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Optimalisasi Manajemen Sentimen di Media Sosial Universitas melalui Machine Learning dan AI: Studi Kasus pada Komentar Instagram
Get PDFPenelitian ini mengeksplorasi efektivitas penerapan manajemen sentimen di media sosial universitas, terutama dengan menggunakan algoritma Naive Bayes dan teknologi v (AI) GPT-40, dalam menganalisis komentar calon mahasiswa dan stakeholder di Instagram. Penelitian ini bertujuan untuk memahami pola sentimen audiens, yang diklasifikasikan menjadi positif, negatif, dan netral, serta mengidentifikasi gaya bahasa yang kompleks seperti ironi, sindiran, sarkasme, satire, dan metafora. Algoritma Naive Bayes digunakan untuk pengklasifikasian sentimen dasar, sedangkan AI GPT-40 berperan dalam menganalisis makna lebih dalam dari gaya bahasa yang tidak eksplisit, sehingga meningkatkan akurasi klasifikasi dan mengoptimalkan interpretasi sentimen. Business Intelligence (BI) digunakan untuk menyediakan visualisasi data dan mendukung pengambilan keputusan yang cepat. Temuan penelitian menunjukkan bahwa pendekatan yang memperhatikan konteks budaya dan linguistik menghasilkan pemahaman sentimen yang lebih akurat dan memberikan wawasan penting dalam strategi branding universitas. Kombinasi teknologi Machine learning dan AI dalam analisis sentimen memberikan kontribusi pada pengembangan model manajemen sentimen yang lebih responsif dan relevan dengan kebutuhan branding universitas di era digitalPenelitian ini mengeksplorasi efektivitas penerapan manajemen sentimen di media sosial universitas, terutama dengan menggunakan algoritma Naive Bayes dan teknologi v (AI) GPT-40, dalam menganalisis komentar calon mahasiswa dan stakeholder di Instagram. Penelitian ini bertujuan untuk memahami pola sentimen audiens, yang diklasifikasikan menjadi positif, negatif, dan netral, serta mengidentifikasi gaya bahasa yang kompleks seperti ironi, sindiran, sarkasme, satire, dan metafora. Algoritma Naive Bayes digunakan untuk pengklasifikasian sentimen dasar, sedangkan AI GPT-40 berperan dalam menganalisis makna lebih dalam dari gaya bahasa yang tidak eksplisit, sehingga meningkatkan akurasi klasifikasi dan mengoptimalkan interpretasi sentimen. Business Intelligence (BI) digunakan untuk menyediakan visualisasi data dan mendukung pengambilan keputusan yang cepat. Temuan penelitian menunjukkan bahwa pendekatan yang memperhatikan konteks budaya dan linguistik menghasilkan pemahaman sentimen yang lebih akurat dan memberikan wawasan penting dalam strategi branding universitas. Kombinasi teknologi Machine learning dan AI dalam analisis sentimen memberikan kontribusi pada pengembangan model manajemen sentimen yang lebih responsif dan relevan dengan kebutuhan branding universitas di era digital
REVITALISASI PASAR INDUK SAYUR MAYUR BATURITI DENGAN KONSEP OPEN FLOWING MARKET
Get PDFPasar tradisional memiliki peran strategis dalam sistem distribusi pangan di Indonesia, namun keberadaannya semakin terancam oleh perkembangan pasar modern dan e-commerce. Revitalisasi pasar tradisional menjadi strategi penting untuk meningkatkan daya saingnya. Penelitian ini bertujuan untuk menganalisis kondisi eksisting dan memberikan rekomendasi revitalisasi fisik Pasar Induk Sayur Mayur Baturiti. Metode penelitian yang digunakan adalah deskriptif kualitatif dengan pendekatan studi kasus, mencakup observasi langsung, wawancara, serta studi literatur. Hasil penelitian menunjukkan bahwa Pasar Induk Sayur Mayur Baturiti menghadapi berbagai permasalahan, seperti tata letak kios yang tidak terorganisir, sirkulasi pengunjung, distribusi barang yang kurang optimal, keterbatasan fasilitas umum seperti toilet dan area interaksi sosial. Konsep Open Flowing Market diterapkan dalam perancangan revitalisasi, menekankan fleksibilitas ruang, sistem zonasi yang efisien, serta jalur pedestrian dan distribusi barang yang terpisah. Selain itu, penambahan fasilitas pendukung seperti ruang terbuka hijau, foodcourt dan toilet yang lebih memadai diharapkan dapat meningkatkan kenyamanan, daya tarik pasar dan mampu mempertahankan identitas budaya pasar tradisional sebagai ruang interaksi sosial masyarakat di Bali.
