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RAINFALL PREDICTION USING SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE AND GEOGRAPHIC INFORMATION SYSTEM APPROACH
Get PDFRainfall is one indicator to determine the estimated adequacy of groundwater on agricultural land. The groundwater availability produced by rain can determine cropping patterns in an area. The availability of rainfall data depends on the accuracy of information on current climate conditions. This case causes the related parties to find difficulty determining the classification of cropping patterns in the future. Accurate rainfall prediction models are needed to overcome the problem of shifting rain patterns. Rainfall prediction models in determining cropping patterns are recommended by FAO, such as linear regression, which is still widely used today. This study aims to develop a new model of rainfall prediction by using the method SARIMA to determine cropping patterns to increase crop yields. Rainfall data was used from 2010 to 2020 from seven rainfall collection stations in Sleman Regency, and they are used as training data to predict future rainfall. The output of the data analysis is a prediction of rainfall in the range of January-April, which is predicted to be high, May-August, which is predicted to be low; and September-December, which is predicted to be moderate. In addition, based on the identified cropping patterns, recommendations can be given to farmers to set cropping schedules and strategies to increase the productivity of the farmland. The testing of accuracy forecasting used relative mean absolute error (RMAE) for 12 months. The results of the forecasting accuracy test for 12 months in Sleman Regency showed RMAE average of 1.46 was considered low, for it was still below 10%
PENENTUAN KELAYAKAN BANGUNAN CAGAR BUDAYA MENGGUNAKAN METODE SIMPLE MULTI ATTRIBUTE RATING TECHNIQUE (SMART)
Get PDFAbstractβ Nowadays, awareness of the importance of cultural heritage is decreasing among the public, especially among youth who will become leaders and inherit the culture of their region. Law Number 11 of 2010 stipulates the importance of protecting and preserving cultural heritage because it has significant value in history, science, education, religion and culture. Therefore, the existence of cultural heritage must be considered and maintained properly according to applicable regulations. There are several criteria for assessing buildings that will be used as cultural heritage according to Law number 11 of 2010 in Chapter III, article 5, cultural heritage criteria, namely the age of the building, historical value, cultural value and architectural value. This study aims to create a system that can determine the feasibility of a building as a cultural heritage in a precise and accurate way (case study DISPORAPARBUD Purwakarta). In this study, the Simple Multi Attribute Rating Technique (SMART) method was used in the Decision Support System (SPK). The results of this study are to produce recommendations for buildings that are worthy of being cultural heritage in accordance with predetermined criteria, namely the Normal School building with a value of 1 by occupying the first rank, which will then be recommended to the Purwakarta DISPORAPARBU
MENINGKATKAN POTENSI USAHA UMKM GAMBART MELALUI MEDIA SOSIAL
Get PDFThis research aims to explore the potential of TikTok social media utilization in improving the business of MSMEs "GambArt". One of the problems faced is the lack of knowledge of partner employees and owners regarding the application of information technology as a support system in the production process. Therefore, this research aims to see the increased business potential of MSMEs "GambArt" in supporting marketing effectiveness and efficiency. In this research, a qualitative descriptive method is used to get an overview of the application concept using a design thinking approach. This design thinking approach includes the stages of Empathize, Define, Ideate, Prototype, and Test. The results show that TikTok social media is an effective medium in showcasing the art products of MSMEs "GambArt" through interesting and creative short video content. This allows "GambArt" MSMEs to attract the attention of a wider audience, increase brand awareness, and