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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Inotera Jurnal Riset Informatika Santika : Jurnal Ilmiah Sains dan Teknologi Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Jurnal Pengabdian Kepada Masyarakat Abdi Putra
Nunik Destria Arianti
Universitas Nusa Putra
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Public Health Other

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DESIGN OF WEB-BASED VIRTUAL TOURISM INFORMATION SYSTEM AT GEOPARK CILETUH SUKABUMI Elsa Ramadanti; Muhamad Muslih; Nunik Destria Arianti
Jurnal Riset Informatika Vol. 4 No. 3 (2022): June 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v4i3.177

Abstract

Geopark Ciletuh Sukabumi is an earth park with biodiversity such as geological, social, and cultural elements, to locations for research and tourism. Tourist destinations in the Ciletuh Geopark include waterfalls, beaches, mountain peaks, islands, cultural tourism, and biodiversity. Due to the lack of information media about tourist objects in the Ciletuh Geopark, not many tourists visit to enjoy the beauty of natural attractions and local cultural wisdom still maintained at the Ciletuh Geopark. Based on these problems, research was conducted to design and build a tourist information system with a virtual tour feature based on the Geopark Ciletuh Sukabumi website. In this study, the author designed the system using the Zachman Framework system development method and was built using CMS WordPress and Page Builder as well as PHP and MySQL programming languages. Testing the Virtual Tourism Information System at the Ciletuh Sukabumi Geopark using Blackbox Testing. The results of the design of a web-based virtual tourist information system at the Ciletuh Sukabumi Geopark can be used as a medium of tourist information for the general public and visitors who will travel to the tourist attraction.
Comparison of feature extraction and auto-preprocessing for chili pepper (Capsicum Frutescens) quality classification using machine learning Asian, Jelita; Arianti, Nunik Destria; Ariefin, Ariefin; Muslih, Muhamad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i1.pp319-328

Abstract

The low-cost camera for machine vision, such as a webcam, still has a problem with resolution noise. Therefore, it is important to learn strategies to reduce noise from low-cost camera images so that they can be widely used for grading machines in the future. This paper aims to compare three feature extraction methods with auto-preprocessing to classify chili pepper (Capsicum Frutescens) quality using a machine learning algorithm. Three extraction methods were used, including the color feature, oriented FAST and rotated BRIEF (ORB), and the combination color feature and ORB. A total of 525 image data for quality chili pepper were collected using the webcam. The auto-preprocessing strategy to classify chili peppers can improve the performance of machine-learning algorithms for all data generated by the feature extractor. The performance of the chili paper quality classification model with auto-preprocessing of the variable color feature can improve the performance of machine learning algorithms by up to 64.21%. The performance improvement of the classification model using the ORB feature variable and the auto-preprocessing of up to 4.41%. The performance improvement of the classification model using machine learning algorithms is 11.27% when using the combination color feature and ORB feature and auto-preprocessing.
Implementation of Multiple Linear Regression Algorithm to Predict Air Temperature Based on Pollutant Levels in South Tangerang City Tedja Diah Rani Octavia; Neny Rosmawarni; Ati Zaidiah; Nunik Destria Arianti
Jurnal Inotera Vol. 9 No. 2 (2024): July - December 2024
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol9.Iss2.2024.ID383