Kata kunci: Revitalisasi pasar, pasar tradisional, tata letak, sirkulasi, Open Flowing Market, Pasar Induk Sayur Mayur Baturiti.
Pasar tradisional memiliki peran strategis dalam sistem distribusi pangan di Indonesia, namun keberadaannya semakin terancam oleh perkembangan pasar modern dan e-commerce. Revitalisasi pasar tradisional menjadi strategi penting untuk meningkatkan daya saingnya dengan mengoptimalkan aspek fisik, sosial, dan ekonomi. Penelitian ini bertujuan untuk menganalisis kondisi eksisting dan memberikan rekomendasi revitalisasi fisik Pasar Induk Sayur Mayur Baturiti di Kabupaten Tabanan, Bali. Metode penelitian yang digunakan adalah deskriptif kualitatif dengan pendekatan studi kasus, yang mencakup observasi langsung, wawancara dengan pemangku kepentingan, serta studi literatur. Hasil penelitian menunjukkan bahwa Pasar Induk Sayur Mayur Baturiti menghadapi berbagai permasalahan, seperti tata letak kios yang tidak terorganisir, sirkulasi pengunjung dan distribusi barang yang kurang optimal, serta keterbatasan fasilitas umum seperti toilet dan area interaksi sosial. Untuk mengatasi hal ini, konsep Open Flowing Market diterapkan dalam perancangan revitalisasi, yang menekankan fleksibilitas ruang, sistem zonasi yang lebih efisien, serta jalur pedestrian dan distribusi barang yang terpisah. Selain itu, penambahan fasilitas pendukung seperti ruang terbuka hijau, area makan (foodcourt) dan toilet yang lebih memadai diharapkan dapat meningkatkan kenyamanan serta daya tarik pasar. Implementasi konsep ini tidak hanya meningkatkan efisiensi operasional pasar dan pengalaman belanja pengunjung, tetapi juga mempertahankan identitas budaya pasar tradisional sebagai ruang interaksi sosial masyarakat lokal. Dengan penerapan strategi yang tepat, revitalisasi Pasar Induk Sayur Mayur Baturiti diharapkan dapat memperkuat posisinya sebagai pusat distribusi pangan di Bali serta meningkatkan daya saing pasar tradisional dalam era modern.
Kata kunci: Revitalisasi pasar, pasar tradisional, tata letak, sirkulasi, Open Flowing Market, Pasar Induk Sayur Mayur Baturiti.
 
Japan’s Soft Power through Doraemon: Story of Seasons in Enhancing Japan’s National Image
Get PDFThis study examines the role of the game Doraemon: Story of Seasons as Japans soft power in enhancing the country’s national image. This game, which combines the iconic Doraemon character with the Story of Seasons gameplay concept, presents a rich narrative and cultural elements. Through the semiotics analysis approach proposed by Roland Gérard Barthes — including sign, signifier, signified — this research explores how Japanese cultural representation is conveyed and received by global players through theme, plot, characterization, setting, and point of view. The study’s findings show that this game is not only a means of entertainment but also effectively introduces traditional values, aesthetics, and the Japanese lifestyle. Thus, Doraemon: Story of Seasons makes a positive contribution to strengthening Japan’s national image on the international stage through narrative-based cultural diplomacy
English Slang in Windah Basudara Live Stream Gaming
Get PDFThis research aims to analyze Windah Basudara\u27s use of English slang during his live-streaming sessions and to understand the context and meanings of these slang terms within the gaming world. The study employs a qualitative descriptive approach, observing and noting the slang used in Windah\u27s live streams accessed on YouTube on March 11, 2024. The findings identify various types of slang, including acronyms, clipping, and blending, demonstrating that slang functions as a communication tool and a means to foster closeness and shared identity among players and viewers. The discussion highlights the significant impact of public figures like Windah on the evolution of the Indonesian language, particularly among Generation Alpha, who adapt and showcase this language in digital contexts. The conclusion drawn from this research is that while slang enriches communication, attention must be given to its effects on the sustainability of standard Indonesian. This study provides new insights into how slang in digital contexts shapes social interactions and culture among young people, offering practical implications for language use in the digital age
Resistance of Main Character Willy in The Conductor Film by Maria Peters (Power Feminism Approach)
