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Muhammad Zulfadhilah
Teknologi Informasi, Universitas Sari Mulia
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Validasi Gerakan Sit-Up dengan Penerapan Konsep Trigonometri dalam Simulasi Python Rahmini Rahmini; Septyan Eka Prastya; Muhammad Zulfadhilah; Muhammad Ziki Elfirman; Usman Syapotro; Haldi Budiman
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 5 (2025): Oktober 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i5.9765

Abstract

Abstrak - Aktivitas sit-up merupakan salah satu latihan fisik yang umum digunakan untuk melatih kekuatan otot perut, namun sering dilakukan dengan teknik yang salah sehingga berpotensi menimbulkan cedera. Penelitian ini bertujuan mengembangkan sistem validasi gerakan sit-up berbasis computer vision dengan pendekatan trigonometri untuk mendeteksi kesesuaian sudut tubuh. Metode yang digunakan adalah pemanfaatan framework MediaPipe untuk ekstraksi titik sendi (keypoints), kemudian dilakukan perhitungan sudut pinggul dan lutut menggunakan aturan kosinus trigonometri. Validasi dilakukan dengan kriteria sudut pinggul 50°–100° dan lutut 60°–110°. Sistem diimplementasikan menggunakan Python dan Flask sebagai antarmuka. Hasil pengujian menunjukkan bahwa metode ini mampu mengidentifikasi gerakan sit-up dengan tingkat akurasi tinggi dan memberikan umpan balik secara real-time. Penelitian ini membuktikan bahwa kombinasi computer vision dan trigonometri dapat digunakan secara efektif dalam validasi gerakan olahraga.Kata kunci: Sit-up; Validasi Gerakan; MediaPipe; Trigonometri; Computer Vision; Abstract - Sit-up is one of the most common physical exercises for strengthening abdominal muscles, but it is often performed incorrectly, leading to a high risk of injury. This study aims to develop a sit-up movement validation system based on computer vision using trigonometric approaches to detect body angle conformity. The method applies the MediaPipe framework to extract body keypoints, followed by angle calculation of the hip and knee joints using the cosine rule of trigonometry. Validation is conducted using hip angle criteria of 50°–100° and knee angle criteria of 60°–110°. The system is implemented in Python with Flask as the user interface. Experimental results show that this method successfully identifies sit-up movements with high accuracy and provides real-time feedback. This study demonstrates that combining computer vision and t
Exploratory Data Analysis Pernikahan di Kabupaten Banjar dengan Pendekatan Machine Learning Nor Azizah; Mambang Mambang; Subhan Panji Cipta; Muhammad Zulfadhilah; Usman Syapotro; Haldi Budiman
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 3 (2025): Juni 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i3.9063

Abstract

Abstrak - Pernikahan adalah ikatan suci antara seorang pria dan wanita yang dilakukan dengan tujuan beribadah kepada Allah SWT. Tujuan dari pernikahan adalah untuk membentuk keluarga yang sakinah (tentram), mawaddah (cinta), dan rahmah (kasih sayang). Laporan Statistik Indonesia mencatat 1,7 juta pernikahan di Indonesia pada tahun 2022, turun 2,1% dari 1,74 juta pernikahan tahun 2021. Ini adalah angka terendah dalam sepuluh tahun terakhir, didorong oleh tren pernikahan yang menurun di Indonesia sejak 2012, yang merupakan angka tertinggi dalam sepuluh tahun terakhir. Penelitian ini bertujuan untuk mengkaji dataset pernikahan di Kabupaten Banjar dengan fokus pada hubungan antara jumlah pernikahan, pendidikan, dan usia pengantin menggunakan Exploratory Data Analysis (EDA) dan machine learning. Hasil penelitian menunjukkan korelasi kuat nilai 0,99 hingga 1 antara jumlah pernikahan, usia dan pendidikan pasangan. Kelompok usia 21–30 tahun dan dengan tingkat pendidikan SLTA memiliki tingkat pernikahan tertinggi. Hasil ini menunjukkan bahwa Exploratory Data Analysis (EDA) sangat penting untuk memahami pola sosial berdasarkan analisis data statistik.Kata kunci: exploratory data analysis; machine learning; pernikahan; supervised learning; python. Abstract - Marriage is a sacred bond between a man and a woman, undertaken with the intention of worshiping Allah SWT. The purpose of marriage is to build a family that is sakinah (peaceful), mawaddah (full of love), and rahmah (compassionate). According to the Indonesian Statistics Report, there were 1.7 million marriages in Indonesia in 2022, marking a 2.1% decrease from 1.74 million marriages in 2021. This represents the lowest number of marriages in the past decade, driven by a declining marriage trend in Indonesia since 2012, which was the peak year in that period. This study aims to examine the marriage dataset in Banjar Regency, focusing on the relationship between the number of marriages, educational background, and the age of the bride and groom using Exploratory Data Analysis (EDA) and machine learning. The results show a strong correlation, with values ranging from 0.99 to 1, between the number of marriages, age, and education levels of the couples. The highest marriage rates were observed among individuals aged 21–30 with a senior high school (SLTA) education level. These findings highlight the importance of Exploratory Data Analysis (EDA) in understanding social patterns through statistical data analysis.Keywords: exploratory data analysis; machine learning; marriage; supervised learning; python.
Analisis Sentimen Terhadap Tindakan Kekerasan Seksual pada Media Sosial Tiktok Menggunakan Metode Support Vector Machine (SVM) Indah Wulandari; Septyan Eka Prastya; Muhammad Zulfadhilah; Rudy Anshari
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 2 (2025): April 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i2.8892

