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ORGANIZATIONAL COMMUNICATION IN SHAPING THE IDENTITY OF FEMALE CADRES BASED ON KOHATI VALUES Jihan Aqilah Zahra; Muhammad Rafiq Daulay; Nurlailan Maghfiroh Silalahi; Putri Nur Hidayah; Feni Khairifa
OPINI: Journal of Communication and Social Science Vol. 2 No. 3 (2025): OPINI: Journal of Communication and Social Science
Publisher : Academic Solution Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70489/zxewa260

Abstract

This study examines the role of organizational communication in shaping the identity of female cadres within Kohati HMI Medan Branch, grounded in the value of #KohatiBerprinsip. Utilizing interviews with cadres at both branch and commissariat levels, the findings show that organizational communication operates through three main channels: structural communication, cultural communication, and digital communication. These interconnected channels form an ecosystem that facilitates the internalization of Islamic, intellectual, and women-oriented values. The value of #KohatiBerprinsip functions not merely as a slogan but as an identity framework embedded through formal training curricula, leadership communication practices, and narrative-based interactions in informal forums. The study also highlights several challenges, including uneven information flow, variations in value interpretation, and digital information fatigue. Overall, organizational communication in Kohati plays a strategic role in strengthening the identity of female cadres as principled, empowered Muslim women prepared to engage in public spaces. However, stronger internal communication design and more consistent value-based narratives are required to optimize identity formation processes.
Automatic Summarization of Court Decision Documents over Narcotic Cases Using BERT Wicaksono, Galih Wasis; Al asqalani, Sheila Fitria; Azhar, Yufis; Hidayah, Nur Putri; Andreawana, Andreawana
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1811

Abstract

Reviewing court decision documents for references in handling similar cases can be time-consuming. From this perspective, we need a system that can allow the summarization of court decision documents to enable adequate information extraction. This study used 50 court decision documents taken from the official website of the Supreme Court of the Republic of Indonesia, with the cases raised being Narcotics and Psychotropics. The court decision document dataset was divided into two types, court decision documents with the identity of the defendant and court decision documents without the defendant's identity. We used BERT specific to the IndoBERT model to summarize the court decision documents. This study uses four types of IndoBert models: IndoBERT-Base-Phase 1, IndoBERT-Lite-Bas-Phase 1, IndoBERT-Large-Phase 1, and IndoBERT-Lite-Large-Phase 1. This study also uses three types of ratios and ROUGE-N in summarizing court decision documents consisting of ratios of 20%, 30%, and 40% ratios, as well as ROUGE1, ROUGE2, and ROUGE3. The results have found that IndoBERT pre-trained model had a better performance in summarizing court decision documents with or without the defendant's identity with a 40% summarizing ratio. The highest ROUGE score produced by IndoBERT was found in the INDOBERT-LITE-BASE PHASE 1 model with a ROUGE value of 1.00 for documents with the defendant's identity and 0.970 for documents without the defendant's identity at a ratio of 40% in R-1. For future research, it is expected to be able to use other types of Bert models such as IndoBERT Phase-2, LegalBert, etc.
Text Summarization on Verdicts of Industrial Relations Disputes Using the Cross-Latent Semantic Analysis and Long Short-Term Memory Wicaksono, Galih Wasis; Hakim, Muhammad Nafi Maula; Hayatin, Nur; Hidayah, Nur Putri; Sari, Tiara Intana
JOIV : International Journal on Informatics Visualization Vol 7, No 3 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3.2052

Abstract

The information presented in the documents regarding industrial relations disputes constitutes four legal disputes. However, too much information leads to difficulty for readers to find essential points highlighted in industrial relations dispute documents. This research aims to summarize automated documents of court decisions over industrial relations disputes with permanent legal force. This research involved 35 documents of court decisions obtained from Indonesia’s official Supreme Court website and employed an extractive summarization approach to summarize the documents by utilizing Cross Latent Semantic Analysis (CLSA) and Long Short-Term Memory (LSTM) methods. The two methods are compared to obtain the best results CLSA was employed to analyze the connection between phrases, requiring the ordering of related words before they were converted into a complete summary. Then, the use of LSTM is combined with the Attention module to decoder and encoder the information entered so that it becomes a form that can be understood by the system and provides a variety of splitting of documents to be trained and tested to see the highest performance that the system can generate. The research has found out that the CLSA method gave a precision of 79.1%, recall score of 39.7%, and ROUGE-1 score of 50.9%, and the use of LSTM was able to improve the performance of the CLSA method with the results obtained 93.6%, recall score of 94.5 %, and ROUGE-1 score of 93.9% on the variation of splitting 95% training and 5% testing.
English English Anwar, Muhammad Hariz Faizul; Anhari, Nizam Avif; Wicaksono, Galih Wasis; Hidayah, Nur Putri
JUITA: Jurnal Informatika JUITA Vol. 14 Issue 1, March 2026
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

