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All Journal Jurnal Ilmiah Informatika Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Kursor Jurnal Transformatika Jurnas Nasional Teknologi dan Sistem Informasi E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal CoreIT JPM (Jurnal Pemberdayaan Masyarakat) Jurnal BALIRESO Dinamisia: Jurnal Pengabdian Kepada Masyarakat ILKOM Jurnal Ilmiah KOMPUTIKA - Jurnal Sistem Komputer Journal of Information System, Applied, Management, Accounting and Research Celebes Abdimas: Jurnal Pengabdian Kepada Masyarakat Buletin Ilmiah Sarjana Teknik Elektro Indonesian Journal of Data and Science Indian Journal of Forensic Medicine & Toxicology International Journal of Engineering, Science and Information Technology Jurnal PkM (Pengabdian kepada Masyarakat) Caraka : Indonesia Journal of Communication Buletin Sistem Informasi dan Teknologi Islam Ilmu Komputer untuk Masyarakat Celebes Journal of Community Services KOPEMAS Jurnal Balireso: Jurnal Pengabdian pada Masyarakat Journal of Information Technology and its Utilization Linier: Literatur Informatika dan Komputer
Dolly Indra
Universitas Muslim Indonesia
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Journal : Jurnal Ilmiah Informatika Komputer

 1 
COMPARISON OF SENTIMENT CLASSIFICATION MODELS AT SULTAN HASANUDDIN AIRPORT IN MAKASSAR Muhammad Farhan Hermansyah; Dolly Indra; Ramdaniah Ramdaniah
Jurnal Ilmiah Informatika Komputer Vol 30, No 1 (2025)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2025.v30i1.14125

Abstract

Analisis sentimen menggunakan machine learning penting untuk memahami persepsi publik terhadap layanan bandara. Renovasi Bandara Sultan Hasanuddin Makassar bertujuan meningkatkan kapasitas dan kenyamanan, namun tanggapan masyarakat terkait perubahan ini beragam. Penelitian ini membandingkan efektivitas tiga algoritma machine learning—Naive Bayes Multinomial, Support Vector Machine (SVM), dan Random Forest—dalam menganalisis sentimen ulasan pengguna terkait renovasi Bandara Sultan Hasanuddin di Makassar. Penelitian ini juga menerapkan teknik pemisahan data dan preprocessing teks menggunakan Google Colab dengan pemrograman berbasis Python, termasuk pembersihan data, stemming dengan Sastrawi, penghilangan stopword, dan ekstraksi fitur menggunakan metode TF-IDF dengan Unigram dan Bigram. Untuk mengatasi ketidakseimbangan kelas pada dataset, diterapkan teknik SMOTE. Data ulasan yang digunakan diambil dari Google Maps selama satu tahun terakhir. Hasil penelitian menunjukkan bahwa SVM dengan kernel linear memberikan performa terbaik dengan F1-score 92,3%, diikuti oleh Naive Bayes 83,7% dan Random Forest 81,9%. Unigram lebih efektif dibandingkan Bigram dalam ekstraksi fitur, dan SMOTE meningkatkan kinerja Naive Bayes pada dataset yang tidak seimbang, namun tidak berpengaruh signifikan pada SVM. Temuan ini memberikan rekomendasi untuk peningkatan layanan di Bandara Sultan Hasanuddin, seperti fasilitas kebersihan dan kenyamanan ruang tunggu.
BISINDO Sign Letters Recognition Through HOG Features and Bagging Decision Tree Indra, Dolly; Alwi, Erick Irawadi; Anwar, Faudiah; Prihandani, St. Nadya Kurnia
Jurnal Ilmiah Informatika Komputer Vol. 30 No. 3 (2025)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2025.v30i3.57

