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Jurnal Informatika dan Teknologi Komputer ( J-ICOM)
Published by Universitas Samudra
ISSN : 27752089     EISSN : 27747115     DOI : https://doi.org/10.33059/j-icom.v2i1.3417
Core Subject :
Jurnal J-ICOM (Jurnal Informatika dan Teknologi Komputer) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi. Jurnal J-ICOM (Jurnal Informatika dan Teknologi Komputer) menerima artikel ilmiah dengan lingkup penelitian pada: Rekayasa Sistem Sistem Pakar Sistem Penunjang Keputusan Data Mining Kecerdasan Buatan Jaringan Komputer Teknik Komputer Pengolahan Citra Algoritma Genetik Perancangan Sistem Informasi Business Intelligence and Knowledge Management Database System Big Data Enterprise Computing Cloud Computing Technology Management Topik kajian lainnya yang relevan Dengan artikel yang memiliki sitasi primer dan tidak pernah dipublikasikan secara online atau versi cetak sebelumnya.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 107 Documents
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Game Edukasi Berbasis Android Pengenalan Serangga Pada Anak Tunagrahita SLB Negeri Sukoharjo Rama, Rama Elian Zuldi; Al Irsyadi, Fatah Yasin
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 5 No 1 (2024): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v5i1.8127

Abstract

Mental Retardation refers to individuals with below-average intellectual or mental limitations caused by abnormalities in the brain's structure or function. They have deficits in adaptive behaviors such as daily living skills, social skills, language, and communication. Special care and support, including special education, are needed to enhance their development and quality of life. SLB Negeri Sukoharjo in Central Java provides special education for individuals with Mental Retardation, teaching basic skills, social skills, and life skills for future independence. Observations and interviews reveal that SLB still uses conventional learning media, leading to issues like students folding, tearing, and discarding paper-based materials. To address this, the author develops educational games as interactive learning media to promote active student participation and make the learning process more engaging for Mental Retardation students. The game, Jelajah Serangga, is designed using Construct2 software and the Game Development Life Cycle (GDLC) research method. It achieves an excellent rating with an SUS score of 85, indicating high quality. This game effectively supports learning at Sukoharjo State Special School.
Prediksi Banjir Di Dki Jakarta Dengan Menggunakan Algoritma K-Means Dan Random Forest Haris, Ruby; Haryo, Wasis; Wahyu Pujiharto, Eka; Yuza, Adela; Kusrini, Kusrini; Kusnawi, Kusnawi
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 5 No 1 (2024): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v5i1.8153

Abstract

This research aims to develop a flood prediction method that can be used to implement effective prevention and mitigation measures in dealing with frequent natural disasters in DKI Jakarta. The approach used in this study involves the utilization of Machine Learning techniques with a combination of K-Means and Random Forest algorithms. Historical data on water gates, water levels, and other relevant factors are used as inputs for the development of the flood prediction model. The K-Means method is employed to cluster the water level data, and the results of the K-Means clustering process are then used as parameters in the Random Forest method. A total of 20 experiments were conducted, varying the value of k from 1 to 20 in the K-Means algorithm. The experimental results show that the best accuracy and f-1 score were achieved at k=14, with an accuracy rate of 95% and an f-1 score of 90%. This indicates that the developed flood prediction model is capable of providing accurate and reliable predictions in identifying flood potential. This research holds significant implications for flood management in vulnerable cities. With an effective flood prediction method, prevention and mitigation measures can be implemented more efficiently, thereby reducing the negative impacts caused by floods.
Peningkatan Kinerja Chatbot NLP Asisten: Tinjauan Literatur tentang Metode dan Akurasi dalam Aplikasi Berbasis Percakapan Tri Khaqiqi, M. Ilyas; Harani, Nisa Hanum
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 5 No 1 (2024): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v5i1.8242

Abstract

Chatbots have been widely used in various industries such as e-commerce, banking, healthcare, and education to improve efficiency and provide 24/7 services to users. In the field of education, NLP chatbot brings the potential to improve soft skills and hard skills through online learning. This research aims to find suitable methods from previous research to be used in the creation of a conversational chatbot for supporting services of an application system. The research method used is Systematic Literature Review, with comprehensive journal search steps using appropriate keyword search strategies. The research results include 20 articles relevant to the topic of chatbot NLP assistants. The various methods identified in the research include machine learning, deep learning, rule-based approaches, and the use of third-party applications such as Dialogflow and IBM Watson. The analysis results show that the Dynamic Memory Network (DMN) method has the best performance with 91% accuracy. DMN combines the advantages of LSTM and Memory Network with a dynamic attention mechanism, allowing the model to focus on the most relevant information in sequential data. Although this study provides interesting findings, further research is needed to deal with the different characteristics and availability of data in various real-world scenarios. Thus, this article highlights the importance of continuously developing NLP chatbot technology for better applications and improved service quality for users. It is hoped that this article can contribute to the development of research related to NLP chatbot assistants in better and more efficient application systems.
ALGORITMA LEBAH, SOLUSI METAHEURISTIK DALAM PENEMUAN NILAI OPTIMAL PADA VARIABEL ALAT INDUSTRI Ginda Maruli Andi Siregar; Novianda; Nurul Fadillah
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 4 No 2 (2023): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v4i2.9013

