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All Journal HAYATI Journal of Biosciences Jurnal Teknologi Industri Pertanian Indonesian Journal of Biotechnology Journal of Agromedicine and Medical Sciences Journal of Tropical Biodiversity and Biotechnology Manajemen Pendidikan BERITA BIOLOGI JURNAL BIOLOGI INDONESIA Jurnal Teknologi Laboratorium Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Chimica et Natura Acta Indonesian Journal of Chemistry Jurnal Sinergitas PkM & CSR FaST : Jurnal Sains dan Teknologi Walisongo Journal of Chemistry Menara Perkebunan Jurnal Teknik Informatika (JUTIF) Bioinformatics and Biomedical Research Journal Cermin Dunia Kedokteran Indonesian Journal of Life Sciences Makara Journal of Science Makara Journal of Technology Biosaintifika: Journal of Biology & Biology Education Jurnal Bioteknologi & Biosains Indonesia (JBBI) Cermin Dunia Kedokteran Kesmas: Jurnal Kesehatan Masyarakat Nasional (National Public Health Journal) Jurnal Bioteknologi & Biosains Indonesia Berita Biologi
Arli Aditya Parikesit
Department Of Bioinformatics, School Of Life Sciences, Indonesia International Institute For Life Sciences (i3l), Jakarta, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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PELATIHAN BERSERI TEKNOLOGI INFORMASI DAN KOMUNIKASI DI SEKOLAH DASAR MEKARSARI JAKARTA [A WORKSHOP SERIES OF INFORMATION COMMUNICATION AND TECHNOLOGY AT MEKARSARI ELEMENTARY SCHOOL JAKARTA] David Agustriawan; Arli Aditya Parikesit; Rizky Nurdiansyah
Jurnal Sinergitas PKM & CSR Vol 4, No 1 (2019): October
Publisher : Universitas Pelita Harapan

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Abstract

Industry 4.0 era needs to introduce current information communication and technology (ICT) to the society starting from the elementary school. However, Mekarsari Elementary school does not have the facility nor curriculum to prepare the students to face the era. This corporate social responsibility (CSR) aimed to introduce the kids with the current development of hardware and software. The participants for the series of the workshop are the 15 4th and 5th grade students and two teachers from Mekarsari Elementary school. The intervention was devised by providing user-friendly teaching-learning materials with hands-on activities related to the current development of ICT. The type of study is the “direct philanthropic giving” because it aims at providing knowledge for free. As the result, the students are familiar with: the type of computer’s hardware and software; python programming; budgeting for their daily allowance using Microsoft Excel; and creating a short story and presentation in Microsoft Word and PowerPoint. Based on the survey, the students could comprehend and enthusiastic to complete the hands-on activities. This CSR suggests that each elementary school should have a curriculum and computer laboratory to prepare the youth to compete in industry 4.0 era.
Pemanfaatan bioinformatika dalam bidang pertanian dan kesehatan (The utilization of bioinformatics in the field of agriculture and health) Arli Aditya PARIKESIT; Dito ANUROGO; Riza A PUTRANTO
E-Journal Menara Perkebunan Vol 85, No 2 (2017): Oktober 2017
Publisher : INDONESIAN RESEARCH INSTITUTE FOR BIOTECHNOLOGY AND BIOINDUSTRY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22302/iribb.jur.mp.v85i2.237