Abstract

Sign language is one of the primary means of communication for people with hearing disabilities. BISINDO (Indonesian sign language) communicates using hand movements, among other things. One solution to this problem is to use image processing to recognize BISINDO letters A-Z based on hand movements. This study aims to create a BISINDO letter recognition system based on image processing using several stages, namely, preprocessing such as converting RGB images to grayscale images, then improving image quality by adjusting image contrast and removing noise with a median filter, HOG (Histogram of Oriented Gradients) feature extraction, and Bagging Decision Tree classification. A total of 156 images were used in the dataset, consisting of 104 letter images for training data and 52 letter images for test data. The data will be processed in the system as training data, and the dataset will then be stored in ‘mat’ format. Based on the results of testing Classification using Bagging Decision Tree, which produced an average accuracy rate of 86.5%. Thus, this research is expected to contribute to the development of BISINDO character recognition technology based on digital image processing.
Co-Authors Abdul Rachman Manga’ Abdul Rauf Tuasikal Achmad Novanto Agung, Riski Dewa Ahmad Toni, Ahmad Alda, A. Nurul Aisya Aldri Frinaldi Amir, Nur Hikmah Andi Apryan Mallarangen andi Widya Mufila Gafar Anik Nur Handayani Anwar, Faudiah Ardhiansya Yusuf Arfan Zainuddin Armind Mauldi Kurniawan As'ad, Ihwana Astuti, Wistiani Damanhuri, Nor Salwa Daris, Mega Asfirawati Djamereng, Asdar Erick Irawadi Alwi Erick Irawadi Alwi Erick Irawadi Alwi, Erick Irawadi Erick, Erick Irawadi Alwi Fadly Achmad Farniwati Fattah Fathrurahman, Fauzy Fery Setyo Aji Firman Shantya Budi, Firman Shantya Fitriyani Umar Hadyan Mardhi Fadlillah Haerdiansyah Syahnur, Muhammad Harlinda Lahuddin Hayudin Hasnanda Maila Herdianti Darwis Herman Herman Hi. Talib, Juraiz Hidayat, Muh Wahyu Huzain Azis Ihwana As’ad Irawati Irawati Irawati Irawati Irja, Mulianty Cipta jabir, sitti rahmah Jufriadif Na`am, Jufriadif Juita Mandasari Julius Santony Kadri Rahmat Suat, Wahyu Kasman Kasman Lilis Nur Hayati lilis nurhayati Lisna Ariani Lukman Syafie Lutfi Budi Ilmawan Lutfi Budi Ilmawan, Lutfi Budi Manga, Abdul Rachman Mansyur, St. Hajrah Mardiyyah Hasnawi Muh Fadlan Risqullah Dwitama N Muh Yeyen Dwi Suherman Muh. Fachrisyam Muh. Ridwan Rahim Muhammad Al Mubarak Muhammad Arfah Asis Muhammad Farhan Hermansyah Mukarramah, Rifqatul Musdalifah Musdalifah Mustika, Mustika Octavia Novanto, Achmad Nur Hayati, Lilis Nurhalima Nurhalima Prihandani, St. Nadya Kurnia Purnawansyah Purnawansyah Rahma, Dewi Ernita Rahmat Suat, Wahyu Kadri Rahmayani, Nurul Ramadan, Syahril Ramdan Satra Ramdaniah Ramdaniah Rezky Anugrah Rifky Saputra Scania, Muhammad Rosa Andrie Asmara Salsa, Salsabila Aurelia Saputra Scania, Muhammad Rifky Satma, Satma St. Hajrah Mansyur Subhan Ardhiman Sugiarti, Sugiarti Sukur, Widianti Syahnur, Muh. Haerdiansyah Syahrul Mubarak Abdullah Tanaka Kazuaki Tasmil Tasmil Tasrif Hasanuddin Tasrif Hasanuddin Taufik, Muhammad Asrai Tenri Sa'nah Umar Mansyur Umar, Fitriyani Veithzal Rivai Zainal Wahyu Sakti Gunawan Irianto Wistiani Astuti Yuhandri Yuhandri, Yuhandri Yundari, Yundari Zahra, Andi Fathimatuz Zahra