Items where Author is "Setya Rintyarna, Bagus"

Trapsilo Rochim, Yachya and Setyawan, Herry and Setya Rintyarna, Bagus and Fitriana, Fitriana (2023) (SIMILARITY) PROTOTYPE OPTIMALISASIISUHU PADA AUTOCLAVEEBERBASIS OUTSEAL PROGRAMMABLE LOGIC CONTROL ( PLC ) DENGAN MENGGUNAKAN HUMAN MACHINE INTERFACE (HMI). Lembaga Penelitian dan Pengabdian Masyarakat STMIK Primakara.

Wahyu Laksana, Rico and Setya Rintyarna, Bagus and Aji, Brahma Nugroho (2023) (Similarity) Pemanfaatan Teknologi IoT pada Smart Farming Microgreen dan Akuisisi Data. Universitas Muhammadiyah Jember.

Setya Rintyarna, Bagus and Setyaningtyas, Rusdiana and DARYANTO, DARYANTO and Safitri Windiarti, Ika (2023) (Similarity+Korespondensi) Assessment of Technology Acceptance Model of Water Quality Monitoring Technology Application on Rural Areas of Jember Regency. The Romance Science Publication and Distribution.

Setya Rintyarna, Bagus (2019) (Peer Review) Evaluating The Performance of Sentence Level Features and Domain Sensitive Features of Product Reviews on Supervised Sentiment Analysis Task. Springer.

Setya Rintyarna, Bagus (2019) (Peer Review) Semantic Features for Optimizing Supervised Approach of Sentiment Analysis on Product Reviews. MDPI.

Setya Rintyarna, Bagus (2019) (Similarity) Evaluating The Performance of Sentence Level Features and Domain Sensitive Features of Product Reviews on Supervised Sentiment Analysis Task. Springer. Springer.

Setya Rintyarna, Bagus (2019) (Similarity) Semantic Features for Optimizing Supervised Approach of Sentiment Analysis on Product Reviews. MDPI.

Setya Rintyarna, Bagus (2018) (Similarity) -Automatic Ranking System of University Based on Technology Readiness Level Using LDA-Adaboost.MH. Universitas AMIKOM.

Setya Rintyarna, Bagus (2015) (Similarity) Seleksi Fitur Dua Tahap Menggunakan Information Gain dan Artificial Bee Colony untuk Kategorisasi Teks Berbasis Support Vector Machine. Program Studi Sistem Informasi UIN Surabaya.

Setya Rintyarna, Bagus (2013) (Similarity) Klasifikasi Penyakit Diabetes dengan Hidden Naive Bayes. Biro Afiliasi Fakultas Teknik UM Jember.