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All Journal Indonesian Journal of Information Technology and Computing (IMAGING) STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer
Widya Novita Al Afifah Irwanto
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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ANALISIS SENTIMEN NEGATIVE PADA APLIKASI JOBSTREET MENGGUNAKAN HADOOP DISTRIBUTED FILE SYSTEM (HDFS) Basiroh, Basiroh; Widya Novita Al Afifah Irwanto
STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Vol. 4 No. 4 (2025): November
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/storage.v4i4.6338

Abstract

Pertumbuhan pesat teknologi informasi telah memudahkan masyarakat dalam mengakses layanan perekrutan kerja melalui platform digital seperti JobStreet. Namun, tingginya interaksi pengguna juga memunculkan berbagai ulasan, termasuk sentimen negatif yang dapat memengaruhi citra perusahaan. Oleh karena itu, analisis sentimen menjadi penting untuk mengidentifikasi opini negatif secara otomatis. Penelitian ini bertujuan untuk menganalisis sentimen negatif pada ulasan pengguna aplikasi JobStreet dengan memanfaatkan Hadoop Distributed File System (HDFS) sebagai media penyimpanan data berskala besar, serta membandingkan kinerja metode Naive Bayes dan Support Vector Machine (SVM). Tahapan penelitian meliputi pengumpulan data ulasan pengguna, pra-pemrosesan teks (pembersihan, tokenisasi, stopword removal, dan stemming), pembobotan menggunakan TF-IDF, serta klasifikasi dengan metode Naive Bayes dan SVM. Evaluasi kinerja dilakukan berdasarkan metrik akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa kedua algoritma mampu mengklasifikasikan sentimen negatif dengan baik, namun SVM memberikan kinerja lebih unggul dibandingkan Naive Bayes. SVM memperoleh akurasi 86%, recall 0,84%, dan F1-score 0,85%, sedangkan Naive Bayes mencatat akurasi 80%, recall 0,76%, dan F1-score 0,79%. Hal ini menunjukkan bahwa pemilihan algoritma berpengaruh terhadap kualitas analisis sentimen
Implementasi Algoritma AHP Sebagai Sistem Penunjang Keputusan dalam Mengevaluasi Kelayakan Rehabilitasi Rumah Warga Berpenghasilan Rendah Basiroh Basiroh; Widya Novita Al Afifah Irwanto
Indonesian Journal of Information Technology and Computing (IMAGING) Vol 5, No 2 (2025): 31 Desember 2025
Publisher : Politeknik Harapan Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52187/img.v5i2.396

Abstract

The availability of decent housing is one of the important indicators in improving the quality of life of the community, especially for residents with low incomes. In practice, the process of determining the eligibility of recipients of housing rehabilitation assistance is often still done manually and subjectively, thus potentially causing inaccuracy and injustice in decision making. The initiative stems from the growing need for systematic and objective tools to support government and social institutions in identifying eligible households for housing rehabilitation programs. In addressing this need, the Analytical Hierarchy Process (AHP) method is employed as a core decision-making framework within the DSS due to its strength in handling complex decision problems involving multiple criteria. The system incorporates various assessment criteria, including household income, structural condition of the house, number of dependents, ownership status, and age of the building. These criteria are structured hierarchically, and their relative importance is determined through pairwise comparisons facilitated by AHP. By applying this method, the system is capable of producing a weighted score for each applicant, thus enabling decision-makers to prioritize assistance based on quantifiable and transparent factors. The research includes both qualitative and quantitative analysis, starting from needs assessment, system requirement analysis, and user interface design, to the implementation of the AHP algorithm within the DSS. Results from case studies and prototype testing demonstrate that the system improves the accuracy and fairness of housing rehabilitation assessments compared to conventional manual evaluations. Moreover, it offers a user-friendly interface for stakeholders with varying technical backgrounds. In conclusion, the integration of AHP in the proposed DSS provides a reliable and scalable solution to support equitable housing policy decisions. Future developments may include integration with GIS for location-based analysis and mobile accessibility for field surveys. 
Co-Authors Basiroh Basiroh