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Implementasi Alat Pengusir Burung Otomatis Berbasis Embedded System di Lahan Pertanian Gede Angga Pradipta; Made Liandana; Putu Desiana Wulaning Ayu; I Made Darma Susila; Dandy Pramana Hostiadi; Yohanes Priyo Atmojo
WIDYABHAKTI Jurnal Ilmiah Populer Vol. 8 No. 1 (2025): Nopember
Publisher : Direktorat Penelitian, Pengabdian Masyarakat, dan HKI Institut Teknologi dan Bisnis STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/widyabhakti.v8i1.875

Abstract

Gangguan hama burung pada lahan pertanian, khususnya di area persawahan, menjadi salah satu faktor yang menyebabkan penurunan hasil panen. Penelitian ini bertujuan untuk mengembangkan sebuah alat otomatis berbasis sistem tertanam (embedded system) yang berfungsi sebagai pengusir burung di sawah. Alat ini bekerja dengan menarik tali lonceng secara otomatis, sehingga menghasilkan bunyi yang dapat mengusir burung secara efektif. Sistem ini terdiri dari beberapa komponen utama, yaitu panel surya sebagai sumber energi, motor penggerak, lengan penarik, dan mikrokontroler sebagai pusat kendali. Mikrokontroler diatur untuk menggerakkan lengan penarik dan mengatur waktu operasional secara otomatis. Hasil pengujian menunjukkan bahwa alat ini mampu beroperasi secara stabil dan efektif dalam mengusir burung, serta dapat bekerja secara mandiri dengan memanfaatkan energi terbarukan dari panel surya. Dengan demikian, alat ini diharapkan dapat menjadi solusi praktis dan berkelanjutan dalam mengatasi masalah hama burung di sektor pertanian.
Optimization Model for Fake Account Detection on Twitter (X) Social Media using Feature Engineering and Machine Learning Approaches Perimawati, Ni Nyoman Eny; Huizen, Roy Rudolf; Hostiadi, Dandy Pramana
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 9 No. 2 (2025)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v9i2.1727

Abstract

Twitter (X) has become an important platform for community interaction, but this also creates serious challenges due to the proliferation of fake accounts that can harm users and undermine credibility. Previous studies have proposed detection methods but often lacked forensic analysis based on extracted feature information. This study utilizes labeled datasets and supervised evaluation metrics (precision, recall, and F1-score) to validate model performance. Extracting behavioral information from features is crucial for achieving accurate and reliable detection results. The study introduces a novelty in the form of engineered behavioral features that significantly enhance detection accuracy, achieving up to 99.94% using AdaBoost. The proposed approach detects fake accounts on Twitter (X) by extracting key feature information and developing an optimal detection method through machine learning algorithms, including Random Forest, SVM, and AdaBoost. Furthermore, the model is optimized using feature engineering techniques. The novelty of this work lies in the development of engineered features through distribution analysis based on data characteristics and the improvement of classification performance through feature engineering optimization. The initial experiment without feature engineering shows that Random Forest achieved the highest accuracy of 98.77%, followed by AdaBoost at 98.57% and SVM at 95.90%. After applying feature engineering, performance improved, with AdaBoost reaching 99.94%, Random Forest 99.69%, and SVM 99.32%. The proposed model can assist system analysts in detecting fake accounts and contribute to solving forensic cybercrime challenges, particularly in identifying fake social media profiles.
Classification of Infected Salmon Using CNN Deep Features and Optuna-Optimized SVM Pradita, Agus Hendra; Ayu, Putu Desiana Wulaning; Hostiadi, Dandy Pramana
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 20, No 1 (2026): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.108820

Abstract

Fish diseases are a major challenge in the aquaculture industry, impacting productivity and the economy, particularly in salmon farming. This study aims to develop an image classification system for infected salmon using Convolution Neural Network (CNN) deep features approach and Support Vector Machine (SVM) classifier optimized with Optuna. The dataset consists of 1,208 images that were balanced through augmentation before being divided into 70% training data and 30% test data. Features were extracted from the middle layer of three pretrained CNN architectures: EfficientNetB1 (block6d_add), ResNet50 (conv4_block6_out), and VGG16 (block4_pool), then selected using the Least Absolute Shrinkage and Selection Operator (LASSO) method to address high-dimensionality issues. An SVM classification model was trained using stratified 5-fold cross-validation, both with default parameters and hyperparameter optimization results from Optuna. The results show that the model with features from EfficientNetB1 tuned by Optuna achieved the highest accuracy of 99.34%, a significant improvement over the default model 98.23%. Meanwhile, ResNet50 and VGG16 achieved optimal accuracies of 98.23% and 98.89%, respectively, after tuning. This study contributes to the development of an adaptive and accurate early detection system for infected fish.
Measuring Instagram Content Effectiveness in Digital Marketing usingthe EPIC Model and Direct Rating Method I Gede Edy Artana; Evi Triandini; Dandy Pramana Hostiadi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 25 No. 2 (2026)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v25i2.4843