Abstract

Bioinformatics can be used to manage the data storage resulted from in silico molecular biology experiments. Off-network (offline) applications require large computing resources, in which researchers in the bioinformatics field of agriculture and health sectors do not necessarily possess. This review paper addressed examples of affordable and applicable in silico analytical cases in both mentioned sectors. Genome sequence analysis and in silico drug design using (1) a computational method, pharmacokinetic parameter prediction, (2) Computer Aided Design and Drafting (CADD) technology, (3) potential protein action prediction, (4) OMICs application in stem cell biology, and (5) lncRNAs based database computing internet sites is one of examples. In agriculture, bioinformatics-based research has been used in (1) the development of molecular markers; (2) the design of primer for differential gene expression analysis; (3) the development of genetic maps; and (4) gene expression analysis. Further application of bioinformatics also targets the design of applicative products for pest control and the protection of plant varieties in the farm. Through this example, novice researchers in the bioinformatics field of agriculture and health sectors can conduct sophisticated research using standard computer tools, internet networks, and sufficient knowledge about bioinformatics. On the other hand, multidisciplinary collaboration between these scientists can be carried out through social networking. The synergy can be directed to improve computing capabilities and data analysis via procurement of computing resources and use of public information clusters. [Key words: genome sequences, in silico drug design, online, bioinformatics, health, agriculture.] AbstrakBioinformatika dapat digunakan dalam manajemen informasi di bidang penyimpanan data in silico dari eksperimen biologi molekuler. Aplikasi luar jaringan (luring) memerlukan sumber daya komputasi yang besar, yang belum tentu dimiliki oleh para peneliti dalam bidang bioinformatika kesehatan dan pertanian. Kajian ilmiah ini membahas contoh kasus analisis in silico yang terjangkau dan aplikatif dalam bidang kesehatan dan pertanian. Contoh kasus tersebut adalah analisis sekuen genom dan desain obat in silico, menggunakan pendekatan metode komputasional, prediksi parameter farmakokinetik, teknologi Computer Aided Design and Drafting (CADD), prediksi potensial aksi protein, aplikasi OMICs pada biologi sel punca, hingga komputasi basis data lncRNAs berbasis situs internet. Pada bidang pertanian, penelitian berbasis bioinformatika telah digunakan dalam (1) pengembangan penanda molekuler; (2) desain primer untuk analisis ekspresi gen diferensial; (3) pengembangan peta genetik; dan (4) analisis ekspresi gen. Pemanfaatan bio-informatika dalam ilmu terapan dibidang pertanian juga menyasar desain produk aplikatif untuk pengendalian hama dan perlindungan varietas tanaman. Melalui contoh tersebut, peneliti pemula dibidang bioinformatika kesehatan dan pertanian dapat melakukan penelitian canggih hanya dengan alat komputer standar, jaringan internet, dan pengetahuan mencukupi tentang bioinformatika. Disisi lain, sinergi dan kolaborasi antar peneliti multi-displiner dapat dilakukan melalui penggunaan jejaring sosial. Sinergi tersebut dapat diarahkan untuk meningkatkan kemampuan komputasi dan analisis data melalui pengadaan sumber daya komputasi dan penggunaan klaster informatika publik.[Kata kunci: sekuen genom, desain obat in silico, daring, bioinformatika, kesehatan, pertanian]
Kajian Prediksi 3-Dimensi Biomarker Kanker Payudara Dari Jalur Ekspresi LincRNA-ROR/MIR-145/ARF6 [3D Prediction of Breast Cancer Biomarker from The Expression Pathway of LincRNA-ROR/MIR-145/ARF6] Arli Aditya Parikesit; Dito Anurogo
FaST - Jurnal Sains dan Teknologi (Journal of Science and Technology) Vol 2, No 1 (2018): May
Publisher : Universitas Pelita Harapan

