Article Per Year (5 Year)
p-Index From 2020 - 2025
0.817
P-Index
This Author published in this journals
All Journal Khizanah al-Hikmah : Jurnal Ilmu Perpustakaan, Informasi, dan Kearsipan Majalah Kedokteran BACA: Jurnal Dokumentasi dan Informasi
Sihombing, Andre
Unknown Affiliation
Library & Information Science Medicine & Pharmacology

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Spondilitis Tuberkulosis pada Pasien dengan Keganasan Tiroid: Laporan Kasus Syefi, Monica; Vande, Godishac A.; Sihombing, Andre; Lubis, Mohammad F.
Majalah Kedokteran UKI Vol. 39 No. 2 (2023): MEI - AGUSTUS
Publisher : Fakultas Kedokteran Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/mk.v39i2.5901

Abstract

Dilaporkan kasus spondilitis tuberkulosis dengan komplikasi. Pada anamnesis di dapatkan keluhan kesulitan berjalan sehingga pasien berjalan dengan posisi membungkuk, nyeri pada pinggang dan lutut kaki kiri, kedua kaki semakin mengecil dan terasa lemas. Selain itu pasien mengeluh napsu makan menurun, keringat dingin malam hari, demam hilang timbul, serta benjolan pada pinggang, punggung, dan punggung kaki kanan. Pada pemeriksaan fisik didapatkan gibbus, abses, dan kifosis. Range of motion spine pasien fleksi anterior terbatas, ekstensi terbatas, fleksi lateral terbatas, rotasi badan terbatas, dan pasien kehilangan kemampuan motorik secara parsial. Pemeriksaan MRI lumbal didapatkan spondilodisitis lumbal 2-3 dengan penekanan fragmen posterior pada kanalis spinalis yang menyebabkan stenosis disertai paravertebral abses. Pengobatan spondilitis yaitu obat anti-tuberkulosis dan pembedahan untuk mengatasi komplikasi. Kata kunci: Pott’s disease, spinal, gibbus, abses, keganasan tiroid A case of tuberculous spondylitis with complications was reported. Anamnesis found complaints of difficulty walking, so the patient walked in a bent position, pain in the waist and left knee, both legs getting smaller, and feeling weak. In addition, the patient complained of decreased appetite, cold sweats at night, intermittent fever, and lumps on the waist, back, and back of the right leg. A physical examination found gibbous, an abscess, and kyphosis. The patient's range of motion in the in the spine was limited by limited anterior flexion, limited extension, limited lateral flexion, and limited body rotation, and the patient lost partial motor skills. Lumbar MRI examination found lumbar spondylodiscitis 2-3 with posterior fragment pressure on the spinal canal, causing stenosis accompanied by paravertebral abscess. Treatment for spondylitis includes anti-tuberculosis drugs and surgery to overcome complications. Keywords: Pott’s disease, spinal, gibbous, abscess, thyroid malignancy
Interactive Visualization Dashboard for Exploring Scientific Publications in Indonesia Sihombing, Andre; Yaniasih; Indrawati, Ariani; Afandi, Sjaeful; Ningsih Maha, Rahmadani
Khizanah al-Hikmah : Jurnal Ilmu Perpustakaan, Informasi, dan Kearsipan Vol 11 No 2 (2023): December
Publisher : Program Studi Ilmu Perpustakaan UIN Alauddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/kah.v11i2a3

