2 citations · 4 across the 4 of their papers we have counts for
6 papers
Cost-Sensitive Machine Learning Classification for Mass Tuberculosis Verbal Screening
Ali Akbar Septiandri, Aditiawarman, Roy Tjiong +2
Score-based algorithms for tuberculosis (TB) verbal screening perform poorly, causing misclassification that leads to missed cases and unnecessary costly laboratory tests for false…
Human Blastocyst Classification after In Vitro Fertilization Using Deep Learning
Ali Akbar Septiandri, Ade Jamal, Pritta Ameilia Iffanolida +2
Embryo quality assessment after in vitro fertilization (IVF) is primarily done visually by embryologists. Variability among assessors, however, remains one of the main causes of th…
UKARA 1.0 Challenge Track 1: Automatic Short-Answer Scoring in Bahasa Indonesia
Ali Akbar Septiandri, Yosef Ardhito Winatmoko
We describe our third-place solution to the UKARA 1.0 challenge on automated essay scoring. The task consists of a binary classification problem on two datasets | answers from two…
Aspect and Opinion Term Extraction for Hotel Reviews using Transfer Learning and Auxiliary Labels
Yosef Ardhito Winatmoko, Ali Akbar Septiandri, Arie Pratama Sutiono
Aspect and opinion term extraction is a critical step in Aspect-Based Sentiment Analysis (ABSA). Our study focuses on evaluating transfer learning using pre-trained BERT (Devlin et…
Aspect and Opinion Terms Extraction Using Double Embeddings and Attention Mechanism for Indonesian Hotel Reviews
Jordhy Fernando, Masayu Leylia Khodra, Ali Akbar Septiandri
Aspect and opinion terms extraction from review texts is one of the key tasks in aspect-based sentiment analysis. In order to extract aspect and opinion terms for Indonesian hotel…
Predicting the Gender of Indonesian Names
Ali Akbar Septiandri
We investigated a way to predict the gender of a name using character-level Long-Short Term Memory (char-LSTM). We compared our method with some conventional machine learning metho…