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INDONESIA
JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Published by Politeknik Negeri Batam
ISSN : -     EISSN : 25486861     DOI : 10.3087
Core Subject : Science,
Computer Science & IT
Journal of Applied Informatics and Computing (JAIC) Volume 2, Nomor 1, Juli 2018. Berisi tulisan yang diangkat dari hasil penelitian di bidang Teknologi Informatika dan Komputer Terapan dengan e-ISSN: 2548-9828. Terdapat 3 artikel yang telah ditelaah secara substansial oleh tim editorial dan reviewer.
Arjuna Subject : -
Articles 15 Documents
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Search results for , issue "Vol 6 No 1 (2022): July 2022" : 15 Documents clear
Implementasi Metode YOLO-V5 pada Sistem Deteksi Social Distancing Berbasis Real-Time Imam Husni Al Amin; Falah Hikamudin Arby
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.v6i1.3484

Abstract

The world is in an uproar with the Covid-19 pandemic, which has had an impact on society. Various efforts have been made by governments around the world to suppress the spread of the Covid-19 virus. One of the health protocols that have been appealed by the government is social distancing or social restrictions, namely limiting interactions between human beings as long as 1-2 meters. But in reality, there are still many people who ignore social distancing policies. The application of a social distancing detection system can be a solution to this problem. This system aims to detect people who are violating health protocols in the form of social distancing and then issue a voice warning to keep their distance from others to avoid the spread of the Covid-19 virus by using the YOLO-v5 method which is the latest version of YOLO (You Only Look Once). . Processing speed of YOLO-v5 has increased drastically with the fastest speed reaching 140 Frames Per Second (FPS) and has a small size, even having a size of 90% compared to the previous version. The accuracy of human detection using YOLO-v5 from this system reaches 83.28% and the accuracy of social distancing detection reaches 90.8%. From the results of the percentage analysis that has been carried out, it can be concluded that the system that has been created can function well for social distancing detection, but it is difficult to detect if humans are too far from the camera.
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%.
Analisis Penerimaan Aplikasi Transportasi Online di Kepulauan Riau Menggunakan Metode Technology Acceptance Model Mangapul Siahaan; Kelvin Kurniawan
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.v6i1.3509

Abstract

Traffic density in the Riau Islands area is increasing day by day. Population density that has exceeded this threshold causes congestion on the road which causes losses to people who are carrying out activities. As e-commerce grows rapidly, it becomes a push for e-commerce applications that develop in line with the community's need for online application-based services that operate on smartphones. The application of online application-based transportation services that are growing rapidly. One of the factors of this online application-based transportation service innovation is the growing number of internet services offered by internet service providers and more and more internet users, so that the internet becomes a necessity and lifestyle for the community. This research is a development of previous research in examining the factors that influence public acceptance of online transportation applications using the UTAUT2 research model; the current study uses the Technology Acceptance Model research model. This questionnaire was distributed to 400 respondents to the residents of the Riau Islands using Amos and SPSS. The results of the analysis of transportation application online acceptance in Riau Kepulauan using Technology Acceptance Model were seen from the construct of behavioral intention use to attitude toward using is 100%, actual system use to behavioral intention to use is 94.7%, perceived usefulness to perceived ease of use is 80.3%, attitude toward using to perceived usefulness is 47.6% whereas behavioral intention use to perceived usefulness is not effected as positive.
Penyembunyian Pesan Terenkripsi pada Citra menggunakan Algoritma LSB dan Transposisi Kolom Kiswara Agung Santoso; Ahmad Tanto Wiraga; Abduh Riski
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.v6i1.3819

Abstract

Data security is a very important thing to do so that messages or information are sent to someone who is not known by unauthorized persons. Data security techniques that The ones that are often used today are cryptography and steganography. In this study, the data is to be secured in text. To increase security, text messages are first encrypted using the vigenere algorithm and column transposition. This text message is then hidden into an image (cover image). The encrypted text message was hidden in the image using the LSB algorithm and column transposition. The results of the study show that the virtual stego image generated is very effective similar to the original image. Based on the results of the MSE and PSNR analysis, it can be seen that the resulting image quality can be categorized as good. This can be seen from the PSNR value above 50 dB and some even above 60 dB. Based on the results of the LSB analysis, the stego image does not look strange so it will not be suspected by unauthorized people that there is a hidden message in the image.
Clustering Data Penduduk Miskin Dampak Covid-19 Menggunakan Algoritma K-Medoids Novi Widiawati; Betha Nurina Sari; Tesa Nur Padilah
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.v6i1.3266