Abstract

Abstrak - Pada aplikasi TikTok banyak sekali kita temukan konten – konten atau postingan video mengenai berita yang sedang viral di Indonesia terutama berita mengenai kekerasan seksual. Pada postingan tentang kekerasan seksual tersebut tidak jarang kita jumpai komentar para masyarakat atau netizen Indonesia yang mengacu pada korban. Tujuan penelitian dilakukan untuk mengidentifikasi pola pendapat atau reaksi yang diberikan oleh pengguna TikTok terhadap tindakan kekerasan seksual dalam komentar pada postingan video menggunakan Metode Support Vector Machine (SVM). Dalam penelitian ini, metode svm yang dikembangkan mencapai akurasi sebesar 79%, hal ini menunjukkan bahwa metode svm yang telah dilatih mampu melakukan klasifikasi sentimen dengan baik pada data uji. Dengan hasil yang didapatkan pada penelitian yang dilakukan menunjukkan bahwa hasil analisis sentimen negatif sekitar 43.6% lebih rendah dibandingkan dengan komentar positif yaitu sekitar 56.4%, selain itu metode svm dapat melakukan analisis sentimen terhadap komentar kekerasan seksual dengan hasil akurasi 79%. Hasil penelitian menunjukkan akurasi metode svm 79%, analisis menunjukkan bahwa 56.4% komentar bersifat positif. hal ini menunjukkan bahwa 56.4% mayoritas pengguna TikTok cenderung memberikan komentar yang mendukung dan empati terhadap korban yang mengalami kekerasan seksual.Kata kunci: kekerasan seksual, sentimen analisis, support vector machine (svm), tiktok.  Abstract - On the TikTok application, we often find content or video posts about news that is currently viral in Indonesia, especially news about sexual violence. In posts about sexual violence, we often find comments from the Indonesian public or netizens referring to the victim. The purpose of this study was to identify patterns of opinion or reactions given by TikTok users to acts of sexual violence in comments on video posts using the Support Vector Machine (SVM) Method. In this study, the svm method developed achieved an accuracy of 79%, this shows that the trained svm method is able to classify sentiment well on the test data. The results obtained in the study showed that the results of the negative sentiment analysis were around 43.6% lower than positive comments, which were around 56.4%, in addition the svm method can analyze sentiment on comments about sexual violence with an accuracy of 79%. The results of the study showed that the accuracy of the svm method was 79%, the analysis showed that 56.4% of the comments were positive. This shows that 56.4% of the majority of TikTok users tend to provide comments that support and empathize with victims who experience sexual violence.Keywords: sexual violence, sentiment analysis, support vector machine (SVM), TikTok.
Online Analisis Sentimen pada Pemilihan Umum Presiden di Kota Banjarmasin 2024 Nur Syifa; Bayu Nugraha; Muhammad Zulfadhilah
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 7, No 6 (2024): Desember 2024
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v7i6.8175

