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All Journal Jurnal Kewirausahaan dan Bisnis Journal of Robotics and Control (JRC) Frontiers JOINTER : Journal of Informatics Engineering Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Prosiding Konferensi Nasional PKM-CSR
Made Krisnanda
Universitas Negeri Manado
Aerospace Engineering Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology Mechanical Engineering Nursing Public Health Social Sciences Other

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Journal : JOINTER : Journal of Informatics Engineering

 1 
Pemodelan Mesin Pendeteksi Ujaran Kebencian di Sosial Media Indonesia Made Krisnanda
JOINTER : Journal of Informatics Engineering Vol 1 No 01 (2020): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

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Abstract

This research discusses the development of a model that can be used to detect hate speech in Indonesia's popular social media. Several methods are collected, analyzed, and implemented to build a framework that is practical and can be used to detect hate speech. The research methodology starts with the study of literature, analysis, and design of the model. From the analysis results, N-Gram, Word2vec, LSTM and emotion classification is used as part of the process of the model. This model consists of ten processes that are carried out sequentially so that comments collected through Facebook and Whatsapp social media can be identified when they contain hate speech. The model also considers the applicable law in Indonesia to facilitate the legal handling of perpetrators.
Sistem Lapor Dini Bencana Kebakaran Berbasis Mobile di Kota Bitung Abdul Fajar Duke; Made Krisnanda; Quido C. Kainde
JOINTER : Journal of Informatics Engineering Vol 1 No 01 (2020): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

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Abstract

Abstract—Fire is one of the disasters that comes difficult to predict, aside from being unwanted by the community, it is also often difficult to control if the fire already becomes large. As for the obstacles that often occur, firefighters are late getting fire reports and also difficulty in finding the location of fires due to lack of information. system development is done by the writer in this study using the Waterfall model (Presmann, 2010). system modeling is documented using DFD (Data Flow Diagrams). The results of this study are a mobile-based early fire disaster detection system with several features to overcome community problems in reporting a fire disaster and help firefighters to get an accurate location and the fastest route to the fire location.
Rancang Bangun Sistem Pariwisata Buton Tengah Berbasis Web satin la ruma; Olivia Kembuan; Made Krisnanda
JOINTER : Journal of Informatics Engineering Vol 3 No 02 (2022): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v3i02.100

Abstract

Central Buton is an area located in the Buton archipelago, Southeast Sulawesi which is a former heritage area of the Sultanate of Buton where the area has many natural and cultural tourist charms that must be preserved. This study aims to design and implement web-based tourism in Buton Tengah. The method used in the development of this application is Waterfall in which there are five namely Analysis, Design, Coding, Testing, and Implementation of Maintenance Programs, with the PHP programming language and Sublime Text 3. The result of the research is that the Central Buton Tourism system is website-based and has a service function, namely the function of providing tourist information, booking tickets, so that the sales system can be improved for the better. Testing this system using the Black Box testing method, so that it is able to answer and show that the system created is in accordance with the objectives of the researcher and is able to meet user needs.
PENGEMBANGAN E-LEARNING BERBASIS WEB DI SMA YADIKA LANGOWAN Klaudia Maki; Ferdinand I. Sangkop; Made Krisnanda
JOINTER : Journal of Informatics Engineering Vol 4 No 02 (2023): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v4i02.87

Abstract

E-learning is the utilization of information technology that is applied in the world of education by using electronic media so that learning can be accessed anywhere and anytime. The existence of e-learning is expected to help in the current teaching and learning process. Yadika Langowan High School is one of the high schools in East Langowan, where the teaching and learning process carried out at this school still uses conventional learning so that the teaching and learning process is still focused on learning in the classroom, this is also supported by the Covid-19 which caused the teaching and learning process is limited to only 50% of students who can attend school. This research aims to help the above problems by creating web-based e-learning at SMA Yadika Langowan as an addition or substitute for the current learning process. The method used in this research is Dynamic System Development Method (DSDM). The system modeling uses Unified Modeling Language (UML) modeling. The results of this research are a school website that is integrated with Moodle-based e-learning, for system testing using Blackbox testing and media expert validation.
Analisis Performa Autoregressive Integrated Moving Average Model dan Deep Learning Long Short-Term Memory Model untuk Peramalan Data Cuaca Montolalu, Vithiaz; Munaiseche, Cindy; Krisnanda, Made
JOINTER : Journal of Informatics Engineering Vol 5 No 02 (2024): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v5i02.112

Abstract

Weather is an aspect that cannot be separated from all activities carried out by humans, so information about the weather is very important. To meet the need for this information, it is necessary to do forecasting. Each data has its own characteristics, and choosing the right forecasting method is very important. The Autoregressive Integrated Moving Average (ARIMA) method is one of the popular statistical methods used in forecasting time-series data. Long Short-Term Memory (LSTM) is a modern deep learning algorithm model that is most suitable for forecasting time-series data. In this study, an analysis was carried out to compare the traditional ARIMA method and the deep learning model, namely LSTM, in forecasting weather data in Manado city to see the best forecasting model that can be used. The results of this study indicate that in terms of the accuracy of the 18 tests performed, the LSTM forecasting model is superior to the ARIMA model as measured by Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). In terms of computational time in making forecasting models for 6 weather data attributes, the LSTM model is faster than the ARIMA model.
Co-Authors Abdul Fajar Duke Cindy Pamela C Munaiseche Derek, Natan Ferdinand I. Sangkop Grace Jenny Soputan Juliana Ohy Klaudia Maki Mario Tulenan Parinsi Montolalu, Vithiaz Nova Ch Mamuaja Nova Ch. Mamuaya Olivia Kembuan Pratasik, Stralen Quido Conferti Kainde Radiansyah, Riva Satya Ronaldo Turang satin la ruma Turang, Ronaldo Yuri Pamungkas