Abstract

Kemiskinan merupakan masalah yang mendasar, kemiskinan bisa berakibat pada terhambatnya pembangunan nasional. Ada beberapa aspek yang berkaitan dengan kemiskinan yaitu faktor ekonomi, politik, dan psikososial. Secara ekonomi, kemiskinan diartikan sebagai kurangnya sumber daya untuk memenuhi kebutuhan hidup dan meningkatkan kesejahteraan. Pada penelitian ini data yang digunakan pada tahun 2020 yang bersumber dari Badan Pusat Statistika. Dalam upaya menemukan kasus kemiskinan dampak covid-19 dapat menggunakan Data Mining. Tujuan dari penelitian ini untuk mengelompokkan kabupaten/kota yang memiliki kemiskinan dampak covid-19 dengan tingkat tinggi dan rendah di Indonesia. Penelitian yang akan dilakukan dengan langkah data mining yaitu CRISP-DM (Cross Industry Standart for Data Mining) yang terdiri dari 6 fase yaitu pemahaman bisnis (business understanding), pemahaman data (data understanding), pengolahan data (data preparation), pemodelan (modelling), evaluasi (evaluation), dan penyebaran (deployment). Algoritme yang digunakan pada penelitian ini yaitu K-Medoids. Pengukuran menggunakan bahasa R dengan bantuan fungsi Pamk sehingga hasil yang didapatkan pada dataset Penduduk Miskin Tahun 2020 memiliki cluster optimal sebanyak 2 cluster. Cluster1 dengan jumlah 121 kabupaten/kota dengan kategori tinggi, sedangkan cluster2 dengan jumlah 427 dengan kategori rendah. Hasil dari evaluasi nilai Silhouette Coefficinet sebesar 0,4735719 .
E-Book Pelajaran IPA Berbasis Mobile (Studi Kasus: Pelajaran IPA Kelas 5 SD) Evaliata Br Sembiring; Wachid Zaini
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.v6i1.3326

Abstract

Buku Sekolah Elektronik merupakan sebuah buku digital atau elektronik agar dapat membantu proses pembelajaran peserta didik dimanapun dan kapanpun berada. Pembuatan ebook ini didasarkan karena pandemi covid-19 yang menyebabkan pembelajaran dilakukan dari rumah. Proses pembuatan e-book menggunkan pendekatan Luther Sutopo dengan memanfaatkan beberapa tool antara lain: Framework React Native, HTML, PHP, Javascript Framework, AngularJS, dan Node.js. E-book yang dihasilkan, dianalisis menggunakan metode evaluasi goal-attainment untuk mengetahui tingkat pemahaman minat belajar siswa. Hasil penelitian adalah: (1) E-book berhasil dibuat dalam bentuk aplikasi mobile dengan memenuhi kategori e-book yaitu dilengkapi dengan fitur login untuk keamanan pengguna, materi pelajaran dalam bentuk video, pdf, gambar dan evaluasi dalam bentuk soal pilihan ganda; (2) Produk telah digunakan oleh responden (siswa) dan berdasarkan analisisi goal attainment, diperoleh nilai MOS sebesar 4.6 berarti pengguna aplikasi sangat puas menggunakan aplikasi sehingga layak dijadikan alternatif media pembelajaran siswa di rumah.
RETRACTED: Pengamatan Tren Ulasan Hotel Menggunakan Pemodelan Topik Berbasis Latent Dirichlet Allocation Suparyati Suparyati; Emma Utami; Agus Fathurahman
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.v6i1.3645

Abstract

Artikel dengan judul "Pengamatan Tren Ulasan Hotel Menggunakan Pemodelan Topik Berbasis Latent Dirichlet Allocation" telah dilakukan pencabutan artikel (RETRACT) dari vol. 6 no. 1 tahun 2022 Journal of Applied Informatics and Computing (JAIC), karena ditemukan duplikasi publikasi oleh penulis yang bersangkutan pada JIKO (Jurnal Informatika dan Komputer) https://ejournal.akakom.ac.id/index.php/jiko/article/view/579Penulis meminta maaf dan meminta untuk melakukan pencabutan artikel dari Journal of Applied Informatics and Computing (JAIC). Berikut surat permohonan pencabutan artikel dari penulis disini.
Penerapan Data Mining Pengelompokan Menu Makanan dan Minuman Berdasarkan Tingkat Penjualan Menggunakan Metode K-Means Genta Triyandana; Lala Aprianti Putri; Yuyun Umaidah
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.v6i1.3824

