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All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) International Journal of Quantitative Research and Modeling SisInfo : Jurnal Sistem Informasi dan Informatika Nuansa Informatika Jurnal Bhakti Karya dan Inovatif Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism) JUSTINFO| Jurnal Sistem Informasi dan Teknologi Informasi
Marwondo
Department Of Informatic, Faculty Of Technology And Informatic, Universitas Informatika Dan Bisnis Indonesia, Bandung, Indonesia.
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Physics Social Sciences Other

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Journal : Nuansa Informatika

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ANALISIS SENTIMEN PELAKSANAAN KULIAH ONLINE MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE Setiana, Elia; Marwondo; Venia Retreva Danestiara; Wiyanudin
NUANSA INFORMATIKA Vol. 17 No. 2 (2023): Volume 17 No 2 Tahun 2023
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v17i2.11

Abstract

This writing aims to assess the satisfaction of students regarding the implementation of online lectures, categorized into three classes: positive, neutral, and negative. Data collection was conducted using Twint from the social media platform Twitter, with a total of 25,000 tweets. The data processing process to determine sentiment analysis utilized the support vector machine algorithm. With this algorithm, the obtained results show an accuracy rate of 76.86% for positive sentiment. The precision is 0.49, recall is 0.53, and the F1 score is 0.51
Klasifikasi Kebutuhan Dokter untuk Kesejahteraan Masyarakat Menggunakan ANFIS Marwondo; Saputra, Jepi Sutarlan; Mahardika, Habib Fauzan; Aziz, Fauzan Nur
NUANSA INFORMATIKA Vol. 18 No. 2 (2024): Nuansa Informatika 18.2 Juli 2024
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v18i2.204

Abstract

In social life, the need for medical workers is different in each region, because the population varies. If doctors cannot treat a large enough number of patients in an area, it can have various impacts on society, such as contracting dangerous diseases if not treated as soon as possible. The effect will be a decline in people's standard of living. By classifying the need for the number of health workers (doctors) relative to the population, the level of welfare in an area can be obtained. To assist in optimizing health workers (doctors) they can use fuzzy logic and ANFIS (Adaptive Neuro Fuzzy Inference System). By using ANFIS, it is hoped that we can find the optimal value for the classification of health workers that will be needed in each region. In the ANFIS test, the RMSE error value was 0.2698 and the first accuracy value was 73%. Then by adding a membership function, an RMSE error value of 0.17698 was obtained, this second accuracy value increased by 10% to 83%. By using the ANFIS method to classify health workers according to different population sizes in each region, you can measure the level of community welfare well.
Co-Authors Alif Gufron Pratama Aziz, Fauzan Nur Catherin Rumambo Mogot Pandin Elia Setiana Imannudin Akbar Iqbal Ardiansyah Iqbal Maulana Mahardika, Habib Fauzan Michael A. Yonathan Nugraha Nugraha Nugraha, Dimas Adi Nugroho, Abdul Hadi R. Yadi Rakhman R. Yadi Rakhman R. Yadi Rakhman Alamsyah Ruslan Efendi Santi Dwi Putri Saputra, Jepi Sutarlan Sardjono Sardjono Sardjono Sardjono Sardjono Sarjono Sarjono Seny Nurhasanah Setiana, Elia Taufik Hidayah Taufik Hidayah Titan Parama Yoga Ujang Riswanto Vani Maharani Nasution Venia Retreva Danestiara Wahyu Kurnianto Wilner Saut Lamhot Wiyanudin