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TINJAUAN PUSTAKA SISTEMATIS : PENERAPAN SMART CITY DALAM SISTEM INFORMASI DESA Yan Kurniawan; Gunawan Gunawan; Wresti Andriani
Biner : Jurnal Ilmiah Informatika dan Komputer Vol 2 No 2 (2023): Juli
Publisher : Program Studi Teknik Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Sains Al-Qur'an

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

Penerapan konsep Smart City dalam sistem informasi desa telah menjadi fokus utama dalam upaya meningkatkan efisiensi, partisipasi masyarakat, dan keberlanjutan di wilayah pedesaan. Artikel ini menyajikan sebuah tinjauan pustaka sistematis yang bertujuan untuk menggali informasi mengenai penerapan Smart City dalam sistem informasi desa. Tinjauan pustaka ini dilakukan dengan melakukan pencarian dan analisis literatur yang relevan yang telah diterbitkan dalam jurnal-jurnal ilmiah dan konferensi yang sesuai. Melalui pendekatan ini, kami berhasil mengidentifikasi artikel-artikel yang membahas konsep Smart City, infrastruktur teknologi, aplikasi cerdas, partisipasi masyarakat, keberlanjutan, dan tantangan yang terkait. Meskipun banyak penelitian telah dilakukan tentang implementasi Teknologi Informasi dan Komunikasi (TIK) di desa, namun fungsi TIK masih sebatas sebagai pendorong. Oleh karena itu, penelitian ini memiliki tujuan penting untuk mengisi kekosongan tersebut dengan mengembangkan sebuah model konseptual Smart City dalam Sistem Informasi Desa. Model konseptual ini dibangun berdasarkan tinjauan pustaka yang dilakukan pada jurnal-jurnal yang terpercaya seperti Google Scholar, Emerald Insight, Elsevier, dan IEEE Explore dengan menggunakan kata kunci "smart village", "smart rural", dan "sustainable village". Hasil tinjauan pustaka ini menunjukkan bahwa penerapan Smart City dalam sistem informasi desa memiliki potensi besar untuk meningkatkan efisiensi pelayanan publik, pengelolaan sumber daya, dan kualitas hidup masyarakat desa. Namun, terdapat tantangan seperti kebutuhan akan infrastruktur teknologi yang memadai, ketersediaan akses internet, pemastian privasi dan keamanan data, serta partisipasi masyarakat yang aktif. Artikel ini memberikan gambaran komprehensif tentang penerapan Smart City dalam sistem informasi desa. Diharapkan tinjauan pustaka ini dapat menjadi sumber referensi bagi pembaca dalam memahami manfaat, tantangan, dan peluang yang terkait dengan implementasi Smart City dalam konteks desa. Selain itu, tinjauan pustaka ini juga memberikan dasar yang kuat untuk penelitian dan pengembangan lebih lanjut dalam bidang ini.

Application of the Dijkstra method in finding the shortest route for hospitals in Kabupaten Tegal Gunawan Gunawan; Wresti Andriani; Khadziqul Humam Munfi
Jurnal Mandiri IT Vol. 12 No. 2 (2023): October: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v12i2.238

Health services are one of the most critical aspects of human life. Getting medical care quickly and efficiently can be a determining factor in saving a person's life in an emergency. In this article, we will review the application of the Dijkstra Method in finding the shortest route to Mitra Siaga hospitals in Kabupaten Tegal. This article is expected to contribute to understanding and developing a more efficient transportation system in Kabupaten Tegal, focusing on health services. Dijkstra algorithm for determining the shortest route. Dijkstra's algorithm is an algorithm that intends to find the shortest path on a graph. The principle of the Dijkstra Algorithm is searching for two passes with the most negligible weight. Based on the results of testing 10 times, the accuracy of this application is 100%. In this study, limited to the initial location tested, this application has not used the current location at its initial location. For the development of this application, you can use the current location at the initial location so that this application runs optimally

ANALISIS PENGARUH DIMENSI GAMBAR PADA KLASIFIKASI MOTIF BATIK DENGAN MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Syefudin Syefudin; Muchamad Nauval Azmi; Gunawan Gunawan
Jurnal Sistem Informasi dan Informatika (Simika) Vol 6 No 2 (2023): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v6i2.2675