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Abstract

According to WHO, breast cancer is one of the main causes of mortality in women. To overcome this malady, molecular biomedical research is carried out intensively. Anomalies in the lincRNA-RoR/miR-145/ARF6 expression pathway were found to play a very important role in breast cancer, especially in the type of Triple-Negative Breast Cancer (TNBC), which is the most dangerous variant of the deadly disease. Bioinformatics research has found the existence of non-coding RNA (ncRNA) in these expression pathways, whose interactions are worth studying with 3-dimensional prediction methods. The 3-D prediction method for biomolecules has been widely developed and has been successfully applied to DNA and protein. However, for the structure of RNA, it has just been developed, due to its low stability and very high dynamics on the biomolecule. Our aim is to apply the latest computational method for predicting the 3-dimensional structure of ncRNA, which can be applied as key information in biomedical application research. Extrapolation of kinetics and thermodynamic indicators of ncRNA ultimately yields the siRNA Linc-ROR 3-Dimensional structure and siRNA mRNA-ARF6, each having 13 and 8 hydrogen bonds. The existence of these hydrogen bonds is very important in maintaining the stability of the compounds and shows its efficacy as drug candidates. It is expected that preliminary information from the predicted 3-dimensional structure of ncRNA is useful for optimization of laboratory experiments in the field of crystallographic biomolecules.
3D And 2D RNA Structure Prediction Of The BRCA2 Gene And Its Silencing RNA In The Breast Cancer Ryan Wijaya; Arli Aditya Parikesit; Rizky Nurdiansyah
Walisongo Journal of Chemistry Vol 3, No 1 (2020): Walisongo Journal of Chemistry
Publisher : Department of Chemistry Faculty of Science and Technology Walisongo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/wjc.v3i1.6019

Abstract

Breast cancer is one of the most threatening diseases for women. It is found that BRCA2 gene plays a significant role in breast cancer, provided that mutations occurred. The objective of this study is to determine whether the bioinformatics approach could provide the gene networking, molecular simulation, and computational metabolomics information to shed the relation between BRCA2 gene mutation with breast cancer progression. The methods are utilizing molecular simulation tools to comprehend the biochemical interaction of BRCA2 gene with other oncogenic genes. Lastly, the molecular docking tool is devised to provide the molecular interactions information. It could be implied that the Computer-Aided Drug Design (CADD)-based in silico transcriptomics tools could provide the fine-grained information on the exact role of BRCA2 gene in the progression of breast cancer. The clinical impact of this study could only be measured after the wet laboratory experiment is conducted to validate the computational approach results
Use of Artificial Intelligence in the Diagnostics of Autism Spectrum Disorder Gabriele Mustika Kresnia; Arli Aditya Parikesit
Cermin Dunia Kedokteran Vol 49, No 6 (2022): Nutrisi
Publisher : PT. Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v49i6.1886

Abstract

Autism Spectrum Disorder (ASD) is a neurologic development disorder; it is listed in the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-V). Early diagnosis is critical in improving the life quality of individuals affected by ASD. Several studies show that Artificial Intelligence can be used in the diagnosis of ASD through biological means such as observing patient EEG data and surveying their genome. Articles were searched in the PUBMED database, ScienceDirect and Springer Link between 2019 - 2020. Four papers were selected for review. The papers were able to devise models that can accurately predict ASD in affected individuals, though some are based on old data and/or require testing on larger datasets to determine accuracy. As ASD diagnosis usually cannot be achieved before the individual shows symptoms, AI has the potential to improve ASD diagnosis in affected individuals. Further study to confirm the models and test on larger, more recent datasets would be required to develop more accurate models and achieve even better results.Autism Spectrum Disorder (ASD) merupakan salah satu gangguan perkembangan saraf yang tercantum pada Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-V). Diagnosis dini sangat penting untuk meningkatkan kualitas hidup individu ASD. Beberapa penelitian menunjukkan bahwa Kecerdasan Buatan dapat digunakan untuk diagnosis ASD melalui metode berbasis biologis seperti mengamati data EEG pasien dan mensurvei genomnya. Review ini berbasis pencarian data antara 2019 – 2020 di database PUBMED, ScienceDirect dan Springer Link. Empat makalah kunci dipilih untuk ditinjau. Makalah-makalah tersebut mampu merancang model yang dapat memprediksi ASD secara akurat, meskipun beberapa aspek implementasinya didasarkan pada data usang dan/atau memerlukan pengujian pada kumpulan data yang lebih besar untuk menentukan akurasi. Mengingat diagnosis ASD biasanya tidak dapat dilakukan sebelum individu menunjukkan gejala sekunder, kecerdasan buatan berpotensi meningkatkan keandalan diagnosis ASD. Masih diperlukan studi lanjutan untuk mengkonfirmasi model dan pengujian pada kumpulan data yang lebih besar dan lebih baru untuk mengembangkan model yang memiliki presisi lebih baik dan hasil lebih akurat.
The Role of Bioinformatics in Personalized Medicine: Your Future Medical Treatment Margareta Deidre Valeska; Gabriella Patricia Adisurja; Stefanus Bernard; Renadya Maulani Wijaya; Muhammad Aldino Hafidzhah; Arli Aditya Parikesit
Cermin Dunia Kedokteran Vol 46, No 12 (2019): Kardiovaskular
Publisher : PT. Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v46i12.402

