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All Journal Jurnal Penelitian Ekonomi Manajemen dan Bisnis Madani: Multidisciplinary Scientific Journal Sahmiyya: Jurnal Ekonomi dan Bisnis Trending: Jurnal Manajemen dan Ekonomi JPNM : Jurnal Pustaka Nusantara Multidisiplin Socius: Social Sciences Research Journal Maslahah: Jurnal Manajemen dan Ekonomi Syariah Journal of Islamic Economics and Finance Jurnal Media Akademik (JMA) Equivalent : Journal of Economic, Accounting and Management JURNAL MULTIDISIPLIN ILMU AKADEMIK Jurnal Riset Multidisiplin Edukasi Ekonosfera: Jurnal Ekonomi, Akuntansi, Manajemen, Bisnis dan Teknik Global Jingji: Jurnal Ekonomi, Bisnis dan Manajemen Journal of Golden Generation Economic
Dwi Novaria Misidawati
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Physics Public Health Social Sciences Other

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ANALISIS SENTIMEN KOMENTAR TIKTOK DAN FORECASTING KEBERLANJUTAN PROGRAM MAKAN BERGIZI GRATIS PEMERINTAH DALAM PERSPEKTIF PUBLIC RELATIONS MENGGUNAKAN MODEL HYBRID Nirma Ayu Suryaningtyas; Selvalentina Rista Anggita; Devita Rizqi Maulida; Dwi Novaria Misidawati
Jurnal Media Akademik (JMA) Vol. 3 No. 12 (2025): JURNAL MEDIA AKADEMIK Edisi Desember
Publisher : PT. Media Akademik Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62281/xe74zg24

Abstract

Penelitian ini bertujuan untuk menganalisis sentimen publik terhadap Program Makan Bergizi Gratis Pemerintah melalui komentar TikTok serta memprediksi keberlanjutannya menggunakan model hybrid yang menggabungkan IndoBERTa dan Random Forest. Sebanyak 1.975 komentar dikumpulkan melalui proses scraping dan diolah menggunakan teknik Natural Language Processing (NLP), meliputi pembersihan teks, normalisasi, tokenisasi, stopword removal, dan stemming. Klasifikasi sentimen dilakukan dengan IndoBERTa, sedangkan peramalan tren dilakukan menggunakan Random Forest berbasis TF-IDF. Hasil penelitian menunjukkan bahwa sentimen negatif mendominasi percakapan publik, terutama terkait kesiapan implementasi, efektivitas, dan keberlanjutan program. Model menghasilkan akurasi 81,77% dengan performa kuat pada sentimen negatif, namun performa untuk sentimen positif masih rendah karena ketidakseimbangan data. Hasil forecasting 30 hari menunjukkan bahwa komentar tidak mendukung diprediksi tetap stabil dan lebih tinggi dibandingkan komentar mendukung, yang muncul secara fluktuatif. Temuan ini menegaskan pentingnya peningkatan strategi komunikasi publik, transparansi kebijakan, dan perbaikan pelaksanaan program guna meningkatkan kepercayaan masyarakat serta mendukung keberlanjutan program.
Analisis Tren Jumlah Kecamatan di Indonesia Berdasarkan Pembentukan Provinsi Baru Tahun 2024 Sifa Sabrina; Yuniar Zahra Wiyani; Dwi Novaria Misidawati
JPNM Jurnal Pustaka Nusantara Multidisiplin Vol. 3 No. 4 (2025): December : Jurnal Pustaka Nusantara Multidisiplin (ACCEPTED)
Publisher : SM Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59945/jpnm.v3i4.858

Abstract

Penelitian ini bertujuan untuk menganalisis tren jumlah kecamatan di Indonesia pascapembentukan provinsi baru pada tahun 2024 dengan menggunakan pendekatan kuantitatif deskriptif. Metode penelitian mencakup analisis statistik deskriptif terhadap jumlah kecamatan pada 38 provinsi serta penerapan algoritma K-Means clustering untuk mengidentifikasi pola pengelompokan antarwilayah. Data diperoleh dari publikasi resmi tahun 2024 dan diolah menggunakan perangkat Python melalui Google Colab. Hasil penelitian menunjukkan bahwa distribusi jumlah kecamatan antarprovinsi tidak merata dan cenderung menceng ke kanan akibat keberadaan provinsi yang memiliki jumlah kecamatan sangat besar, terutama Jawa Timur, Jawa Tengah, dan Jawa Barat. Nilai mean sebesar 191,61 dan standar deviasi sebesar 154,83 menegaskan adanya variasi yang tinggi antarwilayah. Analisis klaster menghasilkan tiga kelompok utama, yaitu provinsi dengan jumlah kecamatan ekstrem, provinsi dengan jumlah kecamatan rendah hingga sedang sebagai kelompok mayoritas, serta provinsi dengan jumlah kecamatan tinggi namun tidak ekstrem. Temuan ini mengindikasikan bahwa faktor geografis, demografis, dan historis berperan besar dalam menentukan kebutuhan subdivisi administratif. Secara keseluruhan, penelitian ini menegaskan bahwa pemekaran provinsi berdampak langsung pada struktur tata kelola administratif Indonesia dan penting untuk dipertimbangkan dalam perencanaan pelayanan publik pada masa mendatang.
Analisis Strategi Komunikasi Krisis PR Pertamina dalam Pemulihan Citra Berbasis Machine Learning Devi Mustika; Lintang Mayzha Safira; Damayanti; Dwi Novaria Misidawati
Jurnal Riset Multidisiplin Edukasi Vol. 2 No. 12 (2025): Jurnal Riset Multidisiplin Edukasi (Edisi Desember 2025)
Publisher : PT. Hasba Edukasi Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71282/jurmie.v2i12.1350