Get PDFThis study aims to find out the resistance of main characters in the movie that illustrate the values of power feminism based on Naomi Wolf\u27s theory. This study uses qualitative method that data from a film will be analyzed descriptively or in the other words the research’s methodology is descriptive qualitative. Furthermore, the struggles of the main character on the process to reaches her goals triggered by the rejection from patriarchal, gender stereotypes, gender bias inequality and injustice for women\u27s rights in a number of fields, such as work, role in public, etc. The results found from the study are the values of power feminism appeared in the main character when she made a struggle and made a difference in the world of music. Namely women and men both have significant roles in their lives, women have the right to determine their own destiny, women\u27s experiences are valuable, women have the right to express what they experience, and women deserve equality and justice in number of fields. In conclusion This research find that resistance is form of power feminism that started from main character itself until she reaches her goals. That because of power feminism that can be influenced on the movement. Finally, this study can provide a useful understanding of power feminism which means doing real things with tolerance rather than self-righteousness and aims to identify collectively held strengths rather than sharing weaknesses and sorrow
Compound Words in Five Selected Skincare Articles from Vogue Website
Get PDFA compound word is one of the processes of creating new words. Knowing compound words will make it easier for people to increase their vocabulary because vocabulary building is essential to any education. As a student\u27s vocabulary becomes more complex, it becomes increasingly important to understand the meaning of words and how they function as part of the overall language. Compound words are one of the first steps in a lifelong journey of vocabulary building. Not only creating new words but also creating new meanings in language. There are two aims in the research process. First, identify the types of compound words, and second, analyze the meaning of compound words. The data in this study was compound words with the five selected skincare articles as the data source. To classify the type of compound words, this study used the theory proposed by Lieber (2010). And for the meaning of the compound words, used theory proposed by Palmer (1976). Observation methods with note-taking techniques were applied in this study. A descriptive qualitative method was applied to analyze the data, which uses in-depth descriptions. The analysis was presented by informal method, in which the examined data are provided verbally. This method was used to explain the type of the compound words and explain the meaning of the compound words. There are five types of compound words found in five selected articles from Vogue Website, those are attributive endocentric, subordinative endocentric, coordinative endocentric, attributive exocentric, and subordinative exocentric. The meaning of the compound words found in 5 articles of Vogue websites are transparent meaning and opaque meaning.
Keywords: Compounding, Meaning, Morphology, Semantic
PERAN HUKUM DALAM PENINGKATAN KESEJAHTERAAN MELALUI EKONOMI BERBASIS KEADILAN: Role Of Law In Enhancing Welfare Through A Justice-Based Economy
Get PDFSocial justice is a fundamental principle in achieving welfare as mandated by Pancasila and the 1945 Constitution. However, socio-economic inequality and uneven wealth distribution remain significant challenges in Indonesia. This study aims to analyze the role of law in supporting welfare improvement through a justice-based economy. Using normative research methods and a qualitative approach, this study evaluates legislation, government policies, and relevant legal practices in realizing social justice principles. The findings indicate that law plays a strategic role in reducing social inequality and ensuring equitable wealth distribution through policies such as agrarian reform, progressive taxation, MSME empowerment, and workers\u27 rights protection. However, the implementation of these policies is often hindered by weak law enforcement, bureaucratic inefficiency, and corruption. Strengthening law enforcement, reforming bureaucracy, and increasing community involvement in policy oversight are crucial steps. This study highlights that synergy between the government, private sector, and society is necessary to create a legal system that supports an inclusive and socially just economy
Satire Humor in the Children\u27s Cartoon Series Spongebob Squarepants by Stephen Hillenburg
Get PDFThe title of this is satirical humor in the childrens cartoon series Spongebob Squarepants. The purpose of this study is to show and explain the scenes containing satirical humor in this cartoon that has been shown to many underage audiences who do not understand what the humor means. In this study, researchers used a descriptive qualitative method and used an objective approach by focusing on the object itself, namely “Spongebob Squarepants” cartoon. Then in collecting data, the researcher uses the listening technique in which the author has watched and listened to this cartoon repeatedly so as to get what will be presented in this study. The results of this study show several scenes containing satirical humor in the Spongebob Squarepants cartoon, which are shown to underage audiences and also explain the depiction of the humor that has been found.
