Article Per Year (5 Year)
p-Index From 2021 - 2026
0.562
P-Index
This Author published in this journals
All Journal Darma Diksani: Jurnal Pengabdian Ilmu Pendidikan, Sosial, dan Humaniora Lingua Technica: Journal of Digital Literary Studies Lingua Technica: Journal of Digital Literary Studies
Rinda Widya Ikomah
University of Mataram
Arts Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Social Sciences Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Pelatihan Dasar Produksi Film pada Komunitas Seni di Kota Mataram: Training Program in Basic Film Production for Art Communities in Mataram City Muh. Khairussibyan; Mari’i Mari’i; Baiq Wahidah; Rinda Widya Ikomah
DARMADIKSANI Vol 6 No 1 (2026): Edisi Maret
Publisher : Jurusan Pendidikan Bahasa dan Seni, FKIP, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/darmadiksani.v6i1.8237

Abstract

Produksi film memainkan peran penting dalam memberdayakan sineas lokal dengan meningkatkan keterampilan teknis, mendorong kreativitas, serta mendukung pengembangan industri film yang berkelanjutan. Dalam konteks ini, Pemerintah Kota Mataram menyelenggarakan Festival Film Sangkareang sebagai upaya untuk meningkatkan kualitas produksi film lokal. Namun, hasil kompetisi menunjukkan bahwa kreativitas sineas lokal belum berkembang secara signifikan. Untuk mengatasi hal tersebut, dilaksanakan pelatihan dasar produksi film yang komprehensif dengan mengintegrasikan aspek teoretis dan praktis, seperti pengoperasian kamera dan penyuntingan video, dengan menghadirkan narasumber dari kalangan akademisi dan praktisi. Pelatihan ini menunjukkan dampak positif terhadap motivasi dan perkembangan kreativitas peserta. Hasil evaluasi pascapelatihan menunjukkan bahwa 94,1% peserta tertarik untuk lebih aktif dalam menulis karya sastra, termasuk penulisan naskah, sementara 5,9% tidak tertarik. Selain itu, 88,2% peserta melaporkan bahwa mereka mampu menghasilkan ide untuk pengembangan naskah, sedangkan 11,8% tidak. Program ini juga mencakup pelatihan aplikatif keterampilan tata rias teater dan film, yang menggabungkan penyampaian materi teoretis oleh akademisi dan demonstrasi praktis oleh praktisi yang berbagi pengalaman nyata dalam proses produksi. Peserta menyatakan bahwa pelatihan ini bermanfaat dan meningkatkan pengetahuan mereka. Selain itu, pelatihan ini membantu mereka mengidentifikasi dan mengembangkan isu-isu sosial budaya menjadi narasi film yang potensial. Temuan ini menunjukkan adanya kebutuhan yang kuat akan pelatihan lanjutan untuk lebih meningkatkan kompetensi perfilman. Oleh karena itu, pelatihan yang berkelanjutan dan berorientasi pada praktik direkomendasikan guna memperkuat keterampilan peserta serta mendukung pengembangan industri film lokal yang berkelanjutan.
Text mining and semantic modeling of literary corpora: a machine learning–based study of Indonesian fiction Rinda Widya Ikomah; Zohaib Hassan Sain
Lingua Technica: Journal of Digital Literary Studies Vol. 2 No. 1 (2026): Literature and computation: Mapping, modeling, and mediation
Publisher : Asosiasi Relawan dan Pengelola Jurnal LPTNU (ARJUNU)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64595/lingtech.v2i1.133

Abstract

Background: The large-scale digitization of Indonesian literary works has produced extensive textual corpora that challenge conventional close-reading approaches and call for systematic, data-driven methods capable of capturing thematic, semantic, and affective patterns in fiction. Objective: This study aims to examine how text mining and semantic modeling can reveal lexical salience, intertextual relations, and narrative emotion in Indonesian fiction across different thematic orientations. Method: Using a quantitative corpus-based design, the study analyzes 36 Indonesian literary texts published between 1980 and 2022 through TF–IDF–based lexical analysis, document-level semantic embeddings with cosine similarity and clustering, and sentence-level sentiment analysis. Results: The findings show distinct lexical signatures that differentiate thematic clusters, coherent semantic groupings reflecting intertextual proximity, and sentiment trajectories dominated by neutral-to-negative polarity with strategically placed affective peaks across narrative progression. Implication: These results demonstrate that computational methods can empirically support literary analysis without displacing interpretive criticism. Novelty: The study integrates lexical, semantic, and affective modeling within a unified framework for Indonesian fiction, offering a scalable and replicable approach to digital literary studies.
Text mining and semantic modeling of literary corpora: a machine learning–based study of Indonesian fiction Rinda Widya Ikomah; Zohaib Hassan Sain
Lingua Technica: Journal of Digital Literary Studies Vol. 2 No. 1 (2026): Literature and computation: Mapping, modeling, and mediation
Publisher : Asosiasi Relawan dan Pengelola Jurnal LPTNU (ARJUNU)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64595/lingtech.v2i1.133

Abstract

Background: The large-scale digitization of Indonesian literary works has produced extensive textual corpora that challenge conventional close-reading approaches and call for systematic, data-driven methods capable of capturing thematic, semantic, and affective patterns in fiction. Objective: This study aims to examine how text mining and semantic modeling can reveal lexical salience, intertextual relations, and narrative emotion in Indonesian fiction across different thematic orientations. Method: Using a quantitative corpus-based design, the study analyzes 36 Indonesian literary texts published between 1980 and 2022 through TF–IDF–based lexical analysis, document-level semantic embeddings with cosine similarity and clustering, and sentence-level sentiment analysis. Results: The findings show distinct lexical signatures that differentiate thematic clusters, coherent semantic groupings reflecting intertextual proximity, and sentiment trajectories dominated by neutral-to-negative polarity with strategically placed affective peaks across narrative progression. Implication: These results demonstrate that computational methods can empirically support literary analysis without displacing interpretive criticism. Novelty: The study integrates lexical, semantic, and affective modeling within a unified framework for Indonesian fiction, offering a scalable and replicable approach to digital literary studies.
Co-Authors Baiq Wahidah Mari’i Mari’i Muh. Khairussibyan Zohaib Hassan Sain