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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

Implementasi Cyber-Physical-Social System berdasarkan Service Oriented Architecture pada Wisata Cerdas Ilham Firman Ashari
Journal of Applied Informatics and Computing Vol 4 No 1 (2020): Juli 2020
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1074.219 KB) | DOI: 10.30871/jaic.v4i1.2077

Abstract

One of the biggest attractions in the tourism industry in Bandung is nature tourism. There is still such a constraint related to get information about nature tourism in Bandung because new attractions in Bandung always appear every year. This is felt particularly for foreign tourists outside of Bandung. Tourists are still confused to find new and popular tourist attractions, which are places that are worth visiting or not. By implementing Cyber-Physical-Social System (CPSS) with a new approach that is emphasized on social aspect in smart tourism based on Service Oriented Architecture (SOA) as methodology can influence other travelers to visit tourist attractions in Bandung. The main results are tourists will get information such as location, route, images, rating, captions of tourist attractions, and the most important thing is to be able to exchange information with others. Smart tourism is more flexible because it is web based and does not depend on the operating system used, does not require database storage, does not take up storage space, and is free. Tourists can access smart tourism anytime and anywhere.
Sistem Penjadawalan Satpam Menggunakan Algoritma Genetika dan Seleksi Tournament Ilham Firman Ashari; Ardi Gaya Manalu; Rahmat Setiawan; Mugi Praseptiawan; Dita Alviuni P; Sisilia Juli A
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3464

Abstract

Institut Teknologi Sumatera (ITERA) is one of the new state universities on the island of Sumatra. ITERA has developed and has a large area and many buildings, of course it requires a lot of security guards to maintain security and order in the campus environment. The working hours of security guards at ITERA are from morning to night. ITERA is required to make a watch or shift schedule for security guards, where currently the scheduling is still done manually and has not been systemized automatically. Genetic Algorithm can be used in the scheduling process automatically and optimally by going through several stages. The result of the research is that the automatic scheduling system was successfully built, from the security data used as many as 16 data obtained scheduling from Monday to Sunday along with its working hours.
Application of Data Mining with the K-Means Clustering Method and Davies Bouldin Index for Grouping IMDB Movies Ilham Firman Ashari; Romantika Banjarnahor; Dede Rodhatul Farida; Sicilia Putri Aisyah; Anastasia Puteri Dewi; Nuril Humaya
Journal of Applied Informatics and Computing Vol 6 No 1 (2022): July 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i1.3485

Abstract

Along with the development of technology, the film industry continues to increase, this can be seen from the number of films that appear both in cinemas and tv shows. The Internet Movie Database (IMDb) is a website that provides information about films from around the world, including the people involved in the films. Information contained on IMDB such as actor/actress, director, writer, to the soundtrack used. In addition, IMDb is the most popular and trusted source of information for movies, TV, and other celebrity content. In this case, the researcher will conduct research on the film with what title is the most popular among the public by looking at some of the parameters contained in IMDB such as the number on the rating, score, certificate, and votes obtained from the audience. The data used comes from the Kaggle.com website. The data mining method used is the K-Means clustering method. To find out the optimal cluster value, the Davies Bouldin index is used. The K-Means algorithm will group the data based on the centroid. The parameters used for clustering are runtime, IMDB rating, meta score, number of votes, and gross. The results of the study obtained that the average calculation of the highest attributes was 48.74 and the number of clusters formed was 4 clusters. The results of the evaluation using the confusion matrix obtained an accuracy value of 100%.
Pengembangan Aplikasi Mobile Kolepa Berbasis Android Menggunakan Metode Agile Ilham Firman Ashari; M. Fazar Zuhdi; Muhammad Tyaz Gagaman; Siraz Tri Denira
Journal of Applied Informatics and Computing Vol 6 No 1 (2022): July 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i1.3932