Keywords: Satirical Humor, Cartoon, Spongebob Squarepant
Studi Pustaka: Optimalisasi Deteksi Malware melalui Integrasi Pembelajaran Mesin Heuristik dan Big Data untuk Keamanan Siber
Get PDFThe increasingly complex and dynamic threat of malware drives the need for a more adaptive detection strategy than conventional signature-based methods. This study aims to evaluate the effectiveness of machine learning, heuristics, and big data approaches in detecting modern malware. The main problem raised is the limitation of traditional methods in identifying new malware variants, especially those that use obfuscation techniques such as polymorphism and metamorphism. Using a systematic literature study approach to the 2016-2024 literature from various reputable sources, this study compares the performance of each approach based on accuracy, efficiency, and resistance to adversarial attacks. The results of the analysis show that deep learning models such as the Convolutional Neural Network (CNN) have the highest detection accuracy, while heuristic methods excel in initial detection efficiency, and big data provides advantages in the scalability of real-time detection systems. This study concludes that the hybrid integration of these three approaches has the potential to create a malware detection system that is more adaptive and resilient to cyberattacks, although further empirical validation is still needed for real-world implementation.Ancaman malware yang semakin kompleks dan dinamis mendorong perlunya strategi deteksi yang lebih adaptif daripada metode konvensional berbasis tanda tangan. Penelitian ini bertujuan untuk mengevaluasi efektivitas pendekatan pembelajaran mesin, heuristik, dan big data dalam mendeteksi malware modern. Permasalahan utama yang diangkat adalah keterbatasan metode tradisional dalam mengidentifikasi malware varian baru, khususnya yang menggunakan teknik obfuscation seperti polymorphism dan metamorphism. Dengan menggunakan pendekatan studi pustaka sistematis terhadap literatur tahun 2016-2024 dari berbagai sumber bereputasi, penelitian ini membandingkan performa masing-masing pendekatan berdasarkan akurasi, efisiensi, dan ketahanan terhadap serangan manipulatif (adversarial attacks). Hasil analisis menunjukkan bahwa model deep learning seperti Convolutional Neural Network (CNN) memiliki akurasi deteksi tertinggi, sedangkan metode heuristik unggul dalam efisiensi deteksi awal, dan big data memberikan keunggulan dalam skalabilitas sistem deteksi secara real-time. Penelitian ini menyimpulkan bahwa integrasi ketiga pendekatan secara hybrid berpotensi menciptakan sistem deteksi malware yang lebih adaptif dan tangguh terhadap serangan siber, meskipun validasi empiris lanjutan masih diperlukan untuk implementasi di dunia nyata
Comparison Of Lung Cancer Classification Using Decision Tree And Random Forest: Perbandingan Klasifikasi Penyakit Kanker Paru-Paru Menggunakan Decision Tree Dan Random Forest
No full textLung cancer is the leading cause of cancer-related deaths across various age groups, with risk factors such as smoking, air pollution, and chronic diseases. Lung cancer is characterized by the uncontrolled growth of cells in lung tissue, which can spread to other organs through metastasis. Machine learning-based classification can assist in the early detection of this disease. This study compares the Decision Tree and Random Forest methods in classifying lung cancer using a dataset containing seven attributes and 1,010 data entries. Missing values were handled using mode imputation. Feature importance analysis with Random Forest identified Coughing, Chronic Disease, Smoking, and Shortness of Breath as the most influential features in classification. The classification results showed that Decision Tree without feature selection achieved an accuracy of 64.85%, higher than Random Forest, which reached only 52.62%. After feature selection, Decision Tree accuracy decreased to 55.94%, while Random Forest experienced a slight decline to 52.47%. These findings indicate that Decision Tree is more effective in capturing data patterns without feature selection, whereas Random Forest tends to be less optimal with relatively small datasets.
Keywords – Machine Learning; Classification; Feature Importance; Entropy; Gain.Kanker paru-paru merupakan penyebab utama kematian akibat kanker di berbagai usia, dengan faktor risiko seperti merokok, polusi udara, dan penyakit kronis. Kanker paru-paru ditandai oleh pertumbuhan sel tidak terkendali di jaringan paru-paru, yang dapat menyebar ke organ lain melalui metastasis Klasifikasi berbasis machine learning dapat membantu dalam deteksi dini penyakit ini. Penelitian ini membandingkan metode Decision Tree dan Random Forest dalam klasifikasi kanker paru-paru menggunakan dataset dengan tujuh atribut dan 1010 baris data. Missing value ditangani dengan metode imputasi modus. Analisis feature importance dengan Random Forest menunjukkan bahwa fitur Coughing, Chronic Disease, Smoking, dan Shortness of Breath memiliki pengaruh tertinggi dalam klasifikasi. Hasil klasifikasi menunjukkan bahwa Decision Tree tanpa pemilihan fitur mencapai akurasi 64,85%, lebih tinggi dibandingkan Random Forest yang hanya mencapai 52,62%. Setelah dilakukan pemilihan fitur, akurasi Decision Tree menurun menjadi 55,94%, sementara Random Forest mengalami sedikit penurunan menjadi 52,47%. Hasil ini menunjukkan bahwa Decision Tree lebih efektif dalam menangkap pola data tanpa seleksi fitur, sedangkan Random Forest cenderung kurang optimal dengan dataset yang relatif kecil.
Kata Kunci – Machine Learning; Klasifikasi; Feature Importance; Entropi; Gain