PREDIKSI NILAI EMAS MENGGUNAKAN ALGORITMA REGRESI LINEAR

Harga emas yang fluktuatif menjadi salah satu tantangan dalam melakukan investasi. Oleh karenanya, prediksi harga emas menjadi penting untuk investor dalam mengambil keputusan investasi yang tepat. Penelitian ini bertujuan untuk melakukan prediksi harga emas menggunakan algoritma regresi linear. Harga emas diprediksi berdasarkan beberapa faktor, seperti suku bunga, inflasi, dan harga minyak. Data harga emas selama beberapa tahun diambil sebagai sampel untuk analisis. Model regresi linear dibangun berdasarkan faktor-faktor tersebut dan hasilnya dianalisis untuk menentukan akurasi prediksi.  Pengumpulan data dilakukan dengan mencari data histori harga emas melalui sumber website. Data yang dikumpulkan adalah harga emas, harga minyak bumi serta nilai dolar terhadap rupiah dari tahun 2019 hingga 2023, yang masing-masing sebesar 43 data.  Proses analisis data dilakukan menggunakan aplikasi RapidMiner. Hasil penelitian menunjukkan bahwa algoritma regresi linear  dapat digunakan untuk memprediksi harga emas di masa depan dengan perbandingan  metode evaluasi MAE sebesar 4341.140 lebih akurat dibanding menggunakan RMSE sebesar 4893.132. Variabel nilai mata uang dolar terhadap rupiah merupakan vaktor prnting yang bisa mempengaruhi pergerakan harga emas artinya menunjukkan model regresi linear dapat memberikan prediksi yang cukup akurat terhadap harga emas pada masa depan

Coastal Batik Motifs Identification Using K-Nearest Neighbor Based on The Grey Level Co-occurrence Method

Indonesia is a country rich in natural, cultural, and tourism resources. One of the famous human cultural heritage in Indonesia is batik. Batik has unique motifs that are very diverse so it is difficult to recognize the in certain classes. This research was conducted to classify coastal batik, especially Tegal batik, Pekalongan batik, and Cirebon batik so that it can help facilitate the introduction and understanding of coastal batik when compared to another batik, such as Yogyakarta batik. The method used is Grey Level Co-occurrence Matrices to extract texture features, while, to determine the proximity of the test image to the training data using the K-Nearest Neighbor method, the calculation of the distance to be used is the Euclidean Distance and Manhattan Distance based on the texture characteristics of the batik image obtained. In this study, the highest score was obtained at 64% for Euclidean Distance and 66% for Manhattan Distance at k=1

Systematic Literature Review Implementation of the Internet of Things (IoT) in Smart City Development

Internet of Things (IoT) "The smart city concept has become a dream that big cities in Indonesia want to achieve, basically the smart city concept focuses on developing the human element using technology. IoT opens up many opportunities for new services by connecting the physical world and the virtual world to various electronic devices. IoT aims to leverage cutting-edge technology to support sustainable services for governments and their citizens. Systematic Literature Review (SLR) is one method in conducting an overview of previous interrelated researchers. The purpose of the literature study in this research is to understand trending research topics, methods, and architecture in the development of smart cities with IoT. In this study, various interesting information was found in various research journals regarding the role of IoT in building a smart city that has a role to serve smart city infrastructure, identify and analyze trends, develop smart cities and become innovations for IoT. Based on the research, there are things that need to be done to improve the study to focus more on the role of IoT that can be more utilized. IoT is also one of the technologies that are widely used in several countries in the development of IoT in the future. IoT in smart cities will become an inseparable technology because humans will increasingly depend on IoT in their daily live

Implementation Of Marker-Based Tracking Method On Augmented Reality In Multimedia Learning (Case Study Of STMIK Tegal)

Introducing campus locations for new students or address seekers is an important activity. Multimedialearning is not only a tool for creating harmonious presentations and alternatives that combine visualand audio media; technology can be used for its tools. Augmented Reality (AR) is one of them.Augmented Reality is helpful as a combination of virtual and Reality devices that operate interactivelyin a realtime natural environment. Based Marker Tracking is a method used to make objects into twodimensions and three dimensions whose process begins with directing the marking object by the userusing the camera on the mobile device until the camera reads the object. Light intensity affects detectionsuccess, and distance calculation also becomes essential. If the marker is successfully detected, theapplication will convert it into a 3-dimensional object as the final result. In this study, a location searchwill be carried out for the STMIK TEGAL Campus Building using Augmented Reality based on theBased Marker Tracking method to produce the most ideal conditions to be able to display 3D objectsfrom the STMIK TEGAL Building, which is a distance of 15 to 25 cm with bright Light using Android,so that this application can be used to find the location of the STMIK TEGAL Building

Implementation Of Marker-Based Tracking Method On Augmented Reality In Multimedia Learning (Case Study Of STMIK Tegal)

Introducing campus locations for new students or address seekers is an important activity. Multimedialearning is not only a tool for creating harmonious presentations and alternatives that combine visualand audio media; technology can be used for its tools. Augmented Reality (AR) is one of them.Augmented Reality is helpful as a combination of virtual and Reality devices that operate interactivelyin a realtime natural environment. Based Marker Tracking is a method used to make objects into twodimensions and three dimensions whose process begins with directing the marking object by the userusing the camera on the mobile device until the camera reads the object. Light intensity affects detectionsuccess, and distance calculation also becomes essential. If the marker is successfully detected, theapplication will convert it into a 3-dimensional object as the final result. In this study, a location searchwill be carried out for the STMIK TEGAL Campus Building using Augmented Reality based on theBased Marker Tracking method to produce the most ideal conditions to be able to display 3D objectsfrom the STMIK TEGAL Building, which is a distance of 15 to 25 cm with bright Light using Android,so that this application can be used to find the location of the STMIK TEGAL Building

DETEKSI HELMET DAN VEST KESELAMATAN SECARA REALTIME MENGGUNAKAN METODE YOLO BERBASIS WEB FLASK

Menurut ILO, setiap tahun ada lebih dari 250 juta kecelakaan di tempat kerja. Penyebab kecelakaan sebanyak 80% dikarenakan kelalaian yang dilakukan oleh pekerja yaitu perilaku tidak aman seperti tidak memakai APD. Perlunya pengawasan terhadap pekerja merupakan hal penting dalam mengurangi kecelakaan kerja. Namun pengawasan tersebut masih manual, sehingga akan memakan waktu lama. Metode yang dapat digunakan untuk pengenalan objek pada citra helmet dan vest keselamatan adalah deeplearning. YOLOv2 merupakan salah satu model deep learning yang dapat digunakan untuk pengenalan objek. Mengingatnya permasalahan tersebut, maka perlu dibuat sistem deteksi helmet dan vest secara realtime berbasis web flask. Tahapan pada penelitian ini diantara lain data acquisition atau pengumpulan data citra. selanjutnya data exprolation atau anotasi data citra, selanjutnya dilakukan Modelling atau training data, dan proses terakhir yaitu deployment menggunakan flask. sistem yang telah dibuat berhasil mendeteksi tidak menggunakan helmet dan vest keselamatan dengan bounding box merah dan menggunakan helmet dan vest keselamatan dengan bounding box hijau dengan akurasi rata rata 81.60% dan memiliki nilai avg loss 0.173 dan nilai validasi mAP (mean Average Precision) 76.68