Selamat kepada Ibu Afiahayati yang bergabung dalam tim NGS untuk Cancer Analysis. Tim telah mempublikasikan paper berjudul “Transcriptome Profile of Next-Generation Sequencing Data Relate to Proliferation Aberration of Nasopharyngeal Carcinoma Patients in Indonesia (Scopus Q2)

Abstract
Objective: Nasopharyngeal carcinoma (NPC) is the most common cancer arising from epithelial cells of the nasopharynx in  Indonesia. This study aims to determine the differential level of gene expression in NPC patients when compared with normal individuals. Transcriptome profiling analysis was performed using RNA-Seq technology to determine the differential gene expression relate to proliferation aberration that occurs in NPC patients compared with normal individuals. So we get the transcriptomic profile of Indonesia NPC patients. Methods: In this study, we used 9 samples, 7 NPC samples and 2 normal samples as control.  Fresh tissue of tumor samples was collected from biopsy, and normal samples were collected brushing technique. The total RNA was isolated from fresh tissue samples and brushing samples using the Rneasy® RNA Extraction Mini Kit. The cDNA library was generated using TruSeq® RNA Library Preparation Kit V2, and its concentration was determined using qPCR. The library was sequenced using the Next-Generation Sequencing (NGS) Illumina Next Seq 550 platform. The raw sequence data quality was analyzed using FastQC and interpreted using HISAT2, HTSeq, edgeR, and PANTHER. Results: From the analysis, 25493 gene transcripts were expressed, with 1956 genes were significantly upregulated, 90 genes were significantly downregulated in NPC samples, and 23897 genes didn’t change the expression level significantly (p <0.05), 10 of which genes were associated with cell proliferation. These genes are involved in the regulation of cancer cell proliferation through several signaling pathways, which are the apoptosis signaling pathway, IGF signaling pathway, Notch signaling pathway, and P13K signaling pathway. Conclusion: There were significant differences in gene expression levels between NPC patients and normal individuals. Each gene that has changed the expression level plays a role in regulating various pathways that lead to cell proliferation aberration in NPC cases. read more

Selamat kepada Andika William (Alumni International Undergradute Program of Computer Science, UGM) dan Ibu Yunita Sari, Ph.D. yang telah mempublikasikan paper berjudul “CLICK-ID: A Novel Dataset for Indonesian Clickbait Headlines”. Paper dipublikasikan pada international journal Data in Brief (Scopus Q4)

Abstract
News analysis is a popular task in Natural Language Processing (NLP). In particular, the problem of clickbait in news analysis has gained attention in recent years [1, 2]. However, the majority of the tasks has been focused on English news, in which there is already a rich representative resource. For other languages, such as Indonesian, there is still a lack of resource for clickbait tasks. Therefore, we introduce the CLICK-ID dataset of Indonesian news headlines extracted from 12 Indonesian online news publishers. It is comprised of 15,000 annotated headlines with clickbait and non-clickbait labels. Using the CLICK-ID dataset, we then developed an Indonesian clickbait classification model achieving favourable performance. We believe that this corpus will be useful for replicable experiments in clickbait detection or other experiments in NLP areas. read more

Kamis, 27 Agustus 2020 Laboratorium Sistem Cerdas DIKE UGM menyelenggarakan kegiatan sharing alumni yang telah menempuh Studi lanjut di Luar Negeri yang dikemas dalam bentuk acara ‘Sharing Alumni Lab. Sistem Cerdas #2 : Overseas Study Experience ‘ secara Online melalui Streaming di Youtube.

Seminar ini disampaikan oleh 4 Narasumber dari Alumni Lab SC yang sudah mengambil Studi di Luar Negeri, yaitu Ibu Meisyarah Dwiastuti, S.Kom., M.Sc. (European Master in LCT at Universität des Saarlandes and Charles University in Prague), Bapak Jason Kurniawan, S.Kom (Master in Computer Science at Tokyo Institute of Technology, Japan (Ongoing)), Ibu Diyah Utami Kusumaning Putri, S.Kom., M.Sc., M.Cs. (Dual Degree Master in CS at UGM and National Central University, Taiwan), dan Bapak Dzikri Rahadian Fudholi, S.Kom., M.Comp. (Master of Computing, Artificial Intelligence at The Australian National University). read more

Laboratorium Riset Sistem Cerdas Departemen Ilmu Komputer dan Elektronika, Fakultas MIPA, Universitas Gadjah Mada collaborating with Himakom and OmahTI proudly present

Alumni Sharing #2 – Overseas Study Experience

Presenters
1. Meisyarah Dwiastuti, S.Kom., M.Sc. – European Master in LCT at Universität des Saarlandes and Charles University in Prague
2. Jason Kurniawan, S.Kom – Master in Computer Science at Tokyo Institute of Technology, Japan (Ongoing)
3. Diyah Utami Kusumaning Putri, S.Kom., M.Sc., M.Cs. – Dual Degree Master in CS at UGM and National Central University, Taiwan
4. Dzikri Rahadian Fudholi, S.Kom., M.Comp. – Master of Computing, Artificial Intelligence at The Australian National University read more