Abstract

Bioinformatika berperan sangat penting dalam personalized medicine. Dua metode penting dalam kajian ini adalah randomized algorithm dan computer assisted drug design (CADD). Kajian ini membahas aplikasi, kekurangan, dan masa depan kedua metode tersebut. Saran-saran untuk meningkatkan efek riset bioinformatika dalam kajian personalized medicine juga akan ditelaah.Bioinformatics is beneficial in personalized medicine. Two methods stand out, the randomized algorithm and computer assisted drug design (CADD). This article will discuss the application, pitfalls, and eventual future of those two methods. Suggestion to improve the clarity of the bioinformatics research in the field of personalized medicine will also be reviewed.
Kontribusi Aplikasi Medis dari Ilmu Bioinformatika Berdasarkan Perkembangan Pembelajaran Mesin (Machine Learning) Terbaru Arli Aditya Parikesit
Cermin Dunia Kedokteran Vol 45, No 9 (2018): Infeksi
Publisher : PT. Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v45i9.618

Abstract

Berkembangnya ilmu bioinformatika merupakan konsekuensi banyaknya data eksperimen laboratorium para peneliti biologi molekuler maupun biomedis. Selain pengembangan basis data terpusat yang merupakan kompetensi inti ilmu bioinformatika, pendekatan komputasi lain seperti pembelajaran mesin juga dikembangkan sehingga data tersebut dapat diolah menjadi informasi yang berguna bagi dunia kesehatan. Kajian ini akan menelaah perkembangan pendekatan pembelajaran mesin pada ilmu bioinformatika, dan aplikasinya pada dunia kesehatan terutama pada informatika kanker dan virus. Masa depan aplikasi medis dengan ilmu bioinformatika menarik karena melibatkan berbagai pendekatan baru seperti kecerdasan buatan dan biologi sistem.The development of bioinformatics science is a consequence of the massive data generation of laboratory experiments conducted by molecular biology and biomedical researchers. In addition to the development of a centralized database that is the core competence of bioinformatics science, other computing approaches such as machine learning are also developed so that the data can be processed into useful information for the human health. This review will examine the development of machine learning approaches in bioinformatics science, and its application to the human health, especially in cancer and virus informatics. The future of medical applications with bioinformatics science is exciting as it involves various new approaches such as artificial intelligence and system biology. 
Troubled Helix – Tinjauan Multiperspektif Genetika dalam Bioetika Dito Anurogo; Arli Aditya Parikesit
Cermin Dunia Kedokteran Vol 48, No 3 (2021): Obstetri dan Ginekologi
Publisher : PT. Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v48i3.1331