Abstract

Global warming is a phenomenon that has widespread effects, particularly on environmental aspects. Globally, the impact of global warming is evident in the rising temperatures of the Earth. In April 2023, much of South Asia experienced a heatwave with temperatures exceeding 40°C. In Indonesia, the daily maximum temperature recorded reached 37.2°C in South Tangerang City. Global warming is caused by the increasing concentration of greenhouse gases in the Earth's atmosphere. This study proposes a model for predicting air temperature by considering the influence of pollutant levels and daily climate data in South Tangerang City. The prediction modeling in this study uses the Multiple Linear Regression algorithm with an 80% training data and 20% testing data split. Out of 8 trials, the sixth model is the best with a k value of 8 and features including RH_avg, RR, ss, ddd_car, ff_avg, no2, o3, and pm10. The evaluation results of the sixth model yielded an R² value of 0.72749, MAE of 0.55593, MSE of 0.50078, and MAPE of 1.99806%.
Kolaborasi Mahasiswa dalam Pengabdian Masyarakat Di Desa Argapura Kecamatan Cigudeg Kabupaten Bogor Jihan Sopyana; Mohamad Najib; Ainaya Arasya Aulia; Kurniawan; Nunik Destria Arianti; Muhamad Muslih
Jurnal Pengabdian Kepada Masyarakat Abdi Putra Vol 4 No 1 (2024): Januari 2024
Publisher : Universitas Nusa Putra & Persatuan Insinyur Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/abdiputra.v4i1.182

Abstract

Community service is an activity that aims to help the community in several activities without expecting anything in return. Community Service Activities are one part of the Tri Dharma of Higher Education. The purpose of holding student collaboration in community service is to hone soft skills and partnerships, cross-disciplinary or scientific team collaboration (cross-competence) and student leadership in managing development programs in rural areas. Facilitating students to apply their knowledge in solving problems at the village level. Forming attitudes and feelings of love, social care, and student responsibility for the progress of society. The service targets cover several aspects, including the implementation of participation in village government, family assistance, school programs, entrepreneurship, professors' seminars, and commemoration of the Republic of Indonesia's Independence Day. During service students are taught to be critical in various matters and learn problem solving that occurs in the community. Argapura Village is a village with a lot of potential, with several programs that we have implemented to make Argapura Village even more developed.
Transformers in Machine Learning: Literature Review T, Thoyyibah; Haryono, Wasis; Zailani, Achmad Udin; Djaksana, Yan Mitha; Rosmawarni, Neny; Arianti, Nunik Destria
Jurnal Penelitian Pendidikan IPA Vol 9 No 9 (2023): September
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i9.5040

Abstract

In this study, the researcher presents an approach regarding methods in Transformer Machine Learning. Initially, transformers are neural network architectures that are considered as inputs. Transformers are widely used in various studies with various objects. The transformer is one of the deep learning architectures that can be modified. Transformers are also mechanisms that study contextual relationships between words. Transformers are used for text compression in readings. Transformers are used to recognize chemical images with an accuracy rate of 96%. Transformers are used to detect a person's emotions. Transformer to detect emotions in social media conversations, for example, on Facebook with happy, sad, and angry categories. Figure 1 illustrates the encoder and decoder process through the input process and produces output. the purpose of this study is to only review literature from various journals that discuss transformers. This explanation is also done by presenting the subject or dataset, data analysis method, year, and accuracy achieved. By using the methods presented, researchers can conclude results in search of the highest accuracy and opportunities for further research.
Co-Authors Achmad Udin Zailani Adhitia Erfina Adithia Erfina Ainaya Arasya Aulia Amelia Nurhalizah Anggy Pradiftha Junfithrana Ariefin, Ariefin Elsa Ramadanti falentino sembiring Fauziani Tanzil Gustian, Dudih Haryono, Wasis Jelita Asian Jihan Sopyana Jordan Chan William Kurniawan M.Iqbal Fauzi Melawati Melawati Melawati Mochamad Khilmi Mohamad Najib Muhammad Muslih Muhammad Rangga Abdurrasyid Muhammad Rifqi Abdul Jabbar Mukti Ginanjar Mupaat Muslih, Muhamad Muthia Meisya Lavil Neng Resti Wardani Neng Sri Intan Septiani Neny Rosmawarni Nita Juliana Oscar Haris Ramdani Amarulloh Rida Ista Stepu Saepudin, Sudin Saepul Ihsan T, Thoyyibah Tedja Diah Rani Octavia Utomo Widiastuti Angraini Wowon Yan Mitha Djaksana Yudi Nata Yusuf Iskandar Zaidiah, Ati Zuliana Dwi Takari