Abstract

This study analyzes Pertamina's public relations crisis communication strategy in responding to the issue of “fake fuel” that went viral on social media in 2025. The rapid spread of public complaints, allegations of fuel adulteration, and increasing criticism on platforms such as X and TikTok had a significant impact on the company's reputation, requiring a data-driven approach to crisis communication. Unlike previous studies, which generally relied on manual content reading, this study offers a new approach by integrating machine learning-based sentiment analysis to map public perceptions in a more structured manner. Data was collected by gathering 1,000 posts on the X platform and supplemented with monitoring data from Brand24. All texts were processed using Natural Language Processing (NLP) techniques and classified with a Support Vector Machine (SVM) algorithm verified through ten iterations of Monte Carlo Cross-Validation. This model produced an average accuracy of 0.559 and showed a strong dominance of negative sentiment in 603 posts. Analysis of public engagement on TikTok showed a variety of responses, ranging from support for fuel distribution activities to sharp criticism of service quality and operations at fuel filling stations.These findings indicate that Pertamina's crisis communication strategy has not been entirely successful in reducing negative public perception. Theoretically, this research contributes by integrating machine learning data into SCCT analysis, thereby providing a more accurate understanding of public responses. Practically, the results of this study are expected to help energy companies improve their crisis communication strategies to be more responsive and effective.
Peran Strategis Public Relations dalam Membangun Citra Perusahaan Modern Dewi, Anggun Fitriana; Dwi Novaria Misidawati
Journal of Golden Generation Economic Vol. 1 No. 2 (2025): Desember 2025 : Journal of Golden Generation Economic
Publisher : PT. Lembaga Penerbit Penelitian Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65244/jggeconomic.v1i2.147

Abstract

Penelitian ini bertujuan untuk menganalisis peran strategis Public Relations (PR) dalam membangun citra perusahaan modern melalui penerapan strategi komunikasi dan prinsip etika profesional. Metode yang digunakan adalah deskriptif kualitatif dengan pendekatan studi pustaka, yaitu dengan menelaah berbagai literatur yang relevan terkait fungsi PR, strategi komunikasi, etika komunikasi, serta tantangan yang dihadapi dalam konteks krisis dan perkembangan media digital. Hasil kajian menunjukkan bahwa PR memiliki fungsi penting tidak hanya sebagai penyampai informasi, tetapi juga sebagai penghubung strategis antara organisasi dan publik untuk membangun hubungan jangka panjang yang saling menguntungkan. Penerapan strategi komunikasi yang efektif, pemahaman terhadap kebutuhan publik, serta integrasi prinsip etika seperti transparansi, akurasi, dan perlindungan data pribadi menjadi faktor kunci dalam pembentukan citra positif perusahaan. Selain itu, tantangan seperti dinamika media digital, kecepatan arus informasi, dan potensi krisis menuntut PR untuk memiliki respons yang cepat, terukur, serta berlandaskan integritas. Penelitian ini memberikan kontribusi teoretis dan praktis bagi penguatan peran PR dalam menciptakan reputasi perusahaan yang berkelanjutan.
Public Relations (PR) Crisis in the AI Era: The Threat of Digital Fraud Using Synthetic Video and Voice Amalia Putri Setya Aryana; Nabil Surya Al Hakim; Dwi Novaria Misidawati
Madani: Jurnal Ilmiah Multidisiplin Vol 3, No 11 (2025): December 2025
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.17905717