Abstract

Dalam review ini, dibahas tinjauan multiperspektif genetika dalam bioetika. Dikemukakan prinsip-prinsip etika mutakhir, seperti: reciprocity, mutuality, solidarity, citizenry, dan universality. Dibahas pula prinsip-prinsip etika dan pemeriksaan genetika, seperti: otonomi, privasi, kebaikan, nonmaleficence, keadilan. Didiskusikan pula perspektif etnokultural dalam layanan genetika, milestones guideline etika dan regulasi riset biomedis internasional, prinsip-prinsip etika menurut Universal Declaration on Bioethics and Human Rights 2005, hak asasi manusia dan etika profesional: apresiasi translasional, perspektif utilitarianisme, perspektif deontologi, “simalakama” pemeriksaan genetika, globalisasi bioetika, etika bioinformatika, dan riset eugenik.In this review, a multiperspective review of genetics in bioethics is discussed. The latest ethical principles are mentioned, such as: reciprocity, mutuality, solidarity, citizenry, and universality. The principles of ethics and genetic inquiry, such as: autonomy, privacy, kindness, nonmaleficence, justice was also discussed. Also discussed are multiperspective, ethnocultural perspectives in genetic services, milestones of ethical guidelines and international biomedical research regulations, ethical principles according to the Universal Declaration on Bioethics and Human Rights 2005, human rights and professional ethics: translational appreciation, utilitarianism perspective, deontological perspective, the “simulacra” of genetic examination, bioethics globalization, bioinformatics ethics, and eugenic research.
Drug Repurposing Option for COVID-19 with Structural Bioinformatics of Chemical Interactions Approach Arli Aditya Parikesit; Rizky Nurdiansyah
Cermin Dunia Kedokteran Vol 47, No 3 (2020): Dermatologi
Publisher : PT. Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v47i3.376

Abstract

The SARS-CoV-2 virus is the pathogenic agent that caused the COVID-19 disease. The epicenter of this disease is the city of Wuhan, China. It is already categorized as “pandemic” by WHO, as many countries already affected with the infections, including recently Indonesia. Although the standard RT-PCR and DNA sequencing protocols has already developed for diagnostic, no drugs are available to cure this disease until today. The anti-malaria drug of chloroquine phosphate was repurposed, as well as other anti-viral drugs. In this regard, a structural bioinformatics pipeline was utilized to validate the claim in the computational realm. Within the sphere of the online molecular docking method, it was found that all the tested repurposed drugs attached accordingly with the SARS-CoV-2 protease enzyme that plays a role in viral replication. The repurposed drugs could be proposed as drug candidates for COVID-19, after clinical trials or further laboratory testing.Virus SARS-CoV-2 adalah patogen penyebab penyakit COVID-19. Episentrum penyakit ini adalah kota Wuhan, Tiongkok. WHO mengeluarkan peringatan ‘pandemi’ karena banyak negara sudah terkena infeksi, termasuk Indonesia. Meskipun protokol RT-PCR dan sekuensing DNA standar telah dikembangkan untuk tujuan diagnostik, hingga saat ini tidak ada obat untuk menyembuhkan penyakit ini. Obat anti-malaria chloroquine phosphate dicoba, bersama dengan beberapa obat anti-virus. Alur analisis bioinformatika struktural digunakan untuk validasi di ranah komputasi. Dalam lingkup metode molecular docking secara daring, ditemukan bahwa obat tersebut tertambat dengan enzim protease SARS-CoV-2 yang berperan dalam replikasi virus. Obat ini dapat diusulkan sebagai kandidat obat untuk COVID-19, setelah pengujian laboratorium dan uji klinis lebih lanjut.
Revolution in Detecting Tuberculosis using Radiology with Application of Deep Learning Algorithm Putri Gabriella Angel Natalia Satya; Arli Aditya Parikesit
Cermin Dunia Kedokteran Vol 48, No 4 (2021): Dermatologi
Publisher : PT. Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v48i4.1475

