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ANALISIS REPRESENTASI BENTUK EKSPRESI FILM TILIK SUTRADARA AGUNG WAHYU PRASETYO Darma, Surya; Wahyuni, Sri; Alfathoni, Muhammad Ali Mursid
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.5109

Abstract

Abstract: The purpose of this study is to analyze the representation of the form of expression in the film Tilik (2018) by director Wahyu Agung Prasetyo. The reason the researcher analyzed the film Tilik (2018) is because it authentically visualizes the social dynamics of rural communities, especially in Java, through dialogue and visuals of its characters. This research method uses descriptive qualitative research with content analysis techniques in the film Tilik (2018) through scenes, visuals, dialogue, narration, facial expressions, body language, and cinematography techniques used. The results of this study produce three main forms of expression in the film Tilik (2018), namely emotional expressions seen through facial expressions and gestures that depict several forms of expression such as anger, happiness, sadness, disgust, and surprise, then linguistic expressions in the form of depiction through sarcastic dialogue and satire through gossip practices as a model of social forms, and visual expressions depicted through cinematography techniques such as close-ups, narrow framing, and natural lighting as supporters of emotional assertiveness. The conclusion of this study is that the film Tilik (2018) presents a micro-portrait of rural Javanese society, which faces complex and dynamic problems. Keywords: Tilik (2018), forms of expression, analysis of expression, cinematography Abstrak: Tujuan penelitian ini adalah analisis representasi bentuk ekspresi film Tilik (2018) karya sutradara Wahyu Agung Prasetyo. Alsan peneliti menganalisis film Tilik (2018) ini karena memvisualkan dinamika sosial masyarakat di pedesaan khususnya Jawa secara autentik melalui dialog dan visual tokohnya. Metode penelitian ini menggunakan penelitian kualitatif desktiptif dengan teknik menganalisis isi (content analysis) pada film Tilik (2018) melalui adegan, visual, dialog, narasi, ekpresi wajah, bahasa tubuh, dan teknik sinematografi yang digunakan. Hasil penelitian ini menghasilkan tiga bentuk ekspresi utama pada film Tilik (2018), yaitu ekspresi emosional yang terlihat melalui mimik wajah dan gestur yang menggambarkan beberapa bentuk ekspresi seperti marah, bahagia, kesedihan, rasa muak, dan terkejut, selanjutnya ekspresi linguistik bentuk penggambarannya melalui dialog sarkastik dan bentuk sindiran melalui praktik gosip sebagai model dari bentuk sosial, dan ekspresi visual yang di gambarkan melalui model teknik sinematografi seperti close-up, framing sempit, dan pencahayaan alami sebagai pendukung ketegasan dari emosional. Kesimpulan dari penelitian ini adalah film Tilik (2018) menghadirkan potret mikro masyarakat di pedesaan Jawa yang memiliki permasalahan kompleks, dan dinamis. Kata kunci: Film Tilik (2018), bentuk ekspresi, analisis ekspresi, sinematografi
Penguatan Kompetensi Transformasi Digital Mahasiswa Universitas Battuta melalui Workshop Pemanfaatan Teknologi Cloud Computing Ginting, Subhan Hafiz Nanda; Wahyuni, Dewi; Sridewi, Nurmala; Wayahdi, M. Rhifky; Darma, Surya
Jurnal Pustaka Dianmas Vol 5, No 2 (2025)
Publisher : Universitas Prof. Dr. Moestopo (Beragama)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32509/dianmas.v5i2.6764

