Article Per Year (5 Year)
p-Index From 2020 - 2025
0.562
P-Index
This Author published in this journals
All Journal Jurnal Sistem Cerdas Journal of Innovative Food Technology and Agricultural Product
Mahadany, Sunu Aditya
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Design of Personalization Exam Classification Model Based on Imbalanced Class Sri Anita; Rachmat, Arif; Mahadany, Sunu Aditya
Jurnal Sistem Cerdas Vol. 7 No. 1 (2024)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v7i1.386

Abstract

Currently, personalized learning has become a necessity in the learning process. Research and implementation of personalization in the planning phases and implementation phases of learning have been extensively studied. However, that research has not yet reached the application stage in the learning assessment phase. Providing homogeneous examination material to each student has not considered the characteristics of learners. Even though the achievements from the assessment phase will provide a measure of the quality of the learning process as a whole. This research has analyzed the individual characteristics model, which is derived as a benchmark for identification of the information and characteristics of the test material, which is then formulated into a classification model based on supervised learning. This study identified text dataset questions and labeled unbalanced multi-classes. This presents a challenge to carry out experiments to find the most optimal data training strategy, the results provide optimal strategy combination results Logic: ENS, Verbal: ENS, Visual: CW+RES+ENS, Natural: CW+RES+ENS. Accuracy measurement results Logic (SVM): 0.85, Verbal (LR) 0.87, Visual (LR) : 0.93, Natural (NN) 0.93.
Desain klasifikasi Cherri Kopi Menggunakan Metode k-Nearest Neighbor Anita, sri; Mahadany, Sunu Aditya; Army, Widya Lelisa
Journal of Innovative Food Technology and Agricultural Product Volume 2, No. 2, Desember 2024
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jitap.v2i2.7410

Abstract

Perkembangan teknologi informasi saat ini sudah mempengaruhi disemua sektor industri, salah satu adalah pertanian. Dalam penelitian ini akan disajikan rujukan desain dalam melakukan penyortiran cherri kopi menggunakan metode artificial intelegence (AI) yaitu metode k-Nearest Neighbor. Hasil percobaan menunjukan tingkat keberhasilan dengan hasil yang cukup memuaskan yaitu 71.12%. Penghematan waktu yang dapat terukur. kata kunci: Klasifikasi cherri kopi, AI teknologi pangan, K-nearest Neighbor
Desain klasifikasi Cherri Kopi Menggunakan Metode k-Nearest Neighbor Anita, sri; Mahadany, Sunu Aditya; Army, Widya Lelisa
Journal of Innovative Food Technology and Agricultural Product Vol 2 No 2 (2024) Desember : Journal of Innovative Food Technology and Agriculture Product
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jitap.v2i2.7410

Abstract

Perkembangan teknologi informasi saat ini sudah mempengaruhi disemua sektor industri, salah satu adalah pertanian. Dalam penelitian ini akan disajikan rujukan desain dalam melakukan penyortiran cherri kopi menggunakan metode artificial intelegence (AI) yaitu metode k-Nearest Neighbor. Hasil percobaan menunjukan tingkat keberhasilan dengan hasil yang cukup memuaskan yaitu 71.12%. Penghematan waktu yang dapat terukur. kata kunci: Klasifikasi cherri kopi, AI teknologi pangan, K-nearest Neighbor
Co-Authors Arif Rachmat, Arif Army, Widya Lelisa Sri Anita