Abstract

Kolepa Minigolf and coffe shop is an instance which run on minigolf services also food and beverages. Kolepa wanted to develope a mobile apps that can be use for Kolepa Customer to check on existing promo and book a table to play. Kolepa Mobile Apps will be integrated with Kolepa database. Based on the interview between Project Manager and owner of Kolepa, there's some feature that must be included on the Mobile Apps, which is Authenticate, Promo, Reservation, and Score Counter. In its implementation, agile methods are applied for each of the functions mentioned above. Aplication will be develope using Dart Programming Languange, which is part of Flutter Framework. Application development is divided into several sprints that are developed with predetermined deadlines. From the results of the development that has been carried out, feature testing is carried out using the blackbox method and it is found that the application has met the functional and non-functional requirements that have been set. With this application, Kolepa can simplify the bussiness they run.
Comparative Analysis of OpenMP and MPI Parallel Computing Implementations in Team Sort Algorithm Nugroho, Eko Dwi; Ashari, Ilham Firman; Nashrullah, Muhammad; Algifari, Muhammad Habib; Verdiana, Miranti
Journal of Applied Informatics and Computing Vol. 7 No. 2 (2023): December 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i2.6409

Abstract

Tim Sort is a sorting algorithm that combines Merge Sort and Binary Insertion Sort sorting algorithms. Parallel computing is a computational processing technique in parallel or is divided into several parts and carried out simultaneously. The application of parallel computing to algorithms is called parallelization. The purpose of parallelization is to reduce computational processing time, but not all parallelization can reduce computational processing time. Our research aims to analyse the effect of implementing parallel computing on the processing time of the Tim Sort algorithm. The Team Sort algorithm will be parallelized by dividing the flow or data into several parts, then each sorting and recombining them. The libraries we use are OpenMP and MPI, and tests are carried out using up to 16 core processors and data up to 4194304 numbers. The goal to be achieved by comparing the application of OpenMP and MPI to the Team Sort algorithm is to find out and choose which library is better for the case study, so that when there is a similar case, it can be used as a reference for using the library in solving the problem. The results of research for testing using 16 processor cores and the data used prove that the parallelization of the Sort Team algorithm using OpenMP is better with a speed increase of up to 8.48 times, compared to using MPI with a speed increase of 8.4 times. In addition, the increase in speed and efficiency increases as the amount of data increases. However, the increase in efficiency that is obtained by increasing the processor cores decreases.
Optimizing Driving Completeness Prediction Models: A Comparative Study of YOLOv7 and Naive Bayes at Institut Teknologi Sumatera Algifari, Muhammad Habib; Ashari, Ilham Firman; Nugroho, Eko Dwi; Afriansyah, Aidil; Vebriyanto, Mario
Journal of Applied Informatics and Computing Vol. 7 No. 2 (2023): December 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i2.6761

Abstract

The number of vehicles in Indonesia is increasing every year. The number of motor vehicle accidents in 2022 will be more than 100,000. It is hoped that several regulations regarding motorbike rider equipment will increase awareness of rider safety. By utilizing image recognition technology developed with artificial intelligence, it is possible to create digital image processing models or images that are fast and accurate for detecting driving equipment. The object detection model developed uses a dataset in the form of images of motorists who want to enter ITERA through the main gate. The object detection model will also be integrated with the classification model to create a program that can detect motorbike rider equipment, such as mirrors, helmets, not wearing a helmet, shoes, not wearing shoes, open clothes, and closed clothes. After detecting motorized rider equipment in the classification area, the results will be transferred to a classification model to determine the level of safety for motorized riders, either insufficient or sufficient safety. The test results show that the optimal object detection model was found at an epoch value of 70 with a batch-size of 16, producing a mAP value of 0.8914. The optimal classification model uses the naive Bayes method which has been trained with a dataset of 62 data and achieves an accuracy of 94%.
Analysis of Elbow, Silhouette, Davies-Bouldin, Calinski-Harabasz, and Rand-Index Evaluation on K-Means Algorithm for Classifying Flood-Affected Areas in Jakarta Ashari, Ilham Firman; Dwi Nugroho, Eko; Baraku, Randi; Novri Yanda, Ilham; Liwardana, Ridho
Journal of Applied Informatics and Computing Vol. 7 No. 1 (2023): July 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i1.4947