Abstract

Digital transformation is a strategic necessity in facing the dynamics of the world of work and developments in the information technology industry. Students, as future professionals, are required to have relevant digital competencies, particularly in the use of cloud computing technology, which is increasingly being used in data management, application development, and network-based collaboration. This community service activity aims to strengthen the digital transformation competencies of Battuta University students through the implementation of structured and applicable cloud computing technology utilization workshops. The methods used in this activity include participant needs analysis, material preparation, interactive workshop implementation, practical guidance, and activity outcome evaluation. The workshop material covered an introduction to the basic concepts of cloud computing, an understanding of key cloud services, and practical use of cloud platforms for data storage, access management, and implementation of simple services. Evaluation was conducted through pre-tests, post-tests, and observation of participant engagement during the activity. The results of the activity showed an increase in students' conceptual understanding and technical abilities in utilizing cloud technology. This activity contributed positively to improving students' readiness to meet competency demands in the digital era and strengthening their technological literacy and adaptation.
Penilaian Kesesuaian Lahan Untuk Pengembangan Tanaman Padi Sawah Irigasi (Oryza Sativa L.) di Kota Samarinda Panjaitan, Pranata Halasan; Darma, Surya; Sulistioadi, Yohanes Budi; Zulkarnain, Zulkarnain; Fahrunsyah, Fahrunsyah; Ibrahim, Ibrahim
Jurnal Agroekoteknologi Tropika Lembab Vol 8, No 2 (2026): Agroekoteknologi Tropika Lembab Volume 8 Nomor 2 Februari 2026
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jatl.8.2.2026.21945.76-82

Abstract

Sektor pertanian pada negara-negara berkembang termasuk Indonesia memiliki pengaruh besar dalam meningkatkan pertumbuhan ekonomi dan ketahanan pangan. Namun, pada saat yang sama lahan pertanian semakin tergerus akibat terjadinya alih fungsi lahan. Perubahan ini menyebabkan lahan-lahan sawah produktif berubah yang menuntut penggunaan lahan sawah eksisting digunakan secara intens untuk memenuhi kebutuhan pangan masyarakat yang menyebabkan menurunnya kondisi kesesuaian lahan dan  bervariasinya kemampuan produksi lahan sawah. Penelitian ini bertujuan untuk mengetahui kesesuaian lahan aktual dan potensial tanaman padi sawah di Kota Samarinda dan memberikan arahan untuk mengatasi faktor-faktor pembatas. Penelitian ini menggunakan metode metode matching yaitu mencocokkan karakteristik lahan dengan persyaratan tumbuh tanaman berdasarkan Petunjuk Teknis Evaluasi Lahan untuk Komoditas Pertanian. Hasil evaluasi kesesuaian lahan aktual komoditas padi di Kota Samarinda secara keseluruhan tergolong kelas S2 (cukup sesuai) berada pada subkelas S2nr,na dan S2nr dengan faktor pembatas KTK, P-Tersedia, KB dan pH tanah. Perbaikan yang dapat dilakukan untuk meningkatkan kesesuaian lahan yaitu dengan pengapuran tanah, penambahan bahan organik dan pemupukan yang akan meningkatkan kelas kesesuaian lahan potensialnya menjadi S1 (sangat sesuai).
IMPLEMENTATION OF THE INTERNET OF THINGS IN CREATING SMART CLASSROOMS Ginting, Subhan Hafiz Nanda; Wahyuni, Dewi; Sridewi, Nurmala; Wayahdi, M. Rhifky; Darma, Surya
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 9, No 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5806