This study focuses on the classification of batik patterns using image data, specifically with three classes: kawung, parang, and pekalongan batik patterns. A total of 180 images were used for the research, divided equally among the three motifs. The dataset was collected through observations from Google. Data preprocessing involved two stages. In the first stage, the data was split into training and validation sets, with a 70% - 30% ratio, respectively. This separation allowed for evaluating the model's performance and generalization ability on unseen data. In the second stage, the Image Data Generator library was utilized to enhance data diversity and improve the model's ability to generalize patterns. Data augmentation techniques, such as rotation, shear, zoom, horizontal flip, and shift, were applied to the training data. The augmented data was then fed into a pre-defined Convolutional Neural Network (CNN) architecture. The CNN model processed the input data through convolutional layers with max pooling and ReLU activation functions. The outputs from the first convolutional layer were used as inputs for subsequent convolutional layers. The resulting feature maps were flattened and passed through fully connected layers for classification. The model's performance was assessed by evaluating accuracy measures. The CNN model achieved the highest accuracy of 98% on the training data and 100% on the validation data after 7 epochs.. The implementation was done using Python programming language and the Google Colab platform, along with required libraries. Model evaluation involved assessing the trained model's performance by inputting test data and computing evaluation metrics, including accuracy, precision, recall, and F1-score. Confusion matrix analysis provided insights into true positive, true negative, false positive, and false negative predictions. The classification report summarized the performance metrics of the model. In conclusion, the CNN method proved effective in classifying batik patterns. The size of the input images significantly influenced the accuracy of the model. A 148x148 pixel image size yielded 100% accuracy. As a suggestion, future research should consider using a larger dataset to maximize the accuracy of the classification model.

PENERAPAN QR-CODE UNTUK APLIKASI INVENTARIS DENGAN METODE RAPID APPLICATION DEVELOPMENT Rifki Dwi Kurniawan; Dwi Fina Fahirah; Gunawan Gunawan
Jurnal Review Pendidikan dan Pengajaran (JRPP) Vol. 6 No. 4 (2023): Volume 6 No 4 Tahun 2023
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jrpp.v6i4.21520

Penelitian ini bertujuan untuk meningkatkan optimalisasi pemanfaatan SMK YPE Nusantara Slawi melalui Penerapan QR-Code untuk Aplikasi Inventaris dengan Metode Rapid Application Development (RAD). Sekolah ini, meskipun memiliki kondisi yang memadai, masih mengalami kesulitan dalam melacak perpindahan barang tanpa sepengetahuan pengelola. Dalam rangka mempermudah pencarian data inventaris, penelitian ini mengusulkan penggunaan teknologi QR-Code untuk mengotomatiskan dan memvalidasi data inventaris. Metodologi RAD dipilih sebagai pendekatan pengembangan sistem, dikenal efektif dalam konteks pengembangan aplikasi. Sistem yang dihasilkan diharapkan mampu mengumpulkan data inventaris dan menghasilkan laporan dengan menggunakan QR-Code yang akan ditempatkan pada barang-barang seperti komputer, printer, meja, kursi, dan sebagainya. Melalui hasil scan QR-Code, informasi yang ditampilkan mencakup username, tanggal, spesifikasi atau merk produk, serta lokasi barang tersebut. Implementasi QR-Code di SMK YPE Nusantara Slawi diharapkan dapat meningkatkan efisiensi, ketepatan, dan transparansi dalam melacak serta mengelola aset sekolah. Dengan demikian, penerapan QR-Code sebagai bagian dari sistem inventarisasi akan memberikan kontribusi positif terhadap manajemen barang dan data di lingkungan sekolah.

Implementation of sugeno fuzzy method on bandwidth management at STMIK YMI Tegal Gunawan Gunawan; Wresti Andriani; Dodi Setiawan
Jurnal Mantik Vol. 7 No. 3 (2023): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v7i3.4145

In the lecture process, the Internet becomes very important, and access settings or bandwidth management is needed so that Internet use can run smoothly. Many users can cause the burden of computer access to be high, so internet use will be unbalanced if bandwidth management is not carried out. Bandwidth management aims to allocate bandwidth in an internet network so that the distribution is equal and the comfort between users and one another is not disturbed. The method used is fuzzy Sugeno to implement Sugeno's fuzzy logic into bandwidth management and optimize internet usage. Fuzzy inputs used include download, streaming, and browsing variables. Using three fuzzy sets, namely low, standard, and solid. The output is Download Limit, Streaming Limit, and Browsing Limit. System testing will be conducted using MATLAB. After testing, results were obtained through bandwidth limits from downloading, streaming, and browsing. One of the study's results included a given system input download = 700, streaming = 668, and browsing = 611. Produce output is Download Limit = 700, Streaming Limit = 481, and Browsing Limit = 319

Comparison of banking stock price movements using KNN and Linier Regresi methods Wresti Andriani; Gunawan; Sawavyya Anandianskha
Jurnal Mantik Vol. 7 No. 3 (2023): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v7i3.4304

Stock price movements are a reflection of various situations and factors such as economics, politics and markets. Influencing factors such as economic news both foreign and domestic such as monetary policy, changes in interest rates and political events such as general elections. Indonesian politics is currently holding a general election process, the Presidential election can influence stock movements. Causing investors to be more careful about investing in this case in banks in Indonesia that have state-owned status, such as BTN, BRI, BNI and Bank Mandiri. This research predicts stock price movements using the Linear Regression method compared to the k-NN method, to find the best evaluation results from the two methods in selecting banks that are more profitable and do not influence political process factors. The results obtained were that Bank Mandiri was safer and promised profits using the Linear Regression method which was better than k-NN with RMSE 281,012, MAE 97,909 and MSE 80348,873. Bank Mandiri is safer and promises profits