Abstract

Abstrak - Penelitian ini dilakukan untuk mengeksplorasi dinamika politik di era digital dan menggali pandangan serta sentimen masyarakat Banjarmasin terkait Pemilihan Umum Presiden 2024. Media sosial memainkan peran penting sebagai alat ekspresi politik dan pertukaran ide. Analisis sentimen digunakan untuk mengevaluasi opini publik dan preferensi politik masyarakat di Banjarmasin. Penelitian ini  bertujuan untuk mengamati dan menganalisis opini masyarakat di media sosial terkait Pilpres 2024. Selain itu, penelitian ini ingin memahami proses pengumpulan data opini masyarakat dan menganalisisnya menggunakan metode Support Vector Machine (SVM). Penelitian ini juga bertujuan untuk mengklasifikasikan sentimen menjadi positif atau negatif dan memahami pengaruhnya terhadap pandangan politik masyarakat. Metode yang digunakan dalam penelitian ini adalah Support Vector Machine (SVM). Data dikumpulkan dari platform media sosial dan form observasi masyarakat Banjarmasin. Distribusi kelas di seluruh dataset menunjukkan ketidakseimbangan yang signifikan, dengan 96,1% data berlabel positif (1071 sampel) dan hanya 3,9% berlabel negatif (44 sampel). Hasil evaluasi model menunjukkan bahwa model Support Vector Machine yang digunakan memiliki tingkat akurasi sebesar 94,62%. Penelitian ini menyoroti dominasi peran Instagram dan platform X dalam mempengaruhi arus informasi dan diskusi publik mengenai Pilpres 2024. Model Support Vector Machine (SVM) terbukti efektif dalam mengklasifikasikan sentimen dengan tingkat akurasi mencapai 94,62%, membuatnya menjadi alat yang kuat untuk analisis sentimen dalam konteks politik modern.Kata Kunci: akurasi, analisis sentimen, media sosial, pemilihan umum presiden, support vector machine (svm). Abstract -  This research aims to explore the political dynamics in the digital era and examine the views and sentiments of the people of Banjarmasin regarding the 2024 Presidential Election. Social media plays a significant role as a tool for political expression and idea exchange. Sentiment analysis is used to evaluate public opinion and political preferences of the people in Banjarmasin. The study aims to observe and analyze public opinions on social media regarding the 2024 Presidential Election. Additionally, it seeks to understand the data collection process of public opinions and analyze them using the Support Vector Machine (SVM) method. The study also aims to classify sentiments as positive or negative and understand their impact on the political views of the public.  The method used in this study is the Support Vector Machine (SVM). Data were collected from social media platforms and observation forms distributed to the people of Banjarmasin. The distribution of classes across the dataset showed significant imbalance, with 96.1% of the data labeled positive (1071 samples) and only 3.9% labeled negative (44 samples). Model evaluation results indicated that the Support Vector Machine model used had an accuracy rate of 94.62%. Conclusion: This study highlights the dominant role of Instagram and platform X in influencing the flow of information and public discourse regarding the 2024 Presidential Election. The Support Vector Machine (SVM) model proved effective in classifying sentiments with an accuracy rate of 94.62%, making it a powerful tool for sentiment analysis in the modern political context.Keywords: accuracy, presidential election, sentiment analysis, social media, support vector machine (svm).
Analysis of the Utilization of TikTok Content as a Coping Strategy to Reduce Stress Among Final-Year Students Using a Classification Method Husna Karima; Zulfadhilah, Muhammad; Prastya, Septyan Eka; Pratiwi, Evi Lestari
INSTALL: Information System and Technology Journal Vol 2 No 3 (2025): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v2i3.991

Abstract

Stress represents a prevalent psychological challenge among final- year university students, particularly during thesis completion. Academic pressure, social demands, and future uncertainty trigger stress that negatively impacts mental health. Social media, especially TikTok, is increasingly utilized as a coping mechanism to reduce stress through entertainment, educational, and motivational content. This study aims to analyze TikTok content utilization as a coping strategy for stress reduction among final-year students using a classification method. This quantitative research employed a survey approach with a population of 342 active TikTok users among final- year students at Sari Mulia University. Data were collected through an online questionnaire covering variables including content type, duration, features used, and psychological indicators such as anxiety, emotions, escapism, and coping effectiveness. Data preprocessing included one-hot encoding, SMOTE, and normalization, followed by classification using Support Vector Machine with RBF kernel optimized through GridSearchCV. Results revealed very high correlations among psychological variables (r ≈ 0.93–1.00), while correlations between content type and stress reduction were relatively low (0.00–0.15). Some pure entertainment content showed negative correlations with psychological improvement. The SVM model achieved high classification accuracy of approximately 94%. This study demonstrates that TikTok can serve as a short-term stress coping tool for final-year students, though its effectiveness depends heavily on the type of content consumed. Educational and motivational content shows greater potential for stress reduction compared to pure entertainment content. This research contributes to understanding digital mental health support mechanisms and provides insights for developing healthier media consumption strategies among university students.
The Effectiveness of early stopping on the efficiency of training CNN models for phishing URL identification Rifani, Muhammad Rifani; Prastya, Septyan Eka; Zulfadhilah, Muhammad; Munsyi
INSTALL: Information System and Technology Journal Vol 3 No 1 (2026): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v3i1.1024