Abstract

Abstract: The development of digital technology has driven the transformation of educational services through the implementation of data-based learning systems and smart devices. One of the emerging approaches is the use of the Internet of Things (IoT) in building smart classrooms, which are classrooms capable of integrating physical devices, sensors, and information systems to improve learning efficiency and learning environment management. This study aims to analyze the implementation of IoT in the formation of smart classrooms, covering aspects of system design, device integration, and evaluation of its effectiveness in supporting the teaching and learning process. The research method used is a quantitative and experimental approach, by designing an IoT-based smart classroom prototype that integrates temperature, humidity, light intensity, and presence detection sensors, as well as device control such as lights, air conditioning, and projectors through an automatic system and remote control. Data was collected through device performance measurements, network stability tests, and questionnaires distributed to users (teachers and students) to assess the system's ease of use and usefulness. The results showed that the implementation of IoT in classrooms can improve the efficiency of facility management through device automation, facilitate real-time monitoring of classroom conditions, and provide a more comfortable and responsive learning environment. In addition, the developed system demonstrated stable data communication performance with low latency within acceptable operational limits. These findings indicate that the application of IoT in smart classrooms has the potential to contribute significantly to improving the quality of learning and classroom management, particularly in supporting a technology-based education ecosystem. This study recommends further development in the areas of data security, device interoperability, and integration with Learning Management Systems (LMS) to strengthen the sustainable implementation of smart classrooms. Keywords: Internet of Things, Smart Classroom, Classroom Automation, Sensors, Technology Based Education. Abstrak: Perkembangan teknologi digital mendorong transformasi layanan pendidikan melalui penerapan sistem pembelajaran berbasis data dan perangkat cerdas. Salah satu pendekatan yang berkembang adalah pemanfaatan Internet of Things (IoT) dalam membangun smart classroom, yaitu ruang kelas yang mampu mengintegrasikan perangkat fisik, sensor, serta sistem informasi untuk meningkatkan efisiensi pembelajaran dan pengelolaan lingkungan belajar. Penelitian ini bertujuan untuk menganalisis implementasi IoT dalam pembentukan smart classroom, mencakup aspek desain sistem, integrasi perangkat, serta evaluasi efektivitasnya dalam mendukung proses belajar mengajar. Metode penelitian yang digunakan adalah pendekatan kuantitatif dan eksperimental, dengan merancang prototipe smart classroom berbasis IoT yang mengintegrasikan sensor suhu, kelembapan, intensitas cahaya, deteksi kehadiran, serta pengendalian perangkat seperti lampu, pendingin ruangan, dan proyektor melalui sistem otomatis maupun kendali jarak jauh. Data dikumpulkan melalui pengukuran kinerja perangkat, uji stabilitas jaringan, serta penyebaran kuesioner kepada pengguna (guru dan siswa) untuk menilai tingkat kemudahan penggunaan dan kebermanfaatan sistem. Hasil penelitian menunjukkan bahwa implementasi IoT pada ruang kelas mampu meningkatkan efisiensi pengelolaan fasilitas melalui otomasi perangkat, mempermudah monitoring kondisi kelas secara real-time, serta memberikan dukungan lingkungan belajar yang lebih nyaman dan responsif. Selain itu, sistem yang dikembangkan menunjukkan performa komunikasi data yang stabil dengan tingkat keterlambatan (latency) yang rendah dalam batas operasional yang dapat diterima. Temuan ini mengindikasikan bahwa penerapan IoT dalam smart classroom berpotensi memberikan kontribusi signifikan terhadap peningkatan kualitas pembelajaran dan manajemen kelas, khususnya dalam mendukung ekosistem pendidikan berbasis teknologi. Penelitian ini merekomendasikan pengembangan lanjutan pada aspek keamanan data, interoperabilitas perangkat, serta integrasi dengan Learning Management System (LMS) untuk memperkuat implementasi smart classroom secara berkelanjutan. Kata Kunci: Internet Of Things, Smart Classroom, Otomasi Ruang Kelas, Sensor, Pendidikan Berbasis Teknologi.
Predictive Analysis of Flood Risk Factors Based on a Machine Learning Approach: Comparative Study of SVM and XGBoost Algorithms Darma, Surya; Al Fayed, Ahmad Jihad; P Pardede, Surya Maruli; Aqsha, Muhammad Hizbul; Novelan, Muhammad Syahputra
Journal of Technology and Computer Vol. 3 No. 1 (2026): February 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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

Abstract

Flood events in Indonesia continue to increase in frequency and impact due to high rainfall variability, land-use change, and complex hydrological conditions. Accurate predictive modeling is therefore essential to support flood risk assessment and mitigation planning. This study evaluates the predictive performance of two supervised machine learning algorithms, Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost), for flood risk classification. The analysis is conducted using a publicly available dataset comprising 500 samples that represent multiple environmental and spatial factors related to flood occurrence. Data preprocessing includes cleaning, normalization, and feature consistency adjustment prior to model implementation. Both algorithms are trained and tested using the same dataset configuration to ensure objective comparison. Model performance is assessed using accuracy, precision, recall, and F1-score metrics. Experimental results indicate that XGBoost achieves higher accuracy and precision, demonstrating stronger capability in reducing false-positive predictions, while SVM shows relatively higher recall, reflecting better sensitivity in identifying flood-prone cases. Overall, XGBoost provides more reliable predictive performance for flood risk modeling on the dataset used. The findings confirm the effectiveness of machine learning-based approaches for flood risk prediction and highlight the importance of algorithm selection in disaster risk analysis.
PERBANDINGAN KINERJA ALGORITMA MACHINE LEARNING DALAM MEMPREDIKSI TINGKAT STRES MAHASISWA BERDASARKAN FAKTOR AKADEMIK DAN NON-AKADEMIK Fayed, Ahmad Jihad Al; Darma, Surya; Aqsha, Muhammad Hizbul; Pardede, Surya Maruli P; Amin, Muhammad
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 9, No 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5805

