate industrial-scale implementation.
Machine Learning-Based Prediction of Sustainable Aviation Fuel Yield using Literature-Derived Hydroprocessing Data Eka Alel, Ariya; Hastuti, Ririn Puji; Suhendri, Suhendri; Alfarisi, Cory Dian
SURYA TEKNIKA Vol 13 No 1 (2026): JURNAL SURYA TEKNIKA
Publisher : Fakultas Teknik UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jst.v13i1.11609

Abstract

The increasing demand for sustainable aviation fuel (SAF) has encouraged the development of efficient predictive approaches for optimizing jet fuel production from renewable feedstocks. Conventional experimental optimization methods are often time-consuming and expensive because hydroprocessing performance is strongly influenced by feedstock characteristics, catalyst composition, and operating conditions. In this study, machine learning (ML) techniques were applied to predict jet fuel yield using a dataset compiled from approximately 50 published scientific articles. The dataset consisted of 101 experimental observations involving different feedstock groups, catalyst metal groups, catalyst supports, catalyst loading, free fatty acid (FFA) content, temperature, pressure, and weight hourly space velocity (WHSV). The ML workflow was developed using Orange Data Mining software and included data preprocessing, feature selection, imputation, model training, and performance evaluation. Four regression algorithms, namely Random Forest, Linear Regression, Neural Network, and Gradient Boosting, were evaluated using 10-fold cross-validation. The Gradient Boosting model achieved the best predictive performance with an RMSE of 7.172, MAE of 5.314, MAPE of 10.026%, and R2 value of 0.286 during cross-validation. Feature ranking analysis indicated that catalyst support type, feedstock group, catalyst metal group, and FFA content were among the most influential variables affecting jet fuel yield.
Co-Authors Adam Rafif Aldori Ahmad Dedi Fadillah Ahmad Fadli Ahmad Fadli Ahmad Fadli Aldo Seveno Mahendra Alltop Amri Ya Habib Annisa Aprilya Putri Aziz, Yelmida Barus, Surya Danta Alberto Chairul Chairul Delef, Fahrul Fajar Desi Heltina Detria Khaerun Nisa Dian Novita Rahmawaty Drastinawati Drastinawati Drastinawati Drastinawati Drastinawati Drastinawati, Drastinawati Eka Alel, Ariya Elvi Yenie Hastuti, Ririn Puji Ida Zahrina Idral Amri Khairat, Khairat Komalasari Komalasari Lisa Legawati Muhammad Ichwan Pradana Multi Handriyani Mutamima, Anisa Nurfatihayati Padil Padil Puji Hastuti, Ririn Purnama, Indra Putra, Eden Putri, Desi Erika Rozanna Sri Irianty Silvia Reni Yenti Silvia Reni Yenti Silvia Reni Yenti Suhendri Suhendri Suhendri Suhendri Sunarno Sunarno Sunarno Utama, Panca Setia Wisrayetti Wisrayetti Wisrayetti Wisrayetti Yelmida Azis Yulia Fitri Yusnimar Sahan