Abstract

Phishing is a significant cybersecurity threat in which malicious URLs deceive users to steal sensitive data. Traditional detection methods, such as blacklists, often fail to keep pace with evolving phishing techniques. Deep learning, particularly Convolutional Neural Networks (CNNs), offers strong potential in phishing URL classification by capturing structural and semantic character-level patterns. However, CNN training demands high computational resources and risks overfitting. This study investigates the effectiveness of early stopping as a regularization technique to improve efficiency and generalization in character-based CNN models. Using a large-scale dataset of 130.080 URLs across four classes (benign, phishing, malware, defacement), the model employed character tokenization, embedding, convolution-pooling layers, and softmax classification. Early stopping monitored validation loss with patience values of 3, 5, and 10 epochs. Results show a 51% training time reduction and accuracy improvement from 96% to 97%, confirming early stopping as an efficient and robust detection approach.
Innovation in Crop Nutrition Planning Based on Rainfall Prediction Using Singular Spectrum Analysis and Boosting to Optimize Agricultural Management Yuslena Sari; Mambang Mambang; Muhammad Zulfadhilah; Subhan Panji Cipta; Muhammad Nursandi; Finki Dona Marleny; Ricardus Anggi Pramunendar; Sunardi Sunardi; Eka Setya Wijaya; Aurelia Monica Sari; Muhammad Alkaff
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 2 (2026): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/z3mgdv08

Abstract

The high variability of rainfall in tropical climates presents a major challenge for agricultural management, as weather uncertainty often leads to inefficient fertilization practices due to nutrient loss. This study aims to develop a robust framework for rainfall prediction, which can inform a flexible and precise crop nutrient scheduling system. Utilizing an hourly rainfall dataset (n=6,624) obtained from IoT sensors, the research proposes an approach that integrates Singular Spectrum Analysis (SSA) for signal decomposition and noise reduction with Gradient Boosting algorithms (LightGBM and XGBoost). Spline interpolation was employed to handle missing data, while SSA served to disentangle deterministic trends from random noise, enabling the models to perform more effectively on the refined dataset. Empirical evaluation demonstrates that the SSA-XGBoost hybrid model achieves superior performance, with an RMSE of 0.0057 and an R² of 0.8278, significantly outperforming the SSA-LightGBM model (R² 0.2879), which struggled to capture non-linear patterns within this dataset. The high predictive accuracy of the SSA-XGBoost model facilitates the implementation of responsive nutrient management strategies, wherein fertilizer application can be deferred during forecasted periods of high rainfall to prevent runoff and environmental pollution. This research contributes to the field of hydroinformatics by demonstrating the effectiveness of combining SSA and XGBoost as a cost-efficient yet high-performance solution for mitigating climate-related risks in tropical wetland agriculture.
DAMPAK PANDEMI COVID-19, EDUKASI PROTOKOL KESEHATAN SEBAGAI STRATEGI EKONOMI BERGERAK DAN MELEK TEKNOLOGI PADA PASAR SUBUH TRADISIONAL DESA KERTAK HANYAR 2 [PANDEMIC IMPACT OF COVID-19, EDUCATION OF HEALTH PROTOCOLS AS A MOBILE ECONOMIC STRATEGY AND TECHNOLOGICAL LITERATURE ON TRADITIONAL EARLY MORNING MARKETS OF KERTAK HANYAR VILLAGE 2] Darini Kurniawati; Muhammad Zulfadhilah; Karlina Karlina
Jurnal Sinergitas PKM & CSR Vol. 5 No. 1 (2020): October
Publisher : Universitas Pelita Harapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19166/jspc.v5i1.2936