Abstract

Abstract: Stress among students is a growing phenomenon due to high academic demands, changes in the social environment, and various non-academic pressures faced during their studies. Stress that is not managed properly can have a negative impact on students' mental health, motivation to study, and academic achievement. Therefore, an approach is needed that can identify and predict students' stress levels objectively and based on data. This study aims to analyze and compare the performance of several machine learning algorithms in predicting student stress levels based on academic and non-academic factors. The dataset used in this study is Student Stress Factors, which includes various variables such as Sleep Quality, Academic Achievement, Study Load, Frequency of Headaches, Extracurricular Activities, Level of Social Support, Screen Time, etc. The algorithms applied are Support Vector Machine and Naive Bayes. This research is expected to contribute to the development of a decision support system for early detection of student stress levels, as well as serve as a reference for educational institutions in designing strategies for the prevention and management of mental health issues in higher education environments. Keywords: Machine Learning, Support Vector Machine, Naive Bayes, Stress, Student Abstrak: Stres pada mahasiswa merupakan fenomena yang semakin meningkat seiring dengan tuntutan akademik yang tinggi, perubahan lingkungan sosial, serta berbagai tekanan non-akademik yang dihadapi selama masa studi. Kondisi stres yang tidak dikelola dengan baik dapat berdampak negatif terhadap kesehatan mental, motivasi belajar, serta capaian akademik mahasiswa. Oleh karena itu, diperlukan suatu pendekatan yang mampu mengidentifikasi dan memprediksi tingkat stres mahasiswa secara objektif dan berbasis data. Penelitian ini bertujuan untuk menganalisis serta membandingkan kinerja algoritma machine learning dalam memprediksi tingkat stres mahasiswa berdasarkan faktor akademik dan non-akademik. Dataset yang digunakan pada penelitian ini adalah Student Stress Factors, yang mencakup berbagai variabel seperti Kualitas Tidur, Prestasi Akademik, Beban Studi, Frekuensi Sakit Kepala, Kegiatan Ekstrakurikuler, Tingkat Dukungan Sosial, Jam Waktu Layar, dll. Algoritma yang diterapkan yaitu Support Vector Machine dan Naive Bayes dengan akurasi tertinggi dihasilkan oleh Algoritma SVM dengan akurasi 85% sedangkan NV memiliki akurasi 83%. Penelitian ini diharapkan dapat memberikan kontribusi dalam pengembangan sistem pendukung keputusan untuk deteksi dini tingkat stres mahasiswa, serta menjadi referensi bagi institusi pendidikan dalam merancang strategi pencegahan dan penanganan masalah kesehatan mental di lingkungan perguruan tinggi. Kata kunci: Machine Learning, Support Vector Machine, Naive Bayes, Stres, Mahasiswa
Empowering coastal women through marine resource innovation: Transforming low-value catch into standardized processed products Safitri, Ikha; Warsidah, Warsidah; Apriansyah, Apriansyah; Sofiana, Mega Sari Juane; Nuraya, Tia; Minsas, Sukal; Kushadiwijayanto, Arie Antasari; Nurdiansyah, Syarif Irwan; Nurrahman, Yusuf Arief; Kuncoro, Iwan; Kusumaningsih, Alvianita Rika Putri; Sukma, Nimaz Tegar; Prayitno, Dwi Imam; Helena, Shifa; Idiawati, Nora; Harianto, Harianto; Darma, Surya
Community Empowerment Vol. 11 No. 2 (2026)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ce.15251

