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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Sistem Komputer Jurnal Simetris Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) Jurnas Nasional Teknologi dan Sistem Informasi CESS (Journal of Computer Engineering, System and Science) JOIV : International Journal on Informatics Visualization JURNAL REKAYASA TEKNOLOGI INFORMASI IJISTECH (International Journal Of Information System & Technology) MIND (Multimedia Artificial Intelligent Networking Database) Journal Journal of Appropriate Technology for Community Services IJISTECH JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Pengabdian Siliwangi International Journal of Applied Information Systems and Informatics
Acep Irham Gufroni
Jurusan Sistem Informasi, Fakultas Teknik, Universitas Siliwangi
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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Journal : JOIV : International Journal on Informatics Visualization

 1 
Implementation of Ensemble Machine Learning Classifier and Synthetic Minority Oversampling Technique for Sentiment Analysis of Sustainable Development Goals in Indonesia Gufroni, Acep Irham; Hoeronis, Irani; Fajar, Nur; Rachman, Andi Nur; Sidik Ramdani, Cecep Muhamad; Sulastri, Heni
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.1949

Abstract

As part of the Sustainable Development Goals (SDGs), governments worldwide have committed to improving people's lives to improve the quality of life for all, including the 17 such goals that were agreed upon in 2015 to benefit the human race as a whole. It would be interesting to see how society responds to the SDGs after approximately half of them have been achieved. This public response was analyzed in terms of sentiment. Within the total number of internet users in Indonesia, there are 18.45 million Twitter users. The platform enables anyone to write about anything they are experiencing in their lives, such as what is happening in their environment, what is happening in their education system, what is happening in the food industry, how people feel, and many more. The platform enables anyone to write about anything they are experiencing in their lives, such as what is happening in their environment, what is happening in their education system, what is happening in the food industry, how people feel, and many more. To model the data collected, the researchers used Ensemble Machine Learning Classifiers (EMLC) to model the data by using a machine learning classifier that uses machine learning techniques. The best model in this study is EMLC-Stacking with a data splitting of 80:20 and using SMOTE, which obtains an accuracy of 91%. This accuracy results from a 5% increase compared to when not using SMOTE. From 15,698 tweets, this research found that 47% were positive sentiments, 28% were negative sentiments, and 25% were neutral sentiments. The results that we measured offer hope that there will be a positive trend in the journey of the SDGs until 2030 if these findings are true.
Academic Performance Prediction Using Supervised Learning Algorithms in University Admission Gufroni, Acep Irham; Purwanto, Purwanto; Farikhin, Farikhin
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2974

Abstract

Each educational institution has designed an academic system with the aim of providing as perfect learning as possible to students. The quality of good students is influenced by various factors, one of which is the available academic system. Previous research has shown that the quality of a student, which can be called academic achievement, can be determined through historical data on the student admission process. This research aims to process one of the admission processes previously implemented in Indonesian state universities using the National Selection for State University Entrance (SNMPTN) data, combined with Cumulative Achievement Index (GPA) data, so that it can be processed using a machine learning model. The algorithm used to create the model is a Supervised Learning Classification algorithm, which includes a Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGB). The research was carried out in three schemes based on the percentages of training data and test data. The results obtained show that DT produces the highest accuracy and precision values, with an accuracy value of 0.79 and a precision value of 0.56, respectively. The XGB produces the highest recall and f1-score values, with a recall value of 0.35 and an f1-score value of 0.36. The model with the highest f1-score can be selected as the best model, namely, the model with the XGB algorithm on a 70%-30% train-test data scheme. The resulting model achieved a success rate of 77%.
Co-Authors -, Rianto Aemy, Nandhitta Andi Nur Rachman Andi Nur Rachman Andi Nur Rachman Andi Nur Rachman Aradea Baetulloh, Uci Baetulloh, Uci Cecep Muhamad Sidik Ramdani Cecep Muhamad SR Dewi , Euis Nur Fitriani Dewi, Euis Nur Fitriani Euis Nur Fitriani Dewi Fransiska, Susanti Gina Rahmayati Heni Sukmawati Heni Sulastri Heni Sulastri Irani Hoeronis Juwanda, Farikhin Miftahul Habib Fachrurozi Millah, Haikal Nanda Adi Pamungkas Nur Fajar Nurul Hiron Nurul Hiron Pratama, Eneng Kurnia Dewi Purwanto Purwanto R. Reza El Akbar Rachman, Andi Nur Rahmi Nur Shofa Rahmi Nur Shofa Rahmi Nur Shofa Ramdani, Cecep Muhamad Sidik Rianto Rianto Rianto, Rianto Riza Lukmanulhakim Rizkya, Adilia Tri Ruswati, Ruswati Ruswati, Ruswati Shofa, Rahmi Nur Sidik Ramdani, Cecep Muhamad Siti Yuliyanti, Siti Sukmawati, Heni Sulastri , Heni Sulastri, Heni Wisandani, Iwan Yaya Abdul Malik