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All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal MediaTIK
Lorosae, Teguh Ansyor
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Computer Science & IT Decision Sciences, Operations Research & Management Education Social Sciences Other

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Perancangan Sistem Informasi Data Pelayanan Perpustakaan Berbasis Web Pada SMAN 2 Parepare Ramadhan, Sahrul; Arfianita, Arfianita; Khairunnisa, Khairunnisa; Lorosae, Teguh Ansyor; Fardan, Muhammad
Jurnal MediaTIK Volume 6 Issue 2, Mei (2023)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/mediatik.v6i2.1396

Abstract

Perpustakaan adalah institusi pengelola koleksi karya tulis, karya cetak, dan karya rekam secara profesional dengan sistem yang baku guna memenuhi kebutuhan pendidikan, penelitian, pelestarian, informasi, dan rekreasi para pemustaka. Perpustakaan di SMAN 2 Parepare belum memiliki sistem informasi data pelayanan yang mana data tersebut masih ditulis secara manual menggunakan kertas. Penulisan data perpustakaan melalui kertas bisa mengakibatkan data-data tersebut rusak atau hilang. Informasi bisa didapatkan melalui perpustakaan yang bisa membantu untuk mendapatkan informasi sebanyak mungkin seperti mengolah data, mengatur berbagai buku yang jumlahnya terus bertambah seiring berjalannya waktu. Untuk dapat melihat data-data buku yang dipinjam, siapa yang meminjam, berapa jumlah buku, dan lain sebagainya maka diperlukan sistem komputerisasi yang memudahkan untuk mencari informasi yang diinginkan dan membuat sistem informasi perpustakaan yang lebih sistematis. Metode yang digunakan pada penelitian ini menggunakan metode waterfall. Berdasarkan hasil penelitian yang dilakukan, dapat diambil kesimpulan bahwa sistem informasi perpustakaan yang dibuat dapat membantu admin dalam mengolah data dan user dalam mengakses website.
nalisis Sentimen Berbasis Aspek Ulasan Aplikasi Ruangguru Pada Platform Android dan iOS menggunakan BiLSTM Mutmainah, Siti; Citra, Erin Eka; Lorosae, Teguh Ansyor; Fathir, Fathir
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): Juli 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7475

Abstract

Analysis of user reviews can provide valuable insights for app developers in improving quality, but conventional sentiment analysis only categorizes sentiment in general terms. Aspect-based Sentiment Analysis (ABSA) is a method that can be used to extract specific opinions from various aspects of user reviews. This study compares ABSA on user reviews of Ruangguru app on Android and iOS platforms. Review data was collected from Google Play Store and Apple App Store, processed, and classified into sentiment polarity using deep learning models such as BiLSTM with Word2Vec. The analysis was conducted to find out the aspects talked about by users and the sentiment associated with each aspect. The evaluation results show that the BiLSTM model with Word2Vec features performs well on the sentiment analysis task achieving 84% accuracy. In the aspect extraction task, the model performs very well with accuracy, precision, recall, and F1 Score values of 97%. These results show that the combination of BiLSTM and Word2Vec is an effective approach in understanding user opinions and preferences from Ruangguru app review text data and has the potential to be applied in the development of automated opinion analysis systems. Price aspect extraction results are the most dominant topic discussed on both platforms, followed by features and materials. Positive sentiment towards the price aspect dominates, but there is also a significant proportion of negative sentiment, especially on the Android platform.
Co-Authors Arfianita, Arfianita Citra, Erin Eka Fardan, Muhammad Fathir Fathir Khairunnisa Khairunnisa Ramadhan, Sahrul Siti Mutmainah