expand the network of potential customers.The implications of this research can help similar MSMEs in utilizing TikTok social media as an effective tool to expand their reach and increase business growth. In order to support this, we created social media accounts such as TikTok and Instagram to help "GambArt" MSMEs to reach their full potential. With a presence on these platforms, it is expected that "GambArt" MSMEs can connect with more potential customers, expand their market share, and optimize their overall business performance.Penelitian ini bertujuan untuk menggali potensi pemanfaatan media sosial TikTok dalam meningkatkan usaha UMKM "GambArt". Salah satu permasalahan yang dihadapi adalah kurangnya pengetahuan pegawai mitra dan pemilik terkait penerapan teknologi informasi sebagai sistem pendukung dalam proses produksi. Oleh karena itu, penelitian ini bertujuan untuk melihat peningkatan potensi usaha UMKM "GambArt" dalam mendukung efektivitas dan efisiensi pemasaran. Dalam penelitian ini, digunakan metode deskriptif kualitatif untuk mendapatkan gambaran konsep aplikasi dengan menggunakan pendekatan design thinking. Pendekatan design thinking ini mencakup tahapan Empathize, Define, Ideate, Prototype, dan Test. Hasil penelitian menunjukkan bahwa media sosial TikTok menjadi media yang efektif dalam memamerkan produk seni UMKM "GambArt" melalui konten video pendek yang menarik dan kreatif. Hal ini memungkinkan UMKM "GambArt" untuk menarik perhatian audiens yang lebih luas, meningkatkan kesadaran merek, dan memperluas jaringan pelanggan potensial. Implikasi dari penelitian ini dapat membantu UMKM sejenis dalam memanfaatkan media sosial TikTok sebagai alat yang efektif untuk memperluas jangkauan dan meningkatkan pertumbuhan bisnis. Dalam rangka mendukung hal tersebut, kami menciptakan akun media sosial seperti TikTok dan Instagram untuk membantu UMKM "GambArt" agar dapat mencapai potensi maksimal. Dengan adanya kehadiran di platform-platform tersebut, diharapkan UMKM "GambArt" dapat terhubung dengan lebih banyak pelanggan potensial, memperluas pangsa pasar, dan mengoptimalkan kinerja bisnis mereka secara keseluruha
IMPLEMENTASI TEKNOLOGI INFORMASI RESOURCE UPAYA PENINGKATAN LAYANAN DAN MANAJEMEN DATA PERKUBURAN KEPADA MASYARAKAT
Get PDFThe Badan Pengelola Perkuburan Islam (BPPI) is an organization that manages cemeteries and provides burial service facilities to the community. BPPI in managing cemetery data experiences problems in data management and cemetery information service facilities are not updated and are slow. The facts found by the PKM team when visiting BPPI were the lack of data management knowledge and skills in using information technology to manage data and service facilities for the community. These findings prove that BPPI has not implemented information technology in managing cemetery data. Based on these findings, the implementing team has prepared a series of activities using structured training and mentoring methods through Community Based Empowerment (PBM) activities. PBM activities are expected to optimize the application of resource information technology and data management training with information technology as an effort to increase the knowledge and skills of BPPI administrators in managing cemetery data. By implementing hybrid-based resource information technology, administrators are helped in managing cemetery data management and the public can use hybrid-based applications to search and find information on cemetery locations online so that cemetery information services are provided more quickly and accurately. The results that have been achieved from PBM activities are an increase in knowledge by 81.93% and an increase in skills for BPPI administrators by 74.37%
FACE DETECTION PADA GAMBAR DENGAN MENGGUNAKAN OPENCV HAAR CASCADE
Get PDFAbstractβOpenCV has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. It has been proven by software companies, that is why the researcher will use it for face detection application with Java programming langguage. The purpose of this paper is trying to implement machine learning library OpenCV with Haarcascade algorithm to detect face from an image and to find the weaknesess of haarcascade algorithm. Haar cascade is proven still relliable to detect face.