Abstract

Kuala Secapah Village serves as a prominent hub for capture fisheries along the coast of West Kalimantan. Alongside premium catches, local fishermen frequently haul trash fish (ikan rucah), that remains economically underutilized. Applying innovative and sustainable processing approaches to these marine resources can significantly generate added value for the community. This community service program aims to educate and train coastal women on upgrading these underutilized catches into competitive food products. The program was delivered in participatory workshop divided into two sessions: an instructional lecture and a hands-on culinary production practice. The intervention yielded substantial progress, with participants' technical knowledge skyrocketing from 64% to 99.6% regarding standardized and proper fish-processing techniques. Ultimately, this initiative successfully fosters local economic resilience by converting underutilized marine waste into high-value commodities.
Co-Authors . Apriansyah Abdullah, Ilmi Adinata, Triawan Al Fayed, Ahmad Jihad Alfathoni, Muhammad Ali Mursid Alferon, Hazalin Algifari, M. Ridho Novtriawan Al’amudi, Ivana Supi Angie, Evelyn Annisa Fithria Aqsha, Muhammad Hizbul Arikha Saputra Asrori, Muhamad Amin Asrullah Asrullah, Asrullah Azmi Ginting, Naufal Bagus Adi Nugroho Bahar Bahar, Bahar Bangun, Sri Melda Damanik, Abdi Rahim Desi, Efani Dewi Wahyuni Dhonanto, Donny Eddy Mart Salim, Eddy Mart Eka Irawan Elhias Nst, Mas Ayoe Ellanda Purwawijaya Fahrunsyah, Fahrunsyah Fayed, Ahmad Jihad Al Firzada, Fahmi fithry tahel, fithry Ginting, Erwin Ginting, Rosita Ginting, Subhan Hafiz Nanda Hadi Pranoto Harahap, Muhammad Farhan Harianto Harianto Helena, Shifa Hendri Budi Kurniyanto Hermansyah Hermansyah Hertanto, Rusdian Heru Satria Tambunan, Heru Satria Hidayat, Wahyu Handoyono Ibni Aura Sasabela Ibrahim Ibrahim Idris, Suria Darma Ikha Safitri Ilham Syahputra Saragih IMANG, NDAN Indra Gunawan Indrajaya, Taufik Indrawan, Yudhistira Fauzy Irmayani Irmayani John Juliandra, Obie Kasron Nst Khairul Amri Kriswiastiny, Rina KUNCORO, IWAN - kurniati, nova Kushadiwijayanto, Arie Antasari Kusumaningsih, Alvianita Rika Putri Liliana Puspa Sari Lubis, Yuliani Mardiati M. Rhifky Wayahdi Manesah, Dani MARIA BINTANG Matra, Ikahariya Pratiwi Mediarty, Mediarty Mega Sari Juane Sofiana Mikhael, Rodry Minsas, Sukal Monang, Sori Muhammad Amin Muhammad Reagan Muhammad Syahputra Novelan Muharraran, Firdha Mulya, Mhd. Ade Mulyadi Mulyadi Mulyadi, Asri Muthia, Putri Muthia, Putri Mutiar Mutiar, Mutiar Nefi Darmayanti Nora Idiawati Nur Riviati, Nur Nurdiansyah, Sy. Irwan Nurdiansyah, Syarif Irwan Nurhartanto, Nurhartanto Nurhasanah Nurhasanah Okprana, Harly P Pardede, Surya Maruli Panjaitan, Pranata Halasan Paranoan, Ria Rachel Pardede, Surya Maruli P Parinduri, Anggi Isnani Polem, Haga Putra Arza Prayitno, Dwi Imam Purnomo, Aji Putra, Dian Eka RACHMAT HIDAYAT Radiyati Umi Partan, Radiyati Umi Rahim Damanik, Abdi Rahman, Nopijal Rizki Ramadani, Alpin Ramadhan, Noor Muhammad Rizky Khairunnisa Sormin Rizqa Amelia, Rizqa Robiansyah, Wendi Roro Kesumaningwati Rudiyanto Rudiyanto, Rudiyanto ruziq, fahmi S, Budiman Salsabila, Ghaisani Samura, Jul Asdar Sarwoto Sarwoto, Sarwoto Silitonga, Aira Priamas Siti Aliyah Sri Wahyuni Sridewi, Nurmala Suherman, R.M. Edy Suherman, Suherman Sukma, Nimaz Tegar Sumarno . Syahputri, Aprilia Taufan Purwokusumaning Daru, Taufan Purwokusumaning Tia Nuraya Umi Partan, Radiyati Usman, Khairul Veithzal Rivai Zainal Warsidah, Warsidah Widodo Saputra Yulianto kusnadi Yuniza, Yuniza Yusuf Arief Nurrahman Zulkarnain Zulkarnain