Abstract

The development of artificial intelligence (AI) in generating videos and mimicking voices presents both opportunities and new threats within the modern communication ecosystem. The ability of technologies such as deepfakes and voice cloning to create highly realistic content has triggered an increase in digital fraud, misinformation, and public manipulation. This study employs a descriptive qualitative method to thoroughly illustrate these phenomena through literature review, case content analysis, and observations of digital fraud trends on social media. The findings indicate that deepfake and voice-cloning technologies not only disrupt interpersonal communication but also have significant impacts on the Public Relations (PR) profession, particularly concerning reputation, public trust, and crisis management. The analyzed fraud cases demonstrate how fabricated content can infiltrate institutions, manipulate individuals, and disrupt decision-making processes. This study highlights the need for communication authentication protocols, PR–cybersecurity collaboration, and public education as mitigation efforts against AI-based fraud threats.
Analisis Sentimen Pengaruh Operasi Zebra terhadap Citra Polri di Mata Masyarakat pada brand24: Studi Respons Publik dan Kepatuhan Berkendara Nabila Juannita Enas; Rina Tisna Nurasih; Dwi Novaria Misidawati
Socius: Jurnal Penelitian Ilmu-Ilmu Sosial Vol 3, No 5 (2025): December 2025
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.17901694

Abstract

This study discusses how the public responds to Operation Zebra and how this response affects the image of the Indonesian National Police (Polri). In this digital age, public opinion is often expressed through social media and online news, so this study uses Brand24 to monitor online conversations and public sentiment. Data was collected during the period of November–December 2025 using keywords related to Operation Zebra and traffic law enforcement activities. The results of the study show that Operation Zebra was a topic that was widely discussed by the public. Positive sentiment was more prevalent, especially among people who believed that this operation helped improve order and safety on the roads. However, negative sentiment still existed, usually related to experiences that were considered unfair or unclear procedures during raids. The majority of conversations originated from social media and news portals, indicating that public opinion is shaped by a combination of direct experiences and media coverage. Overall, the findings of this study show that Operation Zebra contributes significantly to the positive image of the Indonesian National Police, although public criticism still needs to be addressed. Monitoring digital sentiment in this manner can serve as a basis for evaluation for the Indonesian National Police in improving transparency, service, and public communication in the future.
Implementation of Data-Driven Decision Making in Public Relations Strategy: A Case Study on the Social Media Campaign of TikTok Shop E-Commerce Yusufi Noviati; Ayun Farichah Khoniaro; Khopsa Chanda Syaputri; Dwi Novaria Misidawati
Socius: Jurnal Penelitian Ilmu-Ilmu Sosial Vol 3, No 5 (2025): December 2025
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.17817971

Abstract

The implementation of Data-Driven Decision Making (DDDM) in Public Relations strategies for TikTok Shop campaigns transforms communication practices from intuition-based approaches to evidence-based strategies. This study highlights four integrated stages: audience mapping using demographic and behavioral data, content formulation based on historical insights, real-time optimization driven by audience responses, and measurable evaluation linking communication performance to business goals. This approach enables more targeted, personalized, and effective communication, while strengthening the strategic role of PR within the competitive TikTok Shop e-commerce ecosystem.
Co-Authors Abdul Muhyi Ahmad Zaeni Ismail Ajeng Nisa Alfico Agra Rashya Valentino Alifia Salsabila Amalia Putri Setya Aryana Amirul Fatihin, Amirul Ariyanti, Yulia Dewi Arsen Adhita Sendi Aurahman, Sifa Ayun Farichah Khoniaro Azzahra Lailatun Nahdi Baqiyatus Sholikhah Bella Dwi Saputri Damayanti Devi Mustika Devita Rizqi Maulida Dewi, Anggun Fitriana Dina Nazilatul Hidayah Dinda Safira Dwi Sinta Amalia Estu Pramudita Hasan , Hasan Karina Oktaviani Karomatul Izzah Khopsa Chanda Syaputri Lindi Sestia Farba Lintang Mayzha Safira M. Khotim Maheswari Pasa Putri Syamsudar Muhammad Rif’an Muhammad Syahril Romadhan Nabil Surya Al Hakim Nabila Juannita Enas Najwa Azmi Nanda Tribramantya Purnama Nayaka Khansa Ariella Nirma Ayu Suryaningtyas Nur Shihatus Sakinah Nur Zalfa Rifqo Nabila Ratna Firdiyana Rina Tisna Nurasih Riska Naila Zulfa Sariyah Hafsoh Selvalentina Rista Anggita Sifa Sabrina Syifa Rohmah Veranda Ardiyan Putra Pratama vika agustina, prafasta Vina Rizqoeni Wafi Najmi Naufal Athallah Wafik Rofilah Wildan Kharisma Jati Yuniar Zahra Wiyani Yusufi Noviati Zidan Reffa Pratama