Selamat kepada Dyah Aruming Tyas (Mahasiswa PMDSU Ilmu Komputer), Prof. Sri Hartati, Ph.D, Bapak Agus Harjoko, Ph.D. dan Dr. dr. Tri Ratnaningsih yang telah mempublikasikan paper berjudul “Morphological, Texture, and Color Feature Analysis for Erythrocyte Classification in Thalassemia Cases”. Paper dipublikasikan pada international journal IEEEAccess (Scopus Q1, Impact Factor : 3,74)

Abstract:

Abnormal erythrocytes have diverse shapes. The appearance of specific erythrocyte shapes in a person’s blood can indicate certain diseases, including thalassemia. We used thalassemia peripheral blood smear images and applied a segmentation process to produce single erythrocyte sub-images. Each erythrocyte has a unique shape. The selection of appropriate features to represent erythrocytes is critical for classification accuracy. We used morphological features such as moment invariants, geometry parameters of the cell and central pallor, and distance angle signature (DAS) morphological features of the cell and central pallor. We combined morphological features with texture and color features to increase the accuracy of erythrocyte classification. In this study, the multi-layer perceptron is used to classify nine shapes of erythrocytes present in thalassemia cases. The experimental results of 7108 erythrocytes indicated an accuracy of 98.11% based on the combination of features. The experimental results also show that the combination of features we proposed produced higher classification accuracy than previous work, which yielded an accuracy of 93.77%. Keywords: Classification, distance angle signature, erythrocytes, morphological feature, thalassemia

Artikel lengkap dapat diakses melalui URL
https://ieeexplore.ieee.org/document/9046795

Jumat, 14 Agustus 2020 Laboratorium Sistem Cerdas DIKE UGM menyelenggarakan kegiatan sharing alumni yang bekerja di dunia industri yang dikemas dalam bentuk acara ‘Sharing Alumni Lab. Sistem Cerdas #1 : Working with Artificial Intelligence‘ secara Online melalui Streaming di Youtube.

Seminar ini disampaikan oleh 3 Narasumber dari Alumni Lab SC yang sudah bekerja di bidang AI, yaitu Bapak Sigit Dewanto, M.Cs. (Web Crawling Engineer di Scrapinghub), Ibu Fatina Putri Maulida, S.Kom. (Data Research Engineer Quipper, Ltd., Japan), dan Bapak Erwin Eko Wahyudi, M.Cs. (AI Engineer Bukalapak). read more

Laboratorium Riset Sistem Cerdas Departemen Ilmu Komputer dan Elektronika, Fakultas MIPA, Universitas Gadjah Mada collaborating with Himakom and OmahTI proudly present

Alumni Sharing #1 – Working with Artificial Intelligence
Presenters
1. Sigit Dewanto, M.Cs. – Web Crawling Engineer Scrapinghub
2. Fatina Putri Maulida, S.Kom – Data Research Engineer Quipper, Ltd., Japan
3. Erwin Eko Wahyudi, M.Cs. – AI Engineer Bukalapak

Schedule
📆 Friday, August 14th, 2020
🕐 1.30 PM
💻 Youtube (Live streaming link http://ugm.id/sharingSC1) read more

Kamis, 30 Juli 2020 Laboratorium Sistem Cerdas DIKE UGM menyelenggarakan kegiatan pengabdian masyarakat yang dikemas dalam bentuk acara ‘Lab. Sistem Cerdas Online Seminar #5: Evolutionary Computation for Train Dataset & Applications of Matrix Factorization for ML‘ secara Online melalui Streaming di Youtube.

Seminar ini disampaikan oleh 2 Narasumber dari Dosen Departemen Ilmu Komputer dan Elektronika, yaitu Ibu Aina Musdholofah, S.Kom., M.Kom., Ph.D., dan Ibu Diyah Utami K.P, S.Kom, M.Sc., M.Cs. Seminar dibuka dengan Sambutan dari Kepala Lab Sistem Cerdas Bu Afiahayati, S.Kom., M.Cs., Ph.D., dan Sambutan dari Sekretaris Departemen IKE, Bapak Dr. Azhari SN, M.T., dengan Moderator Ibu Yunita Sari S.Kom., M.Sc., Ph.D. read more

Laboratorium Riset Sistem Cerdas Departemen Ilmu Komputer dan Elektronika, Fakultas MIPA, Universitas Gadjah Mada proudly presents

Online Seminar Series #5

Presenters
1. Aina Musdholifah, S.Kom.,M.Kom.,Ph.D.- Evolutionary Computation and Its Application
2. Diyah Utami K.P., S.Kom., M.Sc., M.Cs.- Application of Matrix Factorizations

Moderator
Yunita Sari, S.Kom., M.Sc.,Ph.D.

Schedule
🗓️Kamis, 30 Juli 2020
🕐13.30 WIB
💻 Youtube (Live Streaming pada http://ugm.id/youtubeSC5)

FREE E-CERTIFICATE!
Registration
http://ugm.id/webinarSC5 read more