Article Per Year (5 Year)
p-Index From 2021 - 2026
2.127
P-Index
This Author published in this journals
All Journal CESS (Journal of Computer Engineering, System and Science) Sistemasi: Jurnal Sistem Informasi INTEGER: Journal of Information Technology Jurnal Pengabdian Masyarakat Multidisiplin Jurnal Pengabdian UNDIKMA Jurnal Minfo Polgan (JMP) Prosiding Seminar Nasional Universitas Ma Chung Nusantara Journal of Computers and its Applications Jurnal Pengabdian Kepada Masyarakat SWAGATI: Journal of Community Service Journal of Informatics and Vocational Education
Vit Zuraida
Politeknik Negeri Malang
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
AI Based Digital Book Indexing System Using YAKE and WORD2VEC Methods Mohammad Alfarizi Abdullah; Ulla Delfana Rosiani; Vit Zuraida; Arhan Windu Rizki Putra Budianto; Rizki Putri Ramadhani
Journal of Informatics and Vocational Education Vol. 9 No. 1 (2026): Journal of Informatics and Vocational Education - March
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i1.3026

Abstract

Polinema Press, the publishing unit of the State Polytechnic of Malang (Polinema), requires an efficient solution for automatically generating book indexes. The current manual indexing process is time-consuming and inefficient. This research aims to develop an AI-based automatic indexing system utilizing the YAKE (Yet Another Keyword Extractor) and Word2Vec methods to improve the accuracy and efficiency of index generation. The system is designed to process digital books in PDF format through several stages: (1) text preprocessing (text extraction, stopword removal, tokenization), (2) keyword extraction using YAKE based on statistical features such as word frequency and position, (3) final keyword selection by measuring semantic similarity using Word2Vec, and (4) alphabetical index compilation along with page numbers where keywords appear. The indexing results are evaluated by comparing them with manual indexes using cosine similarity to measure the degree of similarity. This research has been tested on 37 digital books and resulted in the best configuration in the combination of YAKE and Word2Vec with phrases of 2-3 words, which obtained cosine similarity values of up to 0.91, precision of up to 0.38, and average processing time of less than 4 seconds per document. These results show that the system is able to produce relevant, fast, and contextual indexes when compared to manual indexes, and is expected to reduce the manual workload at Polinema Press and become a reference for the application of natural language processing (NLP) technology for Indonesian-language documents.
Automatic Indexing of Digital Books using RAKE and Word2Vec Arhan Windu Rizki Putra Budianto; Ulla Delfana Rosiani; Vit Zuraida; Rizki Putri Ramadhani; Mohammad Alfarizi Abdullah
Journal of Informatics and Vocational Education Vol. 9 No. 1 (2026): Journal of Informatics and Vocational Education - March
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i1.3050

Abstract

Manual indexing of digital books is time-consuming and prone to inconsistency. To address this, this study developed an automatic indexing system using RAKE (Rapid Automatic Keyword Extraction) method and Word2Vec. The system accepts PDF files as input, performs text preprocessing, and extracts key phrases using RAKE. These phrases are subsequently filtered based on semantic relevance to the specified topic using an Indonesian-language Word2Vec model. Users can manually add phrases and select relevant ones to be included in the final index. The resulting index includes phrases, page numbers, and relevance scores, which are inserted as an additional page at the end of the PDF document. Evaluation was conducted by comparing the system-generated index with the author’s manual index using precision, recall, and cosine similarity metrics. The results indicate that although precision and recall were very low, a cosine similarity score of 0.69 suggests a semantic similarity between the system output and the author’s index.
Optimalisasi Seleksi Siswa Teladan: Perpaduan AHP dan TOPSIS dalam Sistem Pendukung Keputusan M. Hasyim Ratsanjani; Fitri Mutiara Devi; Vit Zuraida; Septian Enggar Sukmana
Jurnal Minfo Polgan Vol. 13 No. 2 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i2.14241

Abstract

Program pemilihan siswa teladan di suatu sekolah umumnya memiliki tujuan untuk mencetak lulusan berprestasi dan memilih perwakilan siswa untuk mengikuti suatu kompetisi tingkat lokal maupun nasional. Akan tetapi seringkali pemilihan siswa teladan tersebut dihadapkan pada tantangan subjektivitas. Penilaian yang terlalu bergantung pada persepsi pribadi dan kurangnya kriteria yang dapat menghasilkan keputusan yang tidak adil dan akurat. Untuk mengatasi masalah ini, penelitian ini mengusulkan sebuah solusi inovatif berupa suatu sistem pendukung keputusan yang memanfaatkan data dan metode kuantitatif untuk membuat proses pemilihan menjadi lebih objektif dan transparan. Dengan menggunakan metode Analytic Hierarchy Process (AHP), sistem ini mampu menentukan bobot pentingnya setiap kriteria penilaian, seperti prestasi akademik, keaktifan, kedisiplinan, keberanian, serta perilaku. Kemudian, metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) digunakan untuk merangking siswa berdasarkan kriteria-kriteria tersebut. Dengan adanya sistem ini, diharapkan proses pemilihan siswa teladan di sekolah dapat menjadi lebih efisien, akurat, dan bebas dari bias personal. Selain itu, sistem ini juga dapat memberikan motivasi yang lebih besar bagi siswa untuk berprestasi di berbagai bidang. Hasil pengujian User Acceptance Test(UAT) menunjukkan bahwa sistem ini telah berhasil memenuhi harapan pengguna sebesar 87% dalam hal objektivitas . Hal ini berarti, keputusan yang dihasilkan oleh sistem lebih dapat diandalkan dan mencerminkan penilaian yang lebih adil.
IMPLEMENTASI APLIKASI BANTUAN SEBAGAI PEMAHAMAN PENGGUNA PADA WEB UKM SUYTEESTORE: IMPLEMENTATION BUILD APPLICATION USER GUIDE HELP FOR UNDERSTANDING USERS OF WEB UKM SUYTEESTORE Ariadi Retno Hayati; Habibie Ed; Wilda Imama Sabilla; Vit Zuraida; Candra Bella
Jurnal Pengabdian Masyarakat Multidisiplin Vol 8 No 1 (2024): Oktober
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/jpm.v8i1.5215

