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All Journal Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal S2 Pendidikan Matematika Jurnal Didaktik Matematika AKSIOMA: Jurnal Program Studi Pendidikan Matematika Jurnal Teknologi Informasi dan Ilmu Komputer AlphaMath: Journal of Mathematics Education The Indonesian Journal of Occupational Safety and Health Fountain of Informatics Journal Jurnal Pembelajaran Matematika IKRA-ITH Informatika : Jurnal Komputer dan Informatika Dinamisia: Jurnal Pengabdian Kepada Masyarakat Buana Matematika : Jurnal Ilmiah Matematika dan Pendidikan Matematika JUMANJI (Jurnal Masyarakat Informatika Unjani) Multitek Indonesia : Jurnal Ilmiah JUSIM (Jurnal Sistem Informasi Musirawas) METIK JURNAL M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Ideas: Jurnal Pendidikan, Sosial dan Budaya International Journal on Teaching and Learning Mathematics Mosharafa: Jurnal Pendidikan Matematika Jurnal Tika Lani: Jurnal Kajian Ilmu Sejarah dan Budaya Abdiformatika: Jurnal Pengabdian Masyarakat Informatika MATHEMATIC EDUCATION AND APLICATION JOURNAL (META) Unnes Journal of Mathematics Education PELS (Procedia of Engineering and Life Science) Malcom: Indonesian Journal of Machine Learning and Computer Science TEKNOLOGI NUSANTARA Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat JOINCS (Journal of Informatics, Network, and Computer Science) Biner : Jurnal Ilmiah Informatika dan Komputer Abadi: Jurnal Ahmad Dahlan Mengabdi Prosiding Seminar Nasional Unimus Riemann : Research of Mathematics and Mathematics Education Jurnal Pendidikan Matematika Universitas Lampung Hipotenusa: Journal of Mathematical Society Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK)
Triana Harmini
Teknik Informatika, Universitas Darussalam Gontor
Religion Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : PELS (Procedia of Engineering and Life Science)

 1 
Outlier Detection On Graduation Data Of Darussalam Gontor University Using One-Class Support Vector Machine Oddy Virgantara Putra; Triana Harmini; Ahmad Saroji
Procedia of Engineering and Life Science Vol 2 (2021): Proceedings of the 3rd Seminar Nasional Sains 2021
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (496.665 KB) | DOI: 10.21070/pels.v2i0.1139

Abstract

Outlier detection is an important field of study because it is able to detect abnormal data distribution from a set of data. In the student graduation data, there are students with high semester GPA but do not graduate on time but students with low semester GPA can graduate on time. This study aims to detect outlier values ​​in student graduation data for the 2020-2021 class. Factors (attributes) used in this study are Student Academic Support Credit Scores (AKPAM) and Social Studies from semester one to semester six. The dataset used is 1204 graduates. The outlier detection method used is One-Class Support Vector Machine (SVM). One-class SVM is a derivative of SVM method that detects outliers based on data outside the specified class. The results of outlier detection using One-Class SVM method with three types of kernels produce the following reference values: kernel 'rbf' n by 91.4%, kernel 'linear' by 90% and kernel 'poly' by 90%. After normalization using MinMaxScaler the reference value increased by 2% in each kernel. The results of testing the One-Class SVM method get an average 90.3%, thus it can be concluded that the One-Class SVM method is feasible to be used as an outlier detection method.
Sentiment Analysis Covid-19 Vaccination on Twitter Social Media Using Naïve Bayes Method Dihin Muriyatmoko; Triana Harmini; Maulana Kemal Ardiansyah
Procedia of Engineering and Life Science Vol 2 (2021): Proceedings of the 3rd Seminar Nasional Sains 2021
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (770.976 KB) | DOI: 10.21070/pels.v2i0.1144

Abstract

The government regulations regarding the implementation of vaccinations to tackle the COVID-19 pandemic. The regulation was issued by the Minister of Health Number ten of 2021. This program raises pros and cons so that it requires feedback for evaluation. Feedback can be obtained from opinions and stories that users convey through social media such as Twitter. This study aims to develop a model to determine public sentiment towards Covid-19 vaccination in three topics, namely the vaccination program, the effect of vaccination and the Covid-19 vaccine. The classification method used in this research is Bernoulli Naïve Bayes and Logistic Regression. The results of the comparison of the two methods show that Bernoulli Naïve Bayes gets better accuracy results. The number of tweet messages processed from Twitter is 5877. The model was tested to read public sentiment on Twitter from 7 September to 21 September 2021. The model concluded that public opinion regarding the vaccination program and the effect of vaccination tended to be positive. And opinions regarding the Covid-19 vaccine topic tend to be neutral. For further research, it can be developed by adding datasets.
Co-Authors Abdul Rohman Ahmad Saroji Alif Sita Maharani Andrian Maulana Arifah, Dian Afif Asy’ari, Nur Aini Shofiya Aviary Azahra, Renaya Aziz Musthafa Aziz Musthofa Dewi Retno Sari S Dewi Retno Sari S Dihin Muriyatmoko Dwiki Kurniawan Ebenezer Bonyah Eko Prasetio Widhi Ely Windarti Hastuti Faisal Reza Pradhana Febri Vicky Allen Ghulam Mushthofa Hafidz, Dhiya Irsyad Ilyasa Azmi Imam Sujadi Imam Sujadi Kintoko, Kintoko Lingga Sempana Hidayat Lukman Effendi Lukman Effendi, Lukman Maulana Kemal Ardiansyah Miftahuddin Fahmi Moch. Nasheh Annafii Mochamad Naufal Mohamad Farhat Mohammad Ridho Cahyono Mubarok, M. Shulton Muhamad Anwar Aditya Muhamad Nuradi Arrahmantoro Muhammad Ariel Naafi' Muhammad Naufal Muhammad Nurrizky Ekaputra Muhammad Rijal Yahya Muhammad Taqiyuddin Muhammad Zarkasih, Muhammad Musthofa, Aziz Nabiila Fatimatuz Zahra Naufal Fikri Al Azmi Niken Sylvia Puspitasari Nugroho Arif Sudibyo NUR SURYANITA, DEVI Nurhana Marantika Oddy Virgantara Putra Pradana, Kelvin Pradipta Annurwanda Rafiq, Abid Ratih Andhika Akbar Rahma Saroji, Ahmad Setiawan, Angga Fahri Shoffin Nahwa Utama Siti Suprihatingsih Siti Suprihatiningsih Taufiqurrahman Taufiqurrahman Trisnaningrum, Niken Umi Isnatin Warniasih, Kristina Wildan Sulistiono Zsaffa Aulia Putri Prasetyo