Article Per Year (5 Year)
p-Index From 2020 - 2025
4.124
P-Index
This Author published in this journals
All Journal Telematika : Jurnal Informatika dan Teknologi Informasi Sistemasi: Jurnal Sistem Informasi Jurnal CoreIT Jurnal Informatika Universitas Pamulang Krea-TIF: Jurnal Teknik Informatika JOISIE (Journal Of Information Systems And Informatics Engineering) Building of Informatics, Technology and Science Zonasi: Jurnal Sistem Informasi Jurnal Daur Lingkungan Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Computer Science and Information Technology (CoSciTech) AloHA International Journal of Health Advancement (AIJHA) Journal of Community Development JURNAL ILMU DAN TEKNOLOGI KESEHATAN TERPADU Malcom: Indonesian Journal of Machine Learning and Computer Science JURNAL SANITASI LINGKUNGAN Journal Of Artificial Intelligence And Software Engineering SEGANTANG LADA : JURNAL PENGABDIAN KESEHATAN Jurnal Indonesia : Manajemen Informatika dan Komunikasi Science, Technology, and Communication Journal
Iwan Iskandar
Jurusan Kesehatan Lingkungan, Poltekkes Kemenkes, Tanjungpinang, Kepulauan Riau,, 29124
Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Nursing Public Health Social Sciences

Published : 34 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Jurnal Informatika Universitas Pamulang

 1 
Analisis dan Desain Data Center RSUD Arifin Achmad Pekanbaru Menggunakan Standarisasi TIA 942 Syaputra, Alviandy; Iskandar, Iwan; Darmizal, Teddie; Novriyanto, Novriyanto; Safaat, Nazruddin
Jurnal Informatika Universitas Pamulang Vol 8 No 4 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i4.36564

Abstract

Arifin Achmad Regional General Hospital (RSUD) has a large amount of patient data so it requires a data center to store and manage all the data. In this study, an analysis of the data center at RSUD Arifin Achmad was carried out using the TIA-942 standard. Based on the results of observations that have been made, it is obtained that the current condition of the data center has several shortcomings, including the electrical system that does not yet have a private generator as a redudant, the security system that is still minimal, and the room conditions that are still limited. Based on these problems, an analysis was carried out using the PPDIOO (Prepare, Plan, Design, Implement, Operate, and Optimize) Network Life Cycle Approach method with the TIA-942 standardization approach In this research, it has been carried out up to the design stage, where at the prepare stage, search and collect related information, interview experts to gain a better understanding of the TIA-942 standard, at the planning stage (plan) a comparative analysis of the current data center with the TIA-942 standard using GAP analysis, and at the design stage (design) the design of the proposed Tier 2 data center is made. The results of this study are the current condition of the data center still in Tier 1 and provide recommendations for proposals in the form of data center designs at Tier 2 in accordance with the TIA-942 standard.
Klasifikasi Sentimen Tweet Masyarakat terhadap Kendaraan Listrik Menggunakan Support Vector Machine Ananda, Nuari; Fikry, Muhammad; Yusra, Yusra; Handayani, Lestari; Iskandar, Iwan
Jurnal Informatika Universitas Pamulang Vol 8 No 4 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i4.36754

Abstract

Sentiment analysis involves using classification algorithms to analyze public opinions and feelings in text. Within the automobile industry, electric vehicles (EVs) stem from the circular economy and represent a novel technology under investigation in sentiment classification studies. The Support Vector Machine (SVM) algorithm is commonly used in this research due to its superior accuracy compared to other algorithms. The goal of this study is to apply SVM variable selection techniques to enhance sentiment analysis quality. Python is the programming language used to build the sentiment classification model, which involves feature selection using TF-IDF, training with cross-validation and grid search, evaluation using a confusion matrix, and storing the dataset in a MySQL database. The research focuses on the sentiment classification of 3000 public tweets about electric vehicles on Twitter. Through various scenarios, it was observed that the accuracy of sentiment classification varied depending on factors such as randomizing data, handling negation, and using different types of features like unigrams or bigrams. The highest accuracy achieved was 84% using a scenario with random data, negation handling, and unigram features. Overall, this research highlights the impact of randomizing data and selecting appropriate features on sentiment classification accuracy for electric vehicles on Twitter.
Co-Authors Afriyanti, Liza Agnesti, Syafira Agustian, Surya Agustina, Auliyah Ahmad, Rizmah Zakiah Nur Alvinur Hidayat, Alvinur Amelia, Felina Ananda, Nuari Ananda, Sherly Arasy, Abdurrahman Astuti, Indah Dwi Aulia Ramadhani Budianita , Elvia Cynthia , Eka Pandu Darmizal, Teddie Delifah, Nur Elin Haerani Elvia Budianita Fadhilah Syafria Fauziyyah, Laila Nurul Febi Yanto Fikri, Mhd Ikhsanul Fitri Insani Gusrianti, Elsa Gusti, Siska Kurnia Hamwar, Syahbudin Handayani, Lala Syafitri Haryadi - Herdiana, Dora Horiza, Hevi Idris, M. Fadhil Idris, Muhammad Fadhil Iis Afrianty Irsyad (Scopus ID: 57204261647), Muhammad Jasril Jasril Kholilah Samosir Lawami, Reza Haya Lestari Handayani MF, M.Yusuf Muhammad Affandes Muhammad Fikry Muhammad Irsyad Mukodri, Dewi Mey Lestanti Muliani, Sarifah Nazir, Alwis Nazruddin Safaat Nazruddin Safaat H Negara, Benny Sukma Novriyanto Novriyanto Permata, Rizkiya Indah Purnama, Irgi Putri. P, Zurneli Kurnia Ragil S, Mahdhan Reski Mai Candra Ridho Hilmawan, Ridho Rinaldi Daswito Ristina Rosauli Harianja rizkaramdhaniartie, siti Sandi, Wahyu Ari Sofiyah, Wan Suwanto Sanjaya Syaputra, Alviandy Tri Prastio Nugroho Yuhesti, Mutia Yuli Novita Sari, Yuli Novita Yusra Yusra, Yusra Zulya Erda