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All Journal Biosfer: Jurnal Tadris Biologi Jurnal Pekommas Jurnal Politik Profetik Jurnal Bioedukasi Al-Jabar : Jurnal Pendidikan Matematika JOIV : International Journal on Informatics Visualization JURNAL ILMIAH INFORMATIKA JTAM (Jurnal Teori dan Aplikasi Matematika) Biosel: Biologi Science and Education PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Teknologi Terpadu Jurnal Ilmiah Akuntansi dan Finansial Indonesia Jurnal Performa : Jurnal Manajemen dan Start-up Bisnis Journal of System and Computer Engineering Indonesian Journal of Intellectual Publication (IJI Publication) Journal of Community Engagement Research for Sustainability East Asian Journal of Multidisciplinary Research (EAJMR) JURTEII: Jurnal Teknologi Informasi Jurnal Pengabdian Pelitabangsa Indonesian Journal of Advanced Social Works (DARMA) Economics, Business, Accounting & Society Review Journal of Applied Accounting Journal Pharmacy and Application of Computer Sciences PEDAGOGIC: Indonesian Journal of Science Education and Technology Advances in Computer System Innovation Journal (ACSI Journal) Ihsanniat: Jurnal Pengabdian Kepada Masyarakat Journal of Architecture, Landscape & Urban Design Indonesian Journal of Intellectual Publication (IJI Publication)
Rijal, Muhammad
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : Journal of System and Computer Engineering

 1 
Klasifikasi Ulasan Konsumen Menggunakan Random Forest dan SMOTE Istiqamah, Nurul; Rijal, Muhammad
Journal of System and Computer Engineering Vol 5 No 1 (2024): JSCE: Januari 2024
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v5i1.1061

Abstract

Ulasan berupa deskripsi teks direpresentasikan dalam bentuk skala peringkat tidaklah cukup sebagai acuan dalam menentukan sentimen yang seringkali bias. Penelitian ini dilakukan untuk mengklasifikasi ulasan konsumen dengan menerapkan teknik klasifikasi sentimen pada tingkat dokumen. Penelitian ini berfokus pada imbalanced class klasifikasi ulasan konsumen. Metode yang digunakan dalam mengatasi permasalahan imbalanced class adalah Synthetic Minority Oversampling Technique (SMOTE) dan Random Under-sampling (RUS) pada tahap pre-processing dan pada klasifikasi menggunakan Random Forest. Fitur data yang digunakan adalah fitur teks ulasan (proses analisis dan klasifkasi sentimen) dan fitur peringkat (proses pelabelan). Penerapan teknik class imbalanced (dalam hal ini SMOTE dan RUS) pada tahapan pre-processing mampu memberikan perubahan peningkatan akurasi dan mengenali data yang awalnya dianggap minor.
Evaluating the Effectiveness of Online Learning Methods with a Probabilistic Naive Bayes Approach Butsiarah, Butsiarah; Rijal, Muhammad
Journal of System and Computer Engineering Vol 6 No 1 (2025): JSCE: January 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i1.1669

Abstract

Online learning methods become an important element in supporting the flexibility and effectiveness of teaching and learning process, especially through approaches such as Video Tutorial, Virtual Discussion, and Self-paced Reading. This research aims to evaluate the effectiveness of the three methods in improving students' engagement, comprehension, and learning motivation by utilizing Naive Bayes algorithm. The dataset used includes student data taken through questionnaires and teacher evaluation results, with variables such as material suitability, engagement, ease of access, and student exam results. Through this approach, the research is able to predict the learning method that best suits students' needs based on the analyzed variables. The results show that Video Tutorial is the most effective method in supporting students' understanding and motivation. The implementation of this research is expected to help the development of a better online learning system in improving students' learning experience, and provide practical recommendations for educators in choosing the right learning method.
Performance Exploration of Tree-Based Ensemble Classifiers for Liver Cirrhosis: Integrating Boosting, Bagging, and RUS Techniques Aziz, Firman; Jeffry, Jeffry; Wungo, Supriyadi La; Rijal, Muhammad; Usman, Syahrul
Journal of System and Computer Engineering Vol 6 No 3 (2025): JSCE: July 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i3.2031

Abstract

Liver cirrhosis, as a significant chronic liver disease, exhibits a rising global prevalence, demanding more effective preventive approaches. In an effort to enhance early detection and patient management, this research proposes the development of a liver cirrhosis risk prediction model using machine learning technology, specifically comparing the performance of three ensemble tree models: Ensemble Boosted Tree, Ensemble Bagged Tree, and Ensemble RUSBoosted Tree. Utilizing clinical and laboratory data from adults with a history or risk of cirrhosis, the study reveals that Ensemble Bagged Tree achieved the highest accuracy at 71%, followed by Ensemble Boosted Tree (67.2%) and Ensemble RUSBoosted Tree (66%). Analysis of clinical and laboratory variables provides further insights into the most significant contributors to risk prediction. The findings lay the groundwork for the advancement of a more sophisticated liver cirrhosis risk prediction tool, supporting a vision of more personalized and effective preventive strategies in liver disease management
Co-Authors Abasa, Sustrin Abdillah Abdillah Abdul Rahman Adriana Hiariej, Adriana Al Husaini, Muhammad Arief Al Husaini, Muhd Arief Alfina Hidayah Amil Ahmad Ilham Amirin, Amirin Andita Nurul Kurniawati Putri Anggraini, Pitria Annisa Putri Arifuddin Arifuddin Astri nadira, Nur Astuti, Lidya Aziza Fitriah, Aziza Butsiarah Darwis Said, Darwis Dewi, Alya Puspita Dian Safitri Enny Hardi Firman Aziz Hendera, Hendera Husaini, Muhd. Arief Al Imkari, Sarty Irsyadunas, Irsyadunas Istiqamah, Nurul Jamilah Jamilah Jeffry Jeffry Kamarullah, Reza Kuswoyo, Indra Mardiah, Faijah Marlina Marlina Mashuri Mashuri Masi, Yusman Masnur Masnur Mastuti, Ajeng Gelora Maulida, Sri Mediaty Mira Dharma Susilawaty Morian Saspriatnadi Mughaffir Yunus Muhajir Abd Rahman Muhammad Yunus Muhibuddin Muhibuddin, Muhibuddin Mulyawati, Nina Yuliana Mutmainnah, Heni Mutmainnah, Heny Nadilla, Dhea Nani Nurani Muksin Natsir, Nur Alim Ningsih, Rahmi Dwi Nurmuzayyana, Nurmuzayyana Nurul Fathanah Mustamin Nurul Istiqamah Ola Rivai, Andi Tenri Oriana Paramita Dewi Pary, Cornelia Paundu, Ady Wahyudi Putri Ayu Lestari Rahmat Hidayatullah Ratna Ayu Damayanti Reja Fahlevi Ridwan, La Rifqi Novriyandana Rifyal, Rifyal Rinaldi Rinaldi Rosmawati Rosmawati Rosmiani, Ni Nengah Safrida Safrida Sahputri, Masri Yanti Sahubauwa, Laila Samputri, Salma Sehuwaky, Nurlaila Sulastri Sulastri Sunarmin, Wa Ode Suryani, R. Lisa Susanti, Marisa Syahrul Usman Syamsurijal Syamsurijal, Syamsurijal Syarif, Asrul Bin Tanniewa, Adam M Thomson Mary, Thomson Tri Yunarni, Baiq Reinalda Wahyu Hidayat Wungo, Supriyadi La Yani, Andi Muhammad Zulkarnaim, Zulkarnaim