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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknologi Informasi dan Ilmu Komputer SMATIKA Journal of Applied Engineering and Technological Science (JAETS)
Tri Afirianto
Universitas Brawijaya
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Improving Sentiment Analysis of Short Informal Indonesian Product Reviews using Synonym Based Feature Expansion M. Ali Fauzi; Ro'i Fahreza Nur Firmansyah; Tri Afirianto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.7751

Abstract

Sentiment analysis in short informal texts like product reviews is more challenging. Short texts are sparse, noisy, and lack of context information. Traditional text classification methods may not be suitable for analyzing sentiment of short texts given all those difficulties. A common approach to overcome these problems is to enrich the original texts with additional semantics to make it appear like a large document of text. Then, traditional classification methods can be applied to it. In this study, we developed an automatic sentiment analysis system of short informal Indonesian texts using Naïve Bayes and Synonym Based Feature Expansion. The system consists of three main stages, preprocessing and normalization, features expansion and classification. After preprocessing and normalization, we utilize Kateglo to find some synonyms of every words in original texts and append them. Finally, the text is classified using Naïve Bayes. The experiment shows that the proposed method can improve the performance of sentiment analysis of short informal Indonesian product reviews. The best sentiment classification performance using proposed feature expansion is obtained by accuracy of 98%.The experiment also show that feature expansion will give higher improvement in small number of training data than in the large number of them.
Perbandingan System Functionality, System Interactivity, dan Usability pada Instant Messaging (IM) sebagai Media Pembelajaran Sinkron Faizatul Amalia; Admaja Dwi Herlambang; Tri Afirianto
SMATIKA JURNAL Vol 6 No 02 (2016): Smatika Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1599.351 KB) | DOI: 10.32664/smatika.v6i02.42

Abstract

Kurikulum yang diterapkan di Indonesia saat ini telah mengubah paradigma pembelajaran konvensional yang sudah dilaksanakan selama ini. Pembelajaran yang semula bersifat terisolasi berubah menjadi pembelajaran yang bersifat jejaring. Pembelajaran yang bersifat jejaring juga telah mengalami evolusi dari yang semula bersifat asinkron menjadi bersifat sinkron. Pembelajaran sinkron adalah pembelajaran dimana dosen dan mahasiswa bisa berinteraksi pada waktu yang sama melalui perangkat teknologi informasi. Instant Messaging (IM) merupakan salah satu media yang digunakan untuk menyelenggarakan proses pembelajaran sinkron. Hasil observasi menunjukkan bahwa IM yang sering dipakai oleh mahasiswa adalah Whatsapp, Line, dan BlackBerry Messenger (BBM). Hasil penelitian menunjukkan: (1) IM yang memiliki nilai System functionality tertinggi adalah Whatsapp; (2) IM yang memiliki nilai System interactivity tertinggi adalah Whatsapp; dan (3) IM yang memiliki nilai Usability tertinggi adalah Whatsapp
Pengembangan Sistem Informasi Praktik Kerja Lapangan (PKL) Siswa Berbasis Website Menggunakan Metode Extreme Programming (Studi Kasus: SMK Negeri 1 Sumenep) M. Ro'if; Tri Afirianto; Satrio Hadi Wijoyo
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 1: Februari 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20241116452

Abstract

Dalam pelaksanaannya, kegiatan Praktik Kerja Lapangan (PKL) di SMK Negeri 1 Sumenep masih kurang efektif karena dalam pelaksanaannya masih dilaksanakan secara manual, sehingga proses manajemen kegiatan PKL masih kurang efektif. Berdasarkan permasalahan tersebut, implementasi suatu sistem dibutuhkan untuk mengelola kebutuhan PKL sehingga kegiatan PKL dapat terlaksana secara efektif dan efisien. Peneliti melakukan pengembangan sistem informasi PKL berbasis website di SMK Negeri 1 Sumenep. Peneliti menggunakan metode pengembangan Extreme Programming (XP) dengan harapan sistem dapat dikembangkan dengan cepat dan agile sehingga semua kebutuhan yang diinginkan oleh stakeholder dapat tercapai. Hasil pengujian unit testing secara keseluruhan menghasilkan total 45 tests case dan 119 assertions, dan untuk pengujian acceptance testing menghasilkan total 69 tests case dengan nilai 100% accepted. Hasil pengujian system usability scale (SUS) keseluruhan sistem memiliki nilai rata-rata 76,88 yang berada dalam range 70 – 80 dengan nilai “C” atau “Good”. Sehingga dapat disimpulkan bahwa sistem informasi PKL berbasis website berada dalam acceptability range “acceptable”.
Naive Bayes Analysis for Nutritional Fulfillment Prediction in Children Satrio Agung Wicaksono; Satrio Hadi Wijoyo; Fatmawati Fatmawati; Tri Afirianto; Diva Kurnianingtyas; Mochammad Chandra Saputra
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 2 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i2.6105

Abstract

Stunting in children remains a significant global health challenge, particularly in low- and middle-income countries. Addressing this issue requires an effective approach to predicting and preventing inadequate nutritional fulfillment. This study uses the Naïve Bayes approach to forecast nutritional needs for children's growth and development, providing practical information for stunting prevention efforts. The data used were sourced from 174 infant and toddler examinations at the Puskesmas Lawang, involving eight key attributes: gender, age, weight, height, head circumference, pre-screening, vision tests, and nutritional status. Key performance metrics were evaluated to validate the model's predictive capabilities, including accuracy, precision, recall, and F1-score. Six test scenarios were conducted using different percentages of training data (90%, 80%, 70%, 60%, 50%, and 40%) to evaluate the reliability of the Naïve Bayes method. Results indicated that the highest accuracy of 78.84% was achieved in the sixth test scenario. The third test scenario produced the highest precision at 97.5%, while the highest recall (100%) was observed in the first three scenarios. The highest F-measure of 90.3% occurred in the fourth scenario. These results suggest the algorithm's potential for early detection to decrease the number of stunting children. The study’s implications are twofold: practically, the model can be integrated into health monitoring systems to assist healthcare professionals and policymakers in designing more effective nutrition programs; theoretically, it highlights the adaptability of Naive Bayes for handling complex, multi-dimensional health data.
Co-Authors Admaja Dwi Herlambang Diva Kurnianingtyas Faizatul Amalia Fatmawati Fatmawati M. Ali Fauzi M. Ro'if Mochammad Chandra Saputra Ro'i Fahreza Nur Firmansyah Satrio Agung Wicaksono Satrio Hadi Wijoyo