Abstrakβ OpenCV memiliki lebih dari 2500 algoritma yang sudah dioptimisasi untuk digunakan dalam computer vision dan pembelajaran mesin. Karena keberhasilannya yang sudah dibuktikan oleh banyak perusahaan perangkat lunak, maka peneliti akan menggunakannya untuk aplikasi face detection dengan menggunakan bahasa pemrograman Java. Tujuan dari artikel ini adalah untuk mencoba menerapkan library pembelajaran mesin OpenCV algoritma Haar cascade untuk mendeteksi wajah pada sebuah gambar dan untuk mencari kelemahannya. Haar cascade telah terbukti masih cukup handal dalam mendeteksi wajah
PELATIHAN DASAR PERANCANGAN WEB STATIS DAKWAH MENGGUNAKAN HTML5 DI RUMAH TAHFIDZH DAAR EL HUFFADZH
Get PDFUntuk membentuk SDM yang memiliki integritas yang tinggi tidak bisa dibuat secara instan, namun dibutuhkan waktu yang cukup lama. Salah satu bentuk wadah pendidikan yang diharapkan dapat menciptakan SDM yang memiliki integritas yang tinggi terhadap norma agama dan sosial salah satunya yaitu Rumah Tahfidzh. Rumah Tahfidz Qurβan adalah lembaga dengan aktivitas belajar dan menghafal Al-Qurβan, mengamalkan, dan membudayakan nilai-nilai Al -Qurβan dalam sikap hidup sehari-hari berbasis hunian, lingkungan, dan komunitas. Para santri Rumah Tahfidzh Daar El Huffadzh sehari-harinya dari subuh hingga malam hari berfokus mempelajari ilmu-ilmu dibidang A-Qurβan, seperti tajwid, Bahasa Arab, balaghoh, fikih dan lainnya. Dikarenakan Rumah Tahfidzh Daar El Huffadzh tidak dapat mengeluarkan ijazah formal yang diakui oleh pemerintah sebagaimana MTS atau Aliyah, maka para santri setelah menempuh pendidikan di Rumah Tahfidzh Daar El Huffadzh diharapkan dapat memiliki keterampilan lain agar dapat bersaing mendapatkan pekerjaan di kemudian hari. Keterampilan yang bersifat softskill dapat dikembangkan melalui pelatihan yang dilakukan oleh lembaga-lembaga tertentu. Atas permasalahan yang ada maka kami memutuskan untuk melakukan kegiatan pengabdian masyarakat dalam bentuk pelatihan pada para santri di Rumah Tahfidzh Daar El Huffadzh. Tujuan umum dari kegiatan pengabdian masyarakat ini yaitu memberikan keterampilan kepada santri di bidang teknologi informasi. Dengan harapan santri bisa memiliki kemampuan untuk menyelesaikan permasalahan dengan logika dan penalarannya. Dan pada akhirnya para santri termotivasi untuk mendalami pemrograman web lebih lanjut, hingga kedepannya mereka dapat membuat website untuk mendukung dakwahnya. Berdasarkan evaluasi yang sudah dilaksanakan, kegiatan pengabdian masyarakat ini dapat berjalan dengan baik sesuai dengan perencanaan yang telah disusun dan juga para peserta mampu untuk memahami semua materi yang diberika
PREDICTION PERFORMANCE OF AIRPORT TRAFFIC USING BILSTM AND CNN-BI-LSTM MODELS
Get PDFThe COVID-19 pandemic has had a significant and enduring impact on the aviation industry, necessitating the accurate prediction of airport traffic. This study compares the predictive accuracy of biLSTM (Bidirectional Long Short-Term Memory) and CNN-biLSTM (Convolutional Neural Network-Bidirectional Long Short-Term Memory) models using various optimization techniques such as RMSProp, Stochastic Gradient Descent (SGD), Adam, Nadam, and Adamax. The evaluation is based on Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) indices. In the United States, the biLSTM model utilizing the Nadam optimizer achieved an MAPE score of 9.76%. On the other hand, the CNN-biLSTM model utilizing the Nadam optimizer demonstrated a slightly improved MAPE score of 9.62%. For Australia, the biLSTM model using the Nadam optimizer obtained an MAPE score of 31.52%. However, the CNN-biLSTM model employing the RMSprop optimizer had a marginally higher MAPE score of 33.33%. In Chile, the biLSTM model using the Adam optimizer obtained an MAPE score of 44.04%. Conversely, the CNN-biLSTM model using the RMSprop optimizer had a slightly higher MAPE score of 44.09%. Lastly, in Canada, the biLSTM model using the Nadam optimizer achieved a comparatively low MAPE score of 14.99%. Similarly, the CNN-biLSTM model utilizing the Adam optimizer demonstrated a slightly better MAPE score of 14.75%. These results highlight that the choice of optimization technique, model architecture, and balanced dataset can significantly influence the prediction accuracy of airport traffic
