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All Journal Jurnal Informatika dan Teknik Elektro Terapan Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Pilar Nusa Mandiri Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Informatik : Jurnal Ilmu Komputer INTI Nusa Mandiri REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Infortech Jurnal AbdiMas Nusa Mandiri Paradigma Journal of Artificial Intelligence and Digital Business Jurnal Aruna Mengabdi (ARMI) Informatics and Software Engineering (ISE) Jurnal Ilmiah Sistem Informasi
Rani Irma Handayani, Rani Irma
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Public Health Social Sciences Other

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KOMPARASI METODE SVM DAN BILSTM PADA KLASIFIKASI SENTIMEN APLIKASI PLAY STORE DENGAN TEKNIK HYBRID IMBALANCE HANDLING Ariffadillah, Daryl; Rakha Rajendra Putra Candrasa; Sonu Mutiara Rahma; Pratiwi, Risca Lusiana; Handayani, Rani Irma
Jurnal Informatika dan Teknik Elektro Terapan Vol. 14 No. 1 (2026)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v14i1.8313

Abstract

Penelitian ini melakukan perbandingan kinerja model klasifikasi sentimen pada ulasan aplikasi Google Play Store, dengan fokus utama mengatasi tantangan ketidakseimbangan data. Masalah inti yang ditangani adalah distribusi data yang sangat miring (rasio Positif vs. Negatif ratio≈6:1). Metodologi yang digunakan menerapkan pendekatan komparatif hybrid, yang mengadu Support Vector Machine (SVM) dengan SMOTE (oversampling) melawan Bi-directional LSTM (BiLSTM) dengan Undersampling. Sebanyak 12.973 ulasan valid digunakan untuk pemodelan. Hasil evaluasi menunjukkan bahwa model BiLSTM + Undersampling memberikan kinerja keseluruhan yang superior, mencapai Akurasi 0.8882 dan F1-Score Weighted Avg 0.8940. Kinerja superior ini divalidasi lebih lanjut oleh F1-Score untuk kelas Negatif sebesar 0.6596 (lebih tinggi dari SVM), menunjukkan bahwa BiLSTM lebih efektif dalam mencapai akurasi klasifikasi yang seimbang untuk kelas minoritas. Studi ini menegaskan kemanjuran arsitektur deep learning yang stabil (BiLSTM) dikombinasikan dengan strategi sampling yang efisien (Undersampling) untuk data tekstual yang sangat tidak seimbang.
Comparison of SAW and Topsis Methods in The Selection of The Best Online Bike Shops Jannah, Pri Camelia Marissa; Handayani, Rani Irma; Cahyani, F. Lia Dwi
Paradigma - Jurnal Komputer dan Informatika Vol. 25 No. 1 (2023): March 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i1.1314

Abstract

The need for information technology in this pandemic era is greatly increasing. Many people meet their needs by doing buying and selling transactions as if they were online. Through a decision support system using the SAW (Simple Additive Weighting) and TOPSIS (Technique for Others Reference by Similarity to Ideal Solution), methods can provide the best decision in choosing the best online bicycle store site. On the result of the calculation, it is obtained that the results of the two are appropriate. The SAW and TOPSIS methods produced the same ranking, namely the Rodalink site got the highest ranking with a value of 1.019 on the SAW method of 0.833 on the TOPSIS method followed by serbasepeda, united, and cycles. The results of comparing calculations using these 2 methods are considered the SAW method is the most relevant method.
Co-Authors A Halim Alfianzah, Reza Anggraeni, Cinthya Pramudita Aprilia, Sarah Ari Puspita Ariffadillah, Daryl Astuti, Dyah Ayu Cahyani, Cindy Naulina Cahyani, F. Lia Dwi Cahyanti, F. Lia Dwi Dewi, Eva Zuliana Dewi, Ratna Kusuma Dinar Ajeng Kristiyanti Dinar Ajeng Kristiyanti, Dinar Ajeng Euis Widanengsih Fani, Priti Fitri Ratna Sari Fitriani, Arina Fransisca, May Frieyadie Frisma Handayanna Gathot Pujo Sanyoto, Gathot Pujo Handayani, Aryani Dwi Hernando, Alvin Hidayanti, Putri Eka Jannah, Pri Camelia Marissa Kristiana, Titin Lau, Melania Velisita Listyaningrum, Heni Munawaroh, Enggar Tyastiwi Murniyati, Murniyati Muzakir, Ahmad Normah Normah, Normah Pambudi, Sabtoadhy Bagus Parhan, Aldiansah Pratiwi, Risca Lusiana Putri, Melia Rakha Rajendra Putra Candrasa Rifai , Bakhtiar Rizki Darmawan Salbinda, Virandha Setiaji Setiaji, Setiaji Sonu Mutiara Rahma Stevanus, Rafhael Triningsih Triningsih Tuti Haryanti, Tuti Widodo, Miyosagusti Yudo Wironoto, Deni Yut, Immanuel Vico