Abstract

Heavy equipment or industrial machines have components that involve many variables. The performance of industrial heavy equipment depends on calculating the size of each component so that the machine works optimally. Determining the optimum value of machine component variables is needed so that the machine or industrial equipment can work optimally. The study carried out was to find the optimum variable values ​​for machines or industrial tools using a numerical-computational approach using the bee algorithm. The effectiveness and efficiency of the algorithm will be compared with other methods. The research uses a quantitative approach and is analyzed with statistical descriptions. Based on the results of this research, it is hoped that it can provide a reference for users of industrial equipment in obtaining optimum values. For researchers with similar topics, provides a reference for the application of the bee algorithm in determining function optimization values.
Arsitektur Enterprise Aplikasi SIP Menggunakan Kerangka Kerja Zachman Sugiyanto, Yanto; Shofia Hilabi, Shofa; Huda, Baenil
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 5 No 1 (2024): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v5i1.9665

Abstract

The Pension Information System (SIP) is a digital platform specifically designed for comprehensive and transparent management of pension information. In modern administration, administrative efficiency and transparency are very important to improve the quality of public services. Therefore, the development of an appropriate pension information system (SIP) has a strategic role in increasing the productivity and work efficiency of civil servants. Enterprise application architecture has become an important element in the development of complex information systems. In this research, we investigate the application of the Zachman framework to the architectural design of enterprise pension information system (LIS) applications. Research methods include documentary analysis and interviews with experts in the field of software architecture. Our research results show that the application of the Zachman framework provides an organized and clear structure to the architectural design of enterprise pension information system (LIS) applications. By considering the various aspects provided by the Zachman framework, the architectural design process can be carried out systematically and efficiently. It is hoped that this research can contribute to the development of a company application architecture design methodology, especially those related to the implementation of pension information systems (SIP). The findings of this research also encourage further research regarding the application of new technology to support information system integration at the agency level.
Penilaian Kematangan Manajemen Data Master, Studi Kasus Rumah Terapi XYZ Asymala, Asymala Permata Sari; Hidayanto, Achmad Nizar
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 5 No 1 (2024): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v5i1.9904

Abstract

Master Data Management (MDM) provides a way for an organization to ensure its data consolidation and integration across the whole system using a single master data set, thus benefiting with seamless operational and analytical processes. Not all organizations have good directions nor know the strategies of master data management. Master Data Maturity Management Model (MD3M) provides a blueprint for organizations to assess their currently implemented master data maturity management. The case study in this paper assessed MDM implementation in Therapy House XYZ by using MD3M by Spruitz and Pietzka. The referred MD3M has 5 key topics and 13 focus areas regarding master data management implementations. By assessing each of these points, organizations could know in which directions or area they could improve regarding MDM. The data were collected by using questionnaires and interviewing a Subject Matter Expert (SME) that handled the data management and system in the organization. This research found that 57% or 36 out of 63 of MD3M capabilities have been implemented. The missing capabilities are spread thorough the 5 key topics. The organization can achieve a higher maturity level by implementing the missing capabilities. Keywords: Master Data, Master Data Management, Master Data Maturity Assessment, MD3M
Prediksi Jumlah Produksi Kakao Provinsi Aceh dengan Metode Adam Bashforth-Moulton (ABM) Riezky Purnama Sari; Riska Novita sari
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 4 No 1 (2023): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v4i1.10480