Abstract

The impact of the COVID-19 pandemic is deeply felt by the community, especially in socio-cultural and economic life. Based on the results of observations and interviews with traders, there has been a 60% decrease in sales at the early morning market (Pasar Subuh), Kertak Hanyar 2 Village, Banjar Regency, South Kalimantan. The residents of the dawn market have known about the COVID-19 pandemic through electronic media, but they still lack awareness in complying with the health protocol rules established by the government. Health protocol facilities are also not yet available. The dedication aims to improve the economy in the market at dawn but by adhering to health protocols to prevent the spread of COVID-19. This service was carried out together with the village head by disseminating health protocols and interviews with traders and buyers, providing masks and providing means of washing hands and soap. The result of the activity is the installation of health protocol education banners, traders using masks, the distance between traders is at least 1 meter and using hand washing facilities for buyers and traders at the market entrance. The socio-cultural and economic life of the people at Subuh Market are moving again with a sense of security. BAHASA INDONESIA ABSTRACT: Dampak pandemi COVID-19 sangat dirasakan oleh masyarakat, khususnya kehidupan sosial budaya dan ekonomi. Berdasarkan hasil observasi dan wawancara dengan pedagang, telah terjadi penurunan penjualan 60% di Pasar Subuh Desa Kertak Hanyar 2 Kabupaten Banjar Kalimantan Selatan. Warga pasar subuh telah mengetahui adanya pandemi COVID-19 ini melalui media elektronik, namun masih kurangnya kesadaran dalam mematuhi aturan protokol kesehatan yang ditetapkan pemerintah. Sarana protokol kesehatan juga belum tersedia. Pengabdian bertujuan untuk meningkatkan perekonomian di pasar subuh tetapi dengan mematuhi protokol kesehatan untuk mencegah penyebaran COVID-19. Pengabdian ini dilakukan bersama dengan kepala desa dengan melakukan sosialisasi protokol kesehatan dan wawancara kepada pedagang dan pembeli, pemberian masker dan penyediaan sarana alat cuci tangan dan sabun. Hasil dari kegiatan adalah terpasangnya spanduk edukasi protokol kesehatan, pedagang menggunakan masker, jarak antar pedagang minimal 1meter dan menggunakan sarana cuci tangan untuk pembeli dan pedagang pada pintu masuk pasar. Kehidupan sosial budaya serta perekonomian masyarakat di Pasar Subuh bergerak kembali dengan rasa aman. 
GAMBARAN TINGKAT KESADARAN PASIEN CEDERA KEPALA MENGGUNAKAN GLASGOW COMA SCALE (GCS) Muhammad Riduansyah; Muhammad Zulfadhilah; Annisa Annisa
Jurnal Persatuan Perawat Nasional Indonesia (JPPNI) Vol 5, No 3 (2020)
Publisher : Persatuan Perawat Nasional Indonesia (JPPNI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32419/jppni.v5i3.236

