Bina Nusantara University, Indonesia
BibTex Citation Data :
@article{KIRYOKU87003, author = {Magdalena Putri Harsari and Utari Novella}, title = {Japanese Onomatopoeia in Komi-san wa Komyushou desu: Form, Sound, and Meaning}, journal = {KIRYOKU}, volume = {10}, number = {2}, year = {2026}, keywords = {Japanese Onomatopoeia; Formation; Sound; Meaning}, abstract = { Japanese is one of the languages rich in onomatopoeia, and each onomatopoeia can undergo through various formation process. This study analyzes the types, formation, and meaning process of Japanese onomatopoeia from the viewpoint of phonology and morphosemantic. Data is collected from the anime \"Komi-san wa Komyushou Desu\" Episodes 1-4, excluding the ones shown through conversational dialogues, using note-taking techniques and documentation. The research employs a qualitative approach with descriptive analysis. The analysis uses the theories such as Asano-Kindaichi (1978) and Tamori (1999) for classification of onomatopoeia types, Akimoto (2002) for onomatopoeia word forms, and Hamano's (1984) theory for meaning components. The study shows that giyougo (behavior/movement) as the most common type of onomatopoeia in the data. Various forms of onomatopoeia were found, with repetition (hanpukukei) being the most prevalent. Each form of formation has a semantic function that gives additional meaning to the basic meaning of the onomatopoeia undergoing various changes. }, issn = {2581-0960}, pages = {641--654} doi = {10.14710/kiryoku.v10i2.641-654}, url = {https://ejournal.undip.ac.id/index.php/kiryoku/article/view/87003} }
Refworks Citation Data :
Japanese is one of the languages rich in onomatopoeia, and each onomatopoeia can undergo through various formation process. This study analyzes the types, formation, and meaning process of Japanese onomatopoeia from the viewpoint of phonology and morphosemantic. Data is collected from the anime "Komi-san wa Komyushou Desu" Episodes 1-4, excluding the ones shown through conversational dialogues, using note-taking techniques and documentation. The research employs a qualitative approach with descriptive analysis. The analysis uses the theories such as Asano-Kindaichi (1978) and Tamori (1999) for classification of onomatopoeia types, Akimoto (2002) for onomatopoeia word forms, and Hamano's (1984) theory for meaning components. The study shows that giyougo (behavior/movement) as the most common type of onomatopoeia in the data. Various forms of onomatopoeia were found, with repetition (hanpukukei) being the most prevalent. Each form of formation has a semantic function that gives additional meaning to the basic meaning of the onomatopoeia undergoing various changes.
Article Metrics:
Last update:
Last update: 2026-10-08 11:03:46
Copyright Notice
Starting from 2025, the author(s) whose article is published in the Kiryoku journal attain the copyright for their article and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. By submitting the manuscript to Kiryoku, the author(s) agree with this policy. No special document approval is required.
The author(s) guarantee that:
The author(s) retain all rights to the published work, such as the following rights:
Suppose the article was prepared jointly by more than one author. Each author submitting the manuscript warrants that all co-authors have given their permission to agree to copyright and license notices (agreements) on their behalf and notify co-authors of the terms of this policy. Kiryoku will not be held responsible for anything arising because of the writer's internal dispute. Kiryoku will only communicate with correspondence authors.
Authors should also understand that their articles (and any additional files, including data sets and analysis/computation data) will become publicly available once published. The license of published articles (and additional data) will be governed by a Creative Commons Attribution-ShareAlike 4.0 International License. Kiryoku allows users to copy, distribute, display and perform work under license. Users need to attribute the author(s) and Kiryoku to distribute works in journals and other publication media. Unless otherwise stated, the author(s) is a public entity as soon as the article is published.
Notes for Usage of Generative AI in Scientific Writing
For our policy on the use of Generative AI in scientific writing, please see our Editorial Policies page: https://ejournal.undip.ac.id/index.php/kiryoku/about/editorialPolicies#custom-5
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.