PREDICTING MARKET SEGMENTS FROM TWITTER DATA USING ARIMA TIME SERIES ANALYSIS
Get PDFTwitter data on social media can be used to predict potential market segments in the future. The continuous nature of Twitter data and data collection sequentially over a certain period uses a text mining process with time series data that matches the actual data. The problem to be solved is to forecast market segments using Twitter data with greater accuracy. Various market segments that are of business interest through the tweets of individual Twitter users have not been utilized optimally. Based on the Twitter data pattern, the research shows that the data pattern is not stationary, so to analyze the data, it is necessary to use the Autoregressive Integrated Moving Average (ARIMA) method. This study aims to analyze time series data from Twitter data and predict market segment predictions using the ARIMA method. The ARIMA method is a method that has advantages in flexibility, the ability to handle stationary and non-stationary data, as well as short-term forecasting with a statistical approach in various time series data forecasting applications. Prediction results using the ARIMA method with an accuracy rate of 94.88%. There are several ways to measure model validation including MAD, MSE, RMSE, F1-Score, and MAPE. In this study, MAD, MSE, and MAPE were used with an accuracy rate of 5.22%. This study succeeded in applying the ARIMA method to time series data from Twitter to forecast market segments with high accuracy, opening opportunities for utilizing Twitter data in business strategy
KLASIFIKASI TIPE BERAT TUBUH MENGGUNAKAN METODE SUPPORT VECTOR MACHINE
Get PDFAbstractβThe news of the death of a man in Indonesia is in the public spotlight because doctors have difficulty treating his illness because being overweight or obese causes the organs in the body to fail to function properly. Overweight causes the body to experience several health problems, including heart defects, diabetes, and several other diseases that can attack vital organs in the body. According to data on deaths caused by obesity, there are as many as 60 per 100,000 Indonesian population, and are a very feared killer. Faster handling of recognizing our body weight is important for each individualβs health. Classification can also help overweight in a person known more quickly. In this study, the classification algorithm that will be used is the Support vector machine (SVM). With 252 data, this study will use the SVM algorithm and look for the level of accuracy of the two classification classes, namely normal and overweight. This study produces an accuracy rate of 92.11% with a ROC curve value of 0.990 which means that the classification in this study is very good
IMPLEMENTATION OF WEIGHTED PRODUCT METHOD IN DETERMINING SELECTION THE BEST MUSIC STREAMING SERVICE APPLICATION
Get PDFAt this time, the music streaming service is a platform that is often easily found on every device, either through downloads from the Playstore and Appstore or the default application from the device itself. Many companies in the world are competing to create platforms and applications that provide the most complete songs. For example, several well-known music streaming service applications in Indonesia have their own innovations and characteristics, such as Spotify, Joox, Youtube Music, Apple Music, SoundCloud, and so on. This causes users to have difficulties because of several considerations in deciding how to use the application according to their needs. This study aims to assist in providing solutions to music streaming service subscribers by recommending several music streaming service applications according to the ranking results, which are the best choice for the user version of the application through a Decision Support System using the Weighted Product method based on 5 criteria: subscription rates, available features, streaming quality, music, application design, and application efficiency. The final result of this study is the ranking of applications that have the highest score in accordance with the criteria provided, namely that in first place with a value of 0.415 is Spotify as a recommendation for the best music streaming service application, and Apple Music ranks last out of the 6 alternatives that have been provided