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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA CommIT (Communication & Information Technology) Al-Jabar : Jurnal Pendidikan Matematika Union: Jurnal Ilmiah Pendidikan Matematika Jurnal Matematika: MANTIK Wacana Akademika : Majalah Ilmiah Kependidikan Numeracy : Jurnal Ilmiah Pendidikan Matematika IndoMath: Indonesia Mathematics Education BAREKENG: Jurnal Ilmu Matematika dan Terapan Teorema: Teori dan Riset Matematika JURNAL VOKASI TEKNOLOGI INDUSTRI (JVTI) Pedagogik : Jurnal Pendidikan Guru Sekolah Dasar Recent in Engineering Science and Technology Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Applied Mathematics and Statistics
Samsul Arifin
Binus University
Agriculture, Biological Sciences & Forestry Arts Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation

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Journal : CommIT (Communication

 1 
An Explainable AI Model for Hate Speech Detection on Indonesian Twitter Muhammad Amien Ibrahim; Samsul Arifin; I Gusti Agung Anom Yudistira; Rinda Nariswari; Abdul Azis Abdillah; Nerru Pranuta Murnaka; Puguh Wahyu Prasetyo
CommIT (Communication and Information Technology) Journal Vol. 16 No. 2 (2022): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v16i2.8343

Abstract

To avoid citizen disputes, hate speech on social media, such as Twitter, must be automatically detected. The current research in Indonesian Twitter focuses on developing better hate speech detection models. However, there is limited study on the explainability aspects of hate speech detection. The research aims to explain issues that previous researchers have not detailed and attempt to answer the shortcomings of previous researchers. There are 13,169 tweets in the dataset with labels like “hate speech” and “abusive language”. The dataset also provides binary labels on whether hate speech is directed to individual, group, religion, race, physical disability, and gender. In the research, classification is performed by using traditional machine learning models, and the predictions are evaluated using an Explainable AI model, such as Local Interpretable Model-Agnostic Explanations (LIME), to allow users to comprehend why a tweet is regarded as a hateful message. Moreover, models that perform well in classification perceive incorrect words as contributing to hate speech. As a result, such models are unsuitable for deployment in the real world. In the investigation, the combination of XGBoost and logical LIME explanations produces the most logical results. The use of the Explainable AI model highlights the importance of choosing the ideal model while maintaining users’ trust in the deployed model.
Program Evaluation and Review Technique (PERT) Analysis to Predict Completion Time and Project Risk Using Discrete Event System Simulation Method Yudistira, I Gusti Agung Anom; Nariswari, Rinda; Arifin, Samsul; Abdillah, Abdul Azis; Prasetyo, Puguh Wahyu; Susyanto, Nanang
CommIT (Communication and Information Technology) Journal Vol. 18 No. 1 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i1.8495

Abstract

The prediction of project completion time, which is important in project management, is only based on an estimate of three numbers, namely the fastest, slowest, and presumably time. The common practice of applying normal distribution through Monte Carlo simulation in Program Evaluation and Review Technique (PERT) research often fails to accurately represent project activity durations, leading to potentially biased project completion prediction. Based on these problems, a different method is proposed, namely, Discrete Event Simulation (DES). The research aims to evaluate the effectiveness of the simmer package in R in conducting PERT analysis. Specifically, there are three objectives in the research: 1) develop a simulation model to predict how long a project will take and find the critical path, 2) create an R script to simulate discrete events on a PERT network, and 3) explore the simulation output using the simmer package in the form of summary statistics and estimation of project risk. Then, a library research with a descriptive and exploratory method is used for data collection. The hypothetical network is used to obtain the numerical results, which provide the predicted value of the project completion, the critical path, and the risk level. Simulation, including 100 replications, results in a predicted project completion time and a standard deviation of 20.7 and 2.2 weeks, respectively. The DES method has been proven highly effective in predicting the completion time of a project described by the PERT network. In addition, it offers increased flexibility.
Co-Authors Abdillah, Abdul Azis Abdul Azis Abdillah Adi Adi Agus Sukandi Alfian Alfian Arif Rahman Hakim Arumella Surgandini Assagaf, Idrus Bobbi Rahman Dewi Yanti Liliana Dwi Anto, Septian Dwi Wijonarko Edistria, Ega Effendi, Melody Elita Putri, Rizky Ga, Jonri Lomi I Gusti Agung Anom Yudistira Indra Bayu Muktyas Indra Bayu Muktyas Jimy, Valensius Jonathan, Stanley Jufra, Arlita Aristianingsih Jufra, Jufra Klara Iswara Sukmawati Lucky, Henry Manurung , Monica Mayeni Manurung, Mika Meitriana Manurung, Monica Mayeni Muhamad Faisal, Muhamad Muhammad Amien Ibrahim Muhammad Faisal Muktyas, Indra Bayu Muzakki, Zahran Nerru Pranuta Murnaka, Nerru Pranuta Nugraha, Edwin Setiawan Pimpi, La Pratama, Muhammad Nabil Priambodo, Oktanindita Puguh Wahyu Prasetyo, Puguh Raditha, Alya Maura Ramadhani, Sausan Repka, Joe Rezakusuma, Muhammad Rinda Nariswari Rinda Nariswari RONI Rully Charitas Indra Prahmana Rusli P. D. Kolnel Safitri, Raudhatun Seleki, Jacob Stevy Setyawan, Fariz Siti A. M. Karubaba Suharno Suharno Sulistiawati Sulistiawati Sulistiawati Sulistiawati Susyanto, Nanang Sutrisno, Utis Tri Handayani Usep Widyakusuma, Nita Wijaya, Andryan Kalmer Wijayanti, Dian Eka Winarto Selamet, Muhammad Windria, Hening Wiwik Wiyanti, Wiwik Yanuar Yanuar Yulia Wulandari, Yulia Zenklinov, Amanatullah Pandu