Abstract

Aceh province's cocoa production experiences increases and decreases every year and has not shown significant development even though cocoa has a very important role in supporting the agricultural sector and the economy of Aceh province. The aim of this research is to provide information about estimating the production and supply of cocoa for Aceh province in 2023-2026 with the hope that the government can make more precise plans regarding cocoa and can make Aceh province the largest cocoa producer in Sumatra. This research uses the Adams Bashforth Moulton method which can provide a fairly accurate solution in completing the approximation of cocoa production quantities. Data analysis began by using the fourth order Runge Kutta method to obtain four initial solutions which were then substituted into the fourth order Adams Bashforth predictor equation. The estimation results using the Adams Bashforth Moulton method show that every year the amount of cocoa production increases by an average of 3.67% per year. The predicted cocoa production for Aceh Province in 2023 will be 38451.2 tons, in 2024 it will be 39880.6 tons, in 2025 it will be 41327.5 tons, and in 2026 it will be 42789.6 tons.
Pengembangan dan Penerapan EFDE Gen 3 dengan Pemanfaatan Visualcam Untuk Identifikasi Dampak Mitigasi Lapangan Secara Real-time Nila, Ida Ratna; Alamsyah, Wan
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 3 No 2 (2022): Jurnal Informatika dan Teknologi Komputer (J-ICOM)
Publisher : E-Jurnal Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v3i2.10496

Abstract

Wireless-based technology development, particularly the Internet of Things system, is currently in high demand in a variety of industries, including disaster mitigation. A catastrophe mitigation system will be built as an Internet of Things-based weather station that leverages solar system technology as a power source in this research. Because this utility is a development of the previous version, EFDe, it is known as EFDe Gen 3. This EFDe Gen 3 tool's monitoring mechanism is built on a visual cam that can reach full target range access. Using an ultrasonic sensor, the operating system of this tool is designed to detect changes in water level as early as possible and issue a disaster alarm at the appropriate time in real-time at a dam or sluice (HC-SR04). This instrument also has a measuring limit as well as an IP camera mounted on the solar panel pole. When the water level hits 40 cm, the Arduino Uno will turn on and send an alarm with a link to the flood's location, after which the camera will capture a picture. The URL can be accessed, and the location of the flood can then be determined. It is envisaged that with this instrument, Langsa City, in general, and Samudra University, in particular, will be able to establish their weather station to monitor weather developments and serve as a disaster mitigation system for lessening the consequences of natural disasters.
Penerapan Backpropagation Neural Network pada Prediksi Curah Hujan di Sumatera Utara Ulya Nabila; Indah Ramadhani; Fazrina Saumi
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 4 No 1 (2023): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v4i1.10503

Abstract

Indonesia is located on the equator with a latitude of 6°N to 11°S. This latitude causes a high intensity of solar radiation so that the air temperature becomes high. This causes the evaporation of water from the surface of the sea and land to form clouds and rain. One of the provinces in Indonesia that has high rainfall is North Sumatera. Due to the high rainfall, the province often experiences floods and landslides. In order to minimize the impact of floods and landslides, the first thing that can be done is to predict the rainfall in North Sumatera. The method used is Backpropagation Neural Network. This method is a kind of artificial intelligence designed to process information by imitating the nervous system of the human brain. This research aimed to predict rainfall in North Sumatera using Backpropagation Neural Network and determine the accuracy of this method. The data came from the Badan Pusat Statistik (BPS) of North Sumatera, namely rainfall data from January 2020 to December 2022. The results implied that rainfall in 2023 for each month is 190; 266; 197; 178; 290; 182; 299; 350; 213; 485; 357; and 389 (mm/month) and has an accuracy of Mean Absolute Percentage Error (MAPE) of 35.55%, so this method is categorized as suitable for predicting rainfall.
Virtual Tour Grand Design Destinasi Wisata Monumen Kresek Berbasis VR Masbahah
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 5 No 2 (2024): Jurnal Informatika dan Teknologi Komputer ( J-ICOM)
Publisher : E-Jurnal Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/j-icom.v5i2.8406

Abstract

Tourism development is used as one of the strategies of the Madiun Regency government in increasing regional competitiveness. One of the leading tourist destinations that will be developed by the Madiun Regency government, especially DISPARPORA, is the Kresek Monument. The Kresek Monument is one of the leading tourist destinations based on history and culture in Madiun Regency. One of DISPARPORA's efforts in developing the tourist area is by introducing the Grand Design of the Kresek Monument to investors. So that investors are more interested, the Grand Design is packaged in a Virtual Reality-based virtual tour where investors can get an immersive sensation as if they were at the Kresek Monument which will be developed. The purpose of this research is to develop a Virtual Tour Grand Design Application for the Kresek Monument Tourism Destination based on VR. The method used in the development is MDLC (Multimedia Development Life Cycle) which consists of 6 stages namely concept, design, material gathering, assembly, testing, and distribution. The grand design describes the parts of the area to be developed at the Kresek Monument in a 3D object, including the Gate area, dining area, prayer room area, garden area 1, garden area 2, plaza area, play area, parking area, and historic statue area. The VR application that has been developed is tested for functionality using black box testing, the results show that the virtual tour grand design application for the Kresek Monument Tourism Destination, Madiun Regency is functionally running according to requirements.

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