Abstract

Instagram has become known as one of the leading platforms in digital marketing, making it essential to systematically evaluate the effectiveness of the content presented to ensure successful communication strategies. This study aims to measure the effectiveness of Instagram content produced by Kayana Creative using the EPIC Model and the Direct Rating Method, two complementary evaluative approaches that assess content quality and audience reception. The research involved 100 respondents who follow the Kayana Creative Instagram account. Data collected using a Likert-scale questionnaire and analyzed quantitatively to assess the four EPIC dimensions. Empathy, Persuasion, Impact, and Communication, as well as the overall evaluation through the Direct Rating Method. The results indicate that Instagram content is effective, with an average EPIC score of 4.04. The Communication dimension scored highest, indicating that the audience clearly understood the content’s messages. Using the Direct Rating Method, respondents provided an overall score of 80.48, further confirming that the content effectively captures attention and delivers a positive user experience. This study provides practical contributions for developing content that is more relevant, communicative, and engaging, and theoretical contributions by reinforcing the use of the EPIC Model and the Direct Rating Method as complementary evaluative tools for assessing content effectiveness on social media within the digital marketing context.
Co-Authors Amry wicaksono, Amry Anggreni Antarajaya, I Nyoman Suraja Artamerta, Aditya Naray Candra Ahmadi, Candra Chawaphan, Pharan Danang Setyo Utomo, Danang Setyo Dian Pramana S.Kom., M.Kom, Dian Erma Sulistyo Rini Erma Sulistyo Rini, Erma Sulistyo Eva Hariyanti Evi Triandini Fatonah, Nenden Siti Firgiawan Faira Florentina Tatrin Kurniati Gede Angga Pradipta Gede Angga Pradipta, Gede Angga Gede, Angga Pradipta Hendra Wijaya Hilmi, Muhammad Riza I G K G Puritan Wijaya. ADH, I G K G I Gede Edy Artana I Gede Harsemadi I Gede Ngurah Widya Pradnyana, I Gede Ngurah Widya I Gede Putu Krisna Juliharta I GKG Puritan Wijaya, I GKG I Gusti Ayu Dewi Suardi, I Gusti Ayu Dewi I Gusti Ngurah Darma Paramartha I Gusti Nym Adi Purnama Putra, I Gusti Nym I Made Darma Susila I Made Darma Susila, I Made I Made Darma Susila, I Made Darma I Made Liandana I Nyoman Triwantara Putra, I Nyoman I Putu Harry Wibawa Eka Putra, I Putu Harry Wibawa I Putu Oka Aditya Pratama I Putu Ramayasa, I Putu I Putu Widiantara, I Putu I Wayan Eka Mahardika, I Wayan Eka I Wayan Nesa Masjaya Perdana, I Wayan Nesa I.B. Putra Utama Dhiatmika, I.B. Putra Utama Ida Bagus Suradarma Indah, Hene Nor Intaran, Arya Ngurah Irene Realyta Halldy Trosi Tangkawarow Kadek Evanna Sidarta, Kadek Evanna Komang Yuli Santika Made Liandana Made Liandana, Made Made Sudarma Made, Liandana Mohammad Yazdi Pusadan Muhammad Riza Hilmi Ni Ketut Dewi Ari Jayanti Ni Luh Putri Srinadi Nurfalah, Rizal Farhan Nabila Pande Wira Andika, Pande Perimawati, Ni Nyoman Eny Pradita, Agus Hendra Putu Desiana Wulaning Ayu Rizky Adhitya Ridholloh, Rizky Adhitya Rosalia Hadi Roy Rudolf Huizen Rustamaji, Abdullah Saputra, Made Wisnu Adhi Shofwan Hanief Tubagus Mahendra Kusuma Widhyastuti, Luh Putu Wiwien Wulaning Ayu, Putu Desiana Wulaning Ayu, Putu Desiana Yohanes Priyo Atmojo Yohanes Priyo Atmojo Yohanes Priyo Atmojo, Yohanes Yohanes Priyo Atmojo, Yohanes Priyo Yudhi Pratiwindhya, Yudhi