Abstract

Numerous bibliometric investigations have been carried out in Indonesia, primarily relying on publication data indexed exclusively in Scopus. This study aims to leverage scientific publication data from the Indonesian Scientific Journal Database (ISJD) by constructing an interactive visualization dashboard for the analysis of Indonesian scientific publications. This dashboard is expected to become an additional reference for researchers in the field of bibliometrics. The stages of making this dashboard consist of Identification of visualization needs referring to previous research; data feasibility check; data correction and update; data visualization; and evaluation to assess the correctness of the data and the resulting visualization. Evaluation results indicate that the dashboard's analysis system is functioning effectively, offering diverse analysis options. Nonetheless, the system has limitations related to data quality in ISJD, necessitating improvements in terms of completeness, appropriateness, and data updates. Future research will enhance the dashboard by incorporating citation analysis calculations to evaluate the performance of authors and journals.
ANALYZING THE IMPACT OF RESAMPLING METHOD FOR IMBALANCED DATA TEXT IN INDONESIAN SCIENTIFIC ARTICLES CATEGORIZATION Indrawati, Ariani; Subagyo, Hendro; Sihombing, Andre; Wagiyah, Wagiyah; Afandi, Sjaeful
BACA: Jurnal Dokumentasi dan Informasi Vol. 41 No. 2 (2020): BACA: Jurnal Dokumentasi dan Informasi (Desember)
Publisher : Direktorat Repositori, Multimedia, dan Penerbitan Ilmiah - Badan Riset dan Inovasi Nasional (BRIN Publishing)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.baca.v41i2.702

Abstract

The extremely skewed data in artificial intelligence, machine learning, and data mining cases are often given misleading results. It is caused because machine learning algorithms are designated to work best with balanced data. However, we often meet with imbalanced data in the real situation. To handling imbalanced data issues, the most popular technique is resampling the dataset to modify the number of instances in the majority and minority classes into a standard balanced data. Many resampling techniques, oversampling, undersampling, or combined both of them, have been proposed and continue until now. Resampling techniques may increase or decrease the classifier performance. Comparative research on resampling methods in structured data has been widely carried out, but studies that compare resampling methods with unstructured data are very rarely conducted. That raises many questions, one of which is whether this method is applied to unstructured data such as text that has large dimensions and very diverse characters. To understand how different resampling techniques will affect the learning of classifiers for imbalanced data text, we perform an experimental analysis using various resampling methods with several classification algorithms to classify articles at the Indonesian Scientific Journal Database (ISJD). From this experiment, it is known resampling techniques on imbalanced data text generally to improve the classifier performance but they are doesn’t give significant result because data text has very diverse and large dimensions.
Optimizing Multi-Layer Perceptron Performance in Sentiment Classification through Neural Network Feature Extraction Alam, Muhammad Fikri; Nuryaman, Aang; Khotimah, Purnomo Husnul; Parlina, Anne; Sihombing, Andre
BACA: Jurnal Dokumentasi dan Informasi Vol. 46 No. 1 (2025): BACA: Jurnal Dokumentasi dan Informasi (Juni)
Publisher : Direktorat Repositori, Multimedia, dan Penerbitan Ilmiah - Badan Riset dan Inovasi Nasional (BRIN Publishing)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/baca.2025.8240

Abstract

There are some problems with using the Multi-Layer Perceptron (MLP) model for complex tasks because it can be hard to understand hierarchical relationships and tends to overfit data with a lot of dimensions. This research proposes an enhanced MLP model for sentiment classification by integrating feature extraction layers from advanced neural networks, specifically the Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Bidirectional LSTM (Bi-LSTM). These layers aim to improve the model's representation capabilities by capturing more nuanced features. To evaluate the performance improvements of this augmented MLP model, metrics such as accuracy, precision, recall, F1-score, and the Area Under the Curve for Receiver Operating Characteristics (ROC-AUC) were employed. A key metric focus is the delta value, representing changes in the ROC-AUC, to assess the significance of these enhancements. The integration of CNN as a feature extraction layer yielded optimal ROC-AUC results, achieving values of 93.30% and 93.00%, which reflect an improvement of 0.51% and 4.46% over the baseline model. These findings indicate that adding feature extraction layers significantly enhances MLP performance in sentiment classification tasks. Future research may explore the potential of using alternative neural networks as feature extractors to continue advancing MLP capabilities in complex NLP applications.
Co-Authors Aang Nuryaman Alam, Muhammad Fikri Anne Parlina Hendro Subagyo Indrawati, Ariani Khotimah, Purnomo Husnul Lubis, Mohammad F. Ningsih Maha, Rahmadani Sjaeful Afandi Syefi, Monica Vande, Godishac A. Wagiyah Wagiyah Yaniasih