Abstract

Jakarta is the capital city of Indonesia, which has a high population density, and is an area that is frequently hit by floods. This study aims to determine the classification of flood-affected areas in Jakarta between severe, moderate, and low. Design/method/approach: The study was conducted using the elbow, Silhouette, Davidson-Bouldin, and Calinski-Harabasz methods on the K-means algorithm, as well as the Rand method. index for evaluation. Grouping with 3 and 6 groups is the best grouping value based on Calinski-Harabasz. By using the davies bouldin index from the observations, the K value with a value of 6 has the smallest Davies-Bouldin value with a value of 0.2737. By using sillhoute, the experimental results obtained the best values sequentially, namely K=2, K=3, and K=6 with silhouette values of 0.866, 0.854, and 0.803. In this experiment, based on the elbow method, it was found that the best K value was K=3. This was obtained because it was based on observations on the appearance of the SSE data compared to the value of K. In the graph above, it can be seen that the largest decrease in data occurred at K=3 and after this decrease, the decline began to slope. The rand index is a method used to compare several cluster methods. If the value is >= 90 it is a very good result, if the value is in the range 80 to 90 it identifies a good index, whereas if it is below 80 it indicates a bad index. The results show that cluster three is verified as the best cluster with a value of 1, followed by a second alternative with cluster 2 of 0.9182. From several validation and evaluation methods it can be concluded that the best grouping can be done using 3 clusters. The results of the study yielded a value of 75.4% in low areas, 21.1% in moderate areas, and 3.5% in severe areas.
Co-Authors Achmad Syafriyal Adinda Sekar Tanjung Adrian Putradinata, Gusti Made Afriansyah, Aidil Agustine, Verlina Ahmad Auzan Varian Syahputra Aidil Afriansya Aidil Afriasnyah Ajrina, Fadiah Izzah Akbar, Alvijar Algifari, Muhammad Habib Alkarkhi, Makruf Anastasia Puteri Dewi Andhika Wibawa Bhagaskara Andika Setiawa Andika Setiawan Andre Febrianto Andrianto, Dodi Devrian Ardhi, Alief Moehamad Ardi Gaya Manalu Arimbi Ayuningtyas Arre Pangestu Aryani, Annisa Jufe Azwarman Azwarman Baraku, Randi Clinton, Martin Daniel Rinald Dede Rodhatul Farida Dita Alviuni P Dwi Nugroho, Eko Eka Nur'azmi Yunira Eko Dwi Nugroho Eko Dwi Nugroho Eko Dwi Nugroho Fadhillah A Fikri Halim Ch Filiana, Edinia Rosa Fil’aini, Raizummi Gunawan, Rayhan Fatih Hendri Tri Putra Idris, Mohamad Jaya Megelar Cakrawarty Laisya, Nashwa Putri Leonard Rizta Anugrah P Liwardana, Ridho Londata, Hafizh M. Daffa M. Fazar Zuhdi Majesty, Achmad Bany Marbun, Rustian Afencius Mastuti Widianingsih, Mastuti Muhammad Abdul Mubdi Bindar Muhammad Affandi Muhammad Afif H Muhammad Alfarizi Muhammad Najie K Muhammad Rizky Hikmatullah Muhammad Telaga Nur Muhammad Tyaz Gagaman Muhammad Yusuf Nashrullah, Muhammad Nazla Andintya W Nela Agustin Kurnianingsih Novri Yanda, Ilham Nur'azmi, Eka Nurhayati, Misfallah Nuril Humaya Perdana Raga Winata Praseptiawan, Mugi Prasetyawan, Purwono Radhinka Bagaskara Rahmat Setiawan Raidah Hanifah Raidah Hanifah Revangga, Dwi Arthur Ringgo Galih Sadewo Romantika Banjarnahor Salman Damanhuri Samsu Bahri Satria, Mahesa Darma Sekar A Sianturi, Elsa Elisa Yohana Sicilia Putri Aisyah Sinaga, Nydia Renli Sinaga, Rutlima Siraz Tri Denira Siregar, Abu Bakar Siddiq Sisilia Juli A Siwi, lkhsanudin Raka soleha, Ayu Sophia Nouriska Syamsyarief Baqaruzi Untoro, Meida Cahyo Utoro, Meida Cahyo Vanesa Adhelia Vebriyanto, Mario Verdiana, Miranti Verlina Agustine Vina Oktarina Wicaksono, Ihtiandiko Winda Yulita Yulita, Winda Yunira, Eka Nur'azmi Yusuf, M. Asyroful Nur Maulana