Abstract

Cedera kepala merupakan kasus kegawatdaruratan yang sering dijumpai di Instalasi Gawat Darurat (IGD). Pasien membutuhkan penilaian tingkat kesadaran untuk menentukan tingkat keparahan dan cedera kepala yang dialami. Tujuan: Untuk mengetahui gambaran tingkat kesadaran pasien cedera kepala menggunakan Glasgow Coma Scale (GCS). Metode: Penelitian cross sectional ini melibatkan 30 responden yang mengalami cedera kepala dengan menggunakan metode accidental sampling. Pengumpulan data menggunakan instrumen GCS yang terdiri dari tiga komponen respons kesadaran yaitu mata, verbal dan motorik. Analisis data univariat dilakukan untuk mengetahui frekuensi dan persentase. Hasil: Mayoritas responden berjenis kelamin laki-laki (83,3%) dengan usia 36-45 tahun (53,3%) dan responden paling banyak memiliki tingkat kesadaran composmentis (30%). Respons mata terbanyak yaitu spontan (33,3%), respons verbal terbanyak yaitu orientasi baik (36,3%), dan respons motorik terbanyak yaitu mengikuti perintah (30%). Diskusi: Laki-laki lebih banyak terlibat dalam aktivitas yang berisiko tinggi sehingga kemungkinan mengalami cedera kepala lebih tinggi.  Usia perlu mendapatkan perhatian, karena semakin bertambah usia ada kemungkinan semakin buruk pemulihan pasien.  Pasien cedera kepala akan tetap sadar penuh jika sistem aktivasi retikuler (RAS) di batang otaknya tetap utuh atau tidak terganggu.  Simpulan: Diharapkan menjadi informasi tambahan bagi rumah sakit dalam meningkatkan mutu asuhan keperawatan pada pasien cedera kepala, terutama pemantauan tingkat kesadaran. Hasil penelitian ini juga diharapkan menjadi sumber informasi dan referensi di institusi pendidikan keperawatan mengenai gambaran tingkat kesadaran pasien cedera kepala menggunakan GCS. Diperlukan penelitian lebih lanjut untuk membandingkan keakuratan penilaian tingkat kesadaran dengan GCS dan skala alernatif lainnya seperti Full Outline of Unresponsiveness (FOUR) atau Comprehensive Level of Consciousness Scale (CLOCS).Kata Kunci: Cedera kepala, GCS, tingkat kesadaran.Overview of Consciousness Level of Patients with Head Injury Using Glasgow Coma Scale (GCS)ABSTRACTHead injury is an emergency case that is often found in the Emergency Room (ER). Patients require an assessment of the consciousness level to identify the severity of the head injury. Objective: To obtain an overview of the consciousness level of patients with head injury using the Glasgow Coma Scale (GCS). Methods: This research is a cross-sectional study involving 30 respondents with head injury taken using the accidental sampling method. Data were collected using the GCS instrument, consisting of three components of awareness responses: eye, verbal, and motor. Univariate data analysis was performed to identify frequency and percentage. Results: The majority of respondents were male (83.3%) aged 36-45 years (53.3%), and most respondents had compos mentis (30%). The majority of eye response was spontaneous (33.3%), the majority of verbal response was good orientation (36.3%), and the majority of motor response was following orders (30%). Discussion: Men are more involved in high-risk activities, so that the possibility of having a head injury is higher. Age needs attention because the older an individual gets, the worse the recovery will be. If the reticular activation system (RAS) in the brainstem remains intact or undisturbed, patients with head injury will remain fully conscious. Conclusion: It is expected that this research results can be additional information for hospitals to improve the quality of nursing care for patients with head injury, especially monitoring the consciousness level. The results of this research are also expected can be a source of information and reference in nursing education institutions regarding the overview of the consciousness level of patients with head injury using GCS. Further research is needed to compare the accuracy of the consciousness level assessment using GCS and other alternative scales such as the Full Outline of Unresponsiveness (FOUR) or the Comprehensive Level of Consciousness Scale (CLOCS).Keywords: Head injury, GCS, consciousness level. 
Workshop Kreativitas Digital: Menggali Potensi Imajinasi Siswa Sekolah Dasar Melalui Integrasi Artificial Intelligence Subhan Panji Cipta; Nadia Azaria; Mambang Mambang; Muhammad Zulfadhilah; Septyan Eka Prastya; Abdul Latif; Ratna Lindawati; Trifebi Shina Sabrila; Finki Dona Marleny
Darma Abdi Karya Vol. 5 No. 1 (2026): Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM POLITEKNIK LP3I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/darmaabdikarya.v5i1.2943