Digital Marketing Efforts to Improve Products of Micro Small and Medium Enterprises (UMKM) in Tegal Nugroho Adhi Santoso; Bangkit Indarmawan Nugroho; Aang Alim Murtopo; Sarif Surorejo; Gunawan Gunawan
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3646

Digital marketing is promotional activities and market search through the media digitally online by utilizing various means such as social networks. The aim of this research is to increase knowledge and skills about digital marketing, especially social media, for Small and Medium Enterprises (SME) business people to increase their sales and profits. Digital marketing is the use of social media networks to carry out promotional activities and map digital markets. By using computers or other electronic equipment, digital marketing ideas can bring together geographically diverse parties. The aim of this research is to identify the most effective digital marketing tactics for the growth of MSMEs in Tegal City and Tegal Regency. The method used in this research is descriptive qualitative. With Data collection through observation, interviews, and secondary sources, such as books, journals, and articles, were used to collect information for this research. The results of this research show that the productivity growth of MSMEs in Tegal City and Tegal Regency has not been positive. Even when a website for an online business has been created, not everyone has implemented a digital marketing plan. It can be seen that digital marketing strategies have not received much attention from MSMEs in Tegal City and Tegal Regency. So it is hoped that MSMEs in Tegal City and Tegal Regency can adapt to changing times, namely selling online using digital marketing strategies.

Application of the Dijkstra method in finding the shortest route for hospitals in Kabupaten Tegal Gunawan Gunawan; Wresti Andriani; Khadziqul Humam Munfi
Jurnal Mandiri IT Vol. 12 No. 2 (2023): October: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v12i2.238

Health services are one of the most critical aspects of human life. Getting medical care quickly and efficiently can be a determining factor in saving a person's life in an emergency. In this article, we will review the application of the Dijkstra Method in finding the shortest route to Mitra Siaga hospitals in Kabupaten Tegal. This article is expected to contribute to understanding and developing a more efficient transportation system in Kabupaten Tegal, focusing on health services. Dijkstra algorithm for determining the shortest route. Dijkstra's algorithm is an algorithm that intends to find the shortest path on a graph. The principle of the Dijkstra Algorithm is searching for two passes with the most negligible weight. Based on the results of testing 10 times, the accuracy of this application is 100%. In this study, limited to the initial location tested, this application has not used the current location at its initial location. For the development of this application, you can use the current location at the initial location so that this application runs optimally

Evaluasi Model Deep Learning pada Pola Dataset Biomedis Gunawan, Gunawan; Wibowo, Septian Ari; Andriani, Wresti
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 14 No 2 (2024): September 2024
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v14i2.738

This study aims to evaluate the effectiveness and efficiency of various deep learning models in recognizing patterns within diverse biomedical datasets. The methods involved the collection of biomedical data from various public and synthetic sources, including chest radiographs, MRI, CT scans, as well as electrocardiogram (ECG) and electromyography (EMG) signals. The data underwent preprocessing steps such as normalization, noise removal, and data augmentation to improve quality and variability. The deep learning models evaluated included Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), which were trained to identify patterns within the data. The performance evaluation was conducted using metrics like accuracy, sensitivity, specificity, and AUC to ensure the models' generalization capabilities on test datasets. The results revealed that CNNs excelled in medical image analysis, particularly in terms of accuracy and interpretability, while RNNs were more effective in handling sequential data such as medical signals. The primary conclusion of this study is that the selection of deep learning models should be tailored to the type of data and specific application requirements, emphasizing the importance of improving model interpretability and generalization for broader applications in clinical settings.

Application of machine learning for short-term climate prediction in Indonesia Gunawan, Gunawan; Andriani, Wresti; Aimar Akbar, Aminnur
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5215

This study explores the Application of Machine Learning for Short-Term Climate Prediction in Indonesia, focusing on enhancing forecast accuracy through advanced computational models. The primary objective was to develop and validate Random Forest and Support Vector Machine (SVM) models to predict short-term climate conditions accurately across ten major Indonesian cities. Employing a quantitative approach, the study utilized experimental design, rigorous data analysis, and model validation using historical weather data from April 2024 provided by the Indonesian Meteorological, Climatological, and Geophysical Agency (BMKG). The results indicate that both Random Forest and SVM significantly outperform traditional climate prediction models, with Random Forest achieving an average accuracy of 87.5% and SVM 85.2%. These findings underscore the potential of machine learning to revolutionize short-term climate predictions in regions with complex meteorological dynamics like Indonesia, offering substantial implications for disaster preparedness, agricultural planning, and urban management. Future research can expand upon these models by incorporating real-time data and exploring deep learning techniques to enhance predictive reliability further

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