Abstract

Data mining can be used to find solutions in making sales decisions to increase sales. Sales data storage stores many sales transaction records, where each document provides products purchased by customers in each sales transaction. A problem began to arise with an excess stockpiling of materials. The number of fluctuating sales causes the stock of available materials to be unstable and can directly impact consumers. Mistakes in predicting sales caused the coffee shop to buy large quantities of material stock, which were not widely used or sold out, so the supply of these materials swelled in the warehouse. One way to be implemented is by applying data mining because there are ways and methods to meet needs, one of which is the need for extensive information, then the information that we can use to determine quality in determining a decision. Therefore, it is hoped that this research can help Dpom Coffee minimize material stock inventory management cases such as shortages and excesses and make policies to increase sales by grouping menus based on sales levels using the K-means algorithm. Based on the results of processing the sales dataset at Dpom Coffee, it produces 3 clusters, namely Cluster 1 with eight menus with low sales levels, cluster 2 with 40 menus with moderate sales levels, and cluster 3 with seven menus with high sales levels. The accuracy or performance of the k-means algorithm results in a Davies Bouldin index value of 0.457.
Clustering Tenaga Kesehatan Berdasarkan Kecamatan di Kabupaten Karawang Menggunakan Algoritma K-Means Desi Kristina Sitinjak; Bagus Aji Pangestu; Betha Nurina Sari
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.v6i1.3855

Abstract

Pembangunan kesehatan merupakan bagian dari Pembangunan Nasional yang pada hakekatnya adalah penyelenggaraan upaya kesehatan untuk mencapai kemampuan hidup sehat bagi setiap penduduk agar dapat mewujudkan derajat kesehatan yang optimal, masalah kesehatan yang ada pada masyarakat di Indonesia yaitu masih minimnya tenaga kesehatan pada setiap wilayah. Salah satunya di Kabupaten Karawang, Tenaga kesehatan yang tidak tercukupi di beberapa kecamatan yang ada di Karawang akan membuat masyarakat di kecamatan tersebut kesulitan untuk hidup sehat dan mengobati penyakitnya. Penelitian ini bertujuan untuk melakukan pengelompokan terhadap Kecamatan yang memiliki tenaga kesehatan yang masih kurang sehingga data tersebut dapat digunakan untuk peningkatan kualitas kesehatan. Penelitian ini mengunakan metode K-Means Clustering. Hasil pengolahan dataset tenaga kesehatan yang ada di Kabupaten Karawang menghasilkan 3 cluster, yaitu cluster 1 dengan tenaga kesehatan sedikit sebanyak 24 kecamatan, cluster 2 dengan tenaga kesehatan sedang sebanyak 4 kecamatan dan cluster 3 dengan tenaga kesehatan terbanyak yaitu 2 kecamatan.
Use Case Framework of Computerized Production Monitoring Processes in Textile Industry Irma Santikarama; Faiza Renaldi; Fatan Kasyidi; Agya Java Maulidin
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.v6i1.3977

Abstract

Use cases are a description of system functions resulting from needs analysis and obtained from interviews and observations. In standard practices, this stage is also known as the most time-consuming stage. Although every use case produced in software development is unique, there is always a similarity in its function to systems made previously in other organizations. These similarities are studied to reduce time in the process during the requirements analysis stage. Many studies have built and used a Use Case Framework (UCF) to be used together by software developers. So far, UCF has been owned by the banking industry in mapping use case standards in ATMs, health in standardizing use cases in electronic medical records, libraries in standardizing information retrieval, and mapping processes in crowdfunding. This research adds to the list of the latest UCFs produced, namely in the related textile industry, in standardizing the functions that exist in computer-based production monitoring systems. It is based on the fact that there are many textile companies globally, with more than 1.000 of them are established in Indonesia. This study investigated eight Indonesian textile companies to obtain information data to determine what functions are required, t. The data collection techniques used were interviews and observation. More stages were carried out in this study afterward, namely defining Actor Analysis and Functional Methods, Combining Analysis, Classification of Use Cases, Describing Use Case Scenarios, and Visualizing Frameworks. The data analysis results obtained from each company, we managed to define 10 main use cases, 4 supporting use cases, and four specific use cases. This study’s products can help provide a reference in using case design to create a computer-based textile company monitoring system.

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