Abstract

Radiology is a medical examination of internal body parts using data imaging to interpret an illness. Many illnesses can be detected using this medical discipline; one of the diseases is tuberculosis caused by Mycobacterium tuberculosis bacteria. The supreme ability of Artificial Intelligence and Machine learning has amazed the radiologist in analyzing big data-based information. A better deep learning algorithm can lead radiologist to accurate results. This article will review ten (10) research papers that use a deep learning algorithm in the application to detect tuberculosis by data processing technique. The goal is to know the best type of data processing in deep learning to detect TB.Radiologi adalah pemeriksaan bagian dalam tubuh menggunakan data pencitraan untuk interpretasi suatu penyakit. Banyak penyakit dapat dideteksi menggunakan disiplin medis ini; salah satu adalah tuberkulosis yang disebabkan oleh bakteri Mycobacterium tuberculosis yang menyerang paru-paru. Ahli radiologi tertarik atas kemampuan Artificial Intelligence dan Machine Learning untuk analisis data yang akurat. Artikel ini akan mengulas sepuluh (10) makalah penelitian aplikasi algoritma deep learning untuk deteksi tuberkulosis menggunakan teknik pengolahan data.
Co-Authors Adi Sofyan Ansori, Muhammad Albert Widjaja Aldino Hafidzhah, Muhammad Alhussain, Shaheer Alyaa Farrah Dibha Angelique, Priscilla Arif Nur Muhammad Ansori Bernard, Stefanus Bhat, Nausheen Burkov, Pavel Chandra, Nelson David Agustriawan Dedy Sugiono Deidre Valeska, Margareta Derkho, Marina Dian, Farida Aryani Didik Huswo Utomo Dito Anurogo Dito Anurogo Dito Anurogo Dito ANUROGO Dito Anurogo Dito Anurogo Dito Anurogo, Dito Ema Utami Ezra Bernandus Wijaya Fugaha, Daniel Ryan Gabriela, Vania Gabriele Mustika Kresnia Gabriella Patricia Adisurja Hafidzhah, Muhammad Aldino Heerlie, Devita Mayanda Herdiansyah, Mochammad Aqilah Hutapea, Hotma Martogi Lorensi Imron Imron Jakhmola, Vikash Jeremias Ivan Josephine, Evalina Junaida Astina Karimah, Nihayatul Karimah, Nihayatul Kharisma, Viol Dhea KUSRINI Kusrini, Kusrini Maksim Rebezov Margareta Deidre Valeska Margaretha, Febrina Maria Kiseleva Maulani Wijaya, Renadya Miko Wahyono, Tri Yunis Muhammad Aldino Hafidzhah Muhammad Aldino Handzhah Muhammad Hermawan Widyananda Murtadlo, Ahmad Affan Ali Nadezhda Kenijz Natalia Satya, Putri Gabriella Angel Nelda Aprilia Salim Nihayatul Karimah Patricia Adisurja, Gabriella Patricia, Gabriella Posa, Gabrielle Ann Villar Prakoso, Muhammad Ja'far Pratama, Rico Alexander Putri Gabriella Angel Natalia Satya Rahadian Zainul Ramanto, Kevin Nathanael Ratnasari, Nanda Risqia Pradana Renadya Maulani Wijaya Ridarto, Afif Maulana Yusuf Riza A PUTRANTO Rizky Nurdiansyah Rizky, Wahyu Choirur Ryan Fugaha, Daniel Ryan Wijaya Ryan Wijaya, Ryan Satrio Wibowo Scherbakov, Pavel Sepiashvili, Ekaterina Shemuel, Josia Sofy Permana Sri Wahyuningsih Stefanus Bernard Sudaryo, Mondastri Korib Sugiono, Dedy Svetlana Artyukhova Tambunan, Usman Sumo Friend Teguh Hari Sucipto, Teguh Hari Theo A Tochary Tochary, Theo A. Usman Sumo Friend Tambunan Utomo, Didik Huswo Utomo, Didik Huswo Vikash Jakhmola Viol Dhea Kharisma Wicaksono, Adhityo Wijaya, Renadya Maulani Yanuargi, Bayu Yulia Matrosova