Abstract

Kemajuan teknologi kecerdasan buatan (Artificial Intelligence/AI) menuntut pengenalan sejak dini agar dapat dimanfaatkan secara positif.  Ditemukan fakta bahwa 90% siswa kelas VI telah menggunakan smartphone setiap hari, namun lebih dari 85% di antaranya belum pernah mendengar istilah Artificial Intelligence atau mengetahui bahwa algoritma AI mengendalikan aplikasi hiburan yang mereka gunakan sehari-hari. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan untuk meningkatkan pengetahuan siswa mengenai AI serta peranannya dalam mendukung kreativitas dan imajinasi. Metode yang digunakan adalah pendekatan participatory learning dan experiential learning, yang melibatkan 27 siswa kelas VI. Rangkaian kegiatan meliputi sosialisasi, pemaparan materi edukatif menggunakan media audiovisual interaktif, serta praktik langsung penggunaan teknologi AI sederhana. Hasil evaluasi yang dilakukan melalui observasi partisipatif selama sesi praktik, penilaian kualitas karya digital yang dihasilkan siswa, serta pengisian angket umpan balik setelah kegiatan menunjukkan bahwa program ini memberikan dampak positif yang signifikan dalam meningkatkan pemahaman kognitif serta merangsang kreativitas siswa. Metode ini dinilai lebih efektif dibandingkan pembelajaran konvensional dalam memperkenalkan teknologi masa depan kepada siswa sekolah dasar.
Co-Authors ., Mambang Abdul Kadir Abdul Kadir Abdul Latif Abdul latif Abdul Latif Adryan Ramadhan Ahmad Busairi Ahmad Faisal Ahmad Ghazali Madhony Ahmad Riki Renaldi Ahmad Riki Renaldy Angga Irawan Anggraini Susfarwanti Annisa Annisa Anshori Prasetya, Muhammad Riko Antonia Yenitia Asyiah Asyiah Aulia Rahma Aulia, Hudatul Aurelia Monica Sari Bayu Nugraha Bayu Nugraha Bima Wicaksono Cipta, Subhan Panji Darini Kurniawati Desilestia Dwi Salmarini Dewi Pusparani Sinambela, Dewi Pusparani Dwi Salmarini, Desilestia Eka Prastya, Septyan Ermadiningtyas, Retno Evi Lestari Pratiwi - Politeknik Hasnur Kalimantan Selatan, Evi Lestari Pratiwi Finki Dona Marleny Finki Dona Marleny Fitra Erlina Fitriani Fitriani Gusti Zahratunnisa Hadi, Nofie Haldi Budiman Haniffah Sri Rinjani Heni Pujiastuti Hudatul Aulia Husna Karima Husna Karima Ika Friscilla Imam Riadi Indah Wulandari Irawan, Angga Iwan Yuwindry Jaya Hari Santoso Junius Akbar Karlina Karlina Kartika Kartika Kartika Kartika Kelana, Enisda Libra Lisda Handayani, Lisda Lisyanti, Fatthiya Lufila Fila M Samsul Hasbi M Samsul Hasmi Mambang Maria Ulfah Maulana, Maghfur Maulana, Rahmat Melda Melda Miranda Miranda Misnawati Muhammad Alkaff Muhammad Khairul Akbar Muhammad Nursandi Muhammad Riduan Syafi’i Muhammad Riduansyah Muhammad Satrio Ayuba Muhammad Zaini Bakri Muhammad Ziki Elfirman Munsyi Muthia Elma Mutmainah Mutmainah Nadia Azaria Naparin, Husni Nastiti, Kunti Nita Hestiyana, Nita Noor Pratama, Ramadhani Nopie Hadi Nor Azizah Novalia Widiya Ningrum Novalia Widiya Ningrum Novita Dewi Iswandari Nur Hidayah Nur Lathifah Nur Meilianti Maulida Nur Syifa Nurhaeni Nurhaeni Nurhaeni Nurhaeni NURUL HIDAYAH Pebriadi, Muhammad Syahid Prastya, Septyan Eka Putri Putri Putri Yuliantie Rahmadaniati Hikmah Rahmini Rahmini Ratna Lindawati Rhafiq Abdul Ghani Ricardus Anggi Pramunendar Rifani, Muhammad Rifani Risma Maulida Risma Risma Rismawati Rismawati Rizka Aulia Rizkian Muhammad Fikri Ropikah Ropikah Rudy Ansari Rudy Anshari Sabrila, Trifebi Shina Samita, Mambang Sandro Nesta Pembriano Sari, Rahmadah Septian Eka Prastya Septyan Eka Prasetya Septyan Eka Prastya Septyan Eka Prastya Septyan Eka Prastya Septyan Eka Prastya Setia Budi Shopa Handayani Siti Gadis Hardianti Subhan Panji Cipta Subhan Panji Cipta Subhan Panji Cipta Subhan Panji Cipta Subhan Panji Cipta Sultan Arrasyid Sunardi, Ph.D., Sunardi Susanti Suhartati, Susanti Syapotro, Usman Tasya Salsabila Theresia Kurniati Seran Umi Hanik Fetriyah Usman Syapotro Viviana Viviana Wijaya, Eka Setya Winda Maolinda Wulandari Febriani Wusko, Ikna Urwatul Yudi prayudi Yunandar Yunandar Yuslena Sari, Yuslena Yusri Yusri Zaini Lambri Assyaifi