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

Abstract

This paper presents Legal-Case LLM, an open-source, fine-tuned language model tailored for Indonesian human-trafficking jurisprudence. General-purpose large language models exhibit high fluency but risk factual hallucination and limited jurisprudential fidelity when applied to legal texts. The objective is to develop a reproducible model that improves factual recall, legal terminology use, and jurisprudential alignment for Indonesian trafficking cases. Methods: We assembled a curated corpus of 400 court decisions from the Direktori Putusan Mahkamah Agung, extracted structured metadata and summaries, and generated question–answer pairs via large models followed by multi-stage cleaning and expert validation. We fine-tuned open models from the LLaMA family variants using parameter-efficient techniques (LoRA), evaluated with automatic metrics (ROUGE, BLEU, BERTScore, BARTScore), and a focused qualitative audit. Results: The fine-tuned model demonstrates marked improvements in content recall and semantic alignment versus zero-shot baselines, produces more jurisprudentially aligned phrasing (accurate use of terms such as amar putusan, Majelis Hakim, and percobaan), and reduces hallucination propensity in statute-related outputs. Conclusion and impact: Legal-Case LLM offers a reproducible, transparent tool to assist legal practitioners and researchers in Indonesia, while emphasising human-in-the-loop verification and citation-matching to ensure legal reliability and ethical deployment.
Co-Authors Abdul Kadir Abdul Kadir Jaelani Ahmad Dzaki Abidin Ahmad Faiz, Ahmad Ahmad Siboy Al asqalani, Sheila Fitria Al Sakinata, Annisa' Al-Fatih, Solahudin Aldi Malik Farhad AlFawwaz, Nauval Amanda Shifa Burhanuddinnisa Amiludin, Amiludin Andesti, Kiki Andreawana, Andreawana Anggraini, Putri Cahyaning Anhari, Nizam Avif Anwar, Muhammad Hariz Faizul Arcelia, Allysa Sonia Arifpadilah, Pajri Arsyi Manggali Arya Putra Arsyi Manggali Arya Putra Bayu Dwi Widdy Jatmiko Cholidah, - Christian Sri kusuma Aditya, Christian Sri kusuma Dandi Sanjaya David Pradhan Deni Alamsah Feni Khairifa Firjatullah, Muhamad Sulthan Fitria Esfandiari Hakim, Muhammad Nafi Maula HARIYANTO HARIYANTO Inda Rahadiyan, Inda Intana Sari, Tiara Isdian Anggraeny Jihan Aqilah Zahra Karina Ghea Silvana Komariah Komariah Komariah Komariah Komariah Komariah Komariah Komariah Maharani Zalianty Mohammad Isrok Muafika, Siti Nurmala Lailatul Muhammad Bahrul Ulum Muhammad Rafiq Daulay Noor Prasetyo, Said Novilia Safitri Dewik Nur Fauzia Asmi Nur Hayatin Nur Islamiyah Puspasari Nur Oktaviana, Ulfah Nurlailan Maghfiroh Silalahi Nurpratama, Widya Lestari Ordelia Julayta Syahidah Perdana, Muhammad Ilham Putra, Arsyi Manggali Arya Quincy R. Cloet Ratri Novita Erdianti Saleha, Meisya Maulidina Samira Echaib Sari, Tiara Intana Sholahuddin Al-Fatih Sinta Amipatul Aisiyah Siregar, Santy Anjelyna Br. Siti Kunarti Torri Justiansyah Utami Putri Kinayungan Virga Dwi Efendi Wasis Wasis Wicaksono, Galih Wasis Yuda Munarko Yufis Azhar Yunus, Nur Rohim