Abstract

This activity research implementation application with tools help for users implementation based web for UKM SuyteeStore in Malang. This application have content for understanding by user how to operate the application web for catalogue and order system where each content has explanation for each content as detailed in web based. Design in this application has simply design and easy understanding for users with HTML and PHP programming. The contents of help application in this application are information how to access web for the use of find products and detailed product as catalogue product, the use how to order in system, the use of how process after order in system, the information of UKM SuyteeStore and location and contact and the information in this application can help users to operate the web that building for catalogue and order system in application web based. This application is build as tool for user that link to web UKM SuyteeStore and help users to understand the contents in application web UKM SuyteeStore with different menus and content in this tools application as sub of the web in UKM SuyteeStore. This application is designed with the concept of theory for build application for users as help user guide that in the concept of build application user guide must be have fews contents that different with the application and the contents must be explanation the application contents as detail.
TEXT SIMILARITY PADA DOKUMEN PRODUK CERTIPORT DENGAN DOKUMEN PROFIL CALON KLIEN SERTIFIKASI Hilman Zahrawa Budiarto; Dika Rizky Yunianto; Vit Zuraida
Prosiding Seminar Nasional Universitas Ma Chung (Informatika & Sistem Informasi Bahasa dan Seni
Publisher : Ma Chung Press

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Proses profiling kebutuhan sertifikasi calon klien di Certiport Authorized Testing Center (CATC) JTI Polinema yang masih dilakukan secara manual rentan terhadap subjektivitas dan terkendala kesenjangan antara narasi kompetensi calon klien dengan terminologi teknis pada dokumen produk sertifikasi. Penelitian ini bertujuan merancang dan mengimplementasikan sistem rekomendasi sertifikasi otomatis berbasis hybrid text similarity untuk mengukur tingkat kecocokan antara dokumen Objective Domain sertifikasi Certiport dengan dokumen profil calon klien sertifikasi. Sistem dibangun menggunakan arsitektur komputasi hybrid yang mengintegrasikan TF-IDF pada dimensi numerik dan Sentence Transformers model all-MiniLM-L6-v2 pada dimensi semantik, disertai pipeline penerjemahan otomatis untuk menjembatani perbedaan bahasa antara profil calon klien berbahasa Indonesia dengan Objective Domain berbahasa Inggris. Pengujian dilakukan terhadap 16 dokumen profil calon klien sertifikasi dari tiga institusi yang merepresentasikan variasi kebutuhan kompetensi lintas domain. Evaluasi dilakukan menggunakan metrik Precision, Recall, Accuracy, dan F1-Score untuk mengukur kualitas rekomendasi yang dihasilkan sistem. Hasil pengujian menunjukkan performa optimal pada batas rekomendasi Top-20 dengan rasio pembobotan 40% numerik dan 60% semantik, menghasilkan rata-rata Precision sebesar 29,37%, Recall sebesar 40,20%, Accuracy sebesar 74,68%, dan F1-Score sebesar 29,85%. Ablation study membuktikan bahwa pendekatan hybrid meningkatkan F1-Score sebesar 48,9% dibandingkan TF-IDF Only. Pengujian penerimaan pengguna menghasilkan tingkat kelayakan sebesar 88,57%, yang termasuk dalam kategori sangat layak diimplementasikan. Hasil penelitian ini menunjukkan bahwa CertiMatch mampu membantu proses rekomendasi sertifikasi menjadi lebih cepat, konsisten, dan objektif sehingga dapat mendukung pengambilan keputusan dalam proses profiling kebutuhan sertifikasi calon klien.
Co-Authors Amelia Sahira Rahma Andhika Satrio Wiratama Arhan Windu Rizki Putra Budianto Ariadi Retno Hayati Ariadi Retno Tri Hayati Ririd Candra Bella Candra Bella Vista Chastine Fatichah Deddy kusbianto Deddy Kusbianto Purwoko Aji Diana Purwitasari Dika Rizky Yunianto Dimas Fanny Hebrasianto Permadi Eka Apriani, Meyti Elok Nur Hamdana Evi Suwarni, Evi Fitri Mutiara Devi Habibie Ed Habibie Ed Dien Habibie Ed Dien Hayati, Ariadi Retno Hilman Zahrawa Budiarto Kirana, Puspa M. Hasyim Ratsanjani M. Hasyim Ratsanjani Masitha Nisa Akmalia Mohammad Alfarizi Abdullah Mohammad Reza Pahlevi Pamenang, M. Unggul Pramudhita, Agung Nugroho Rahma, Amelia Sahira Rizki Putri Ramadhani Septian Enggar Sukmana Tiara estu amanda Ulla Delfana Rosiani Widi Dwi Ernawati Wilda Imama Sabilla