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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

Penerapan Replikasi Data pada Aplikasi Ticketing Menggunakan Slony PostgreSQL Defriyanuar Dhining; Yeni Rokhayati; Dwi Ely Kurniawan
Journal of Applied Informatics and Computing Vol 1 No 2 (2017): Desember 2017
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (964.866 KB) | DOI: 10.30871/jaic.v1i2.472

Abstract

Nowadays, almost every company use web aplication to do their business activity. Besides multi-platform it also easier for installation and maintenance. Other that web application need a fast and reliable internet connection. It is necessity to make a server in local area network with syncronize database from one server to another server. Syncronize database will run using replication server database. Database replication can use many tool, one of them is Slony that is specially create for PostgreSQL. Replication database can also to pretend stopping application when there is bad internet connection. Replication database is one of stanby server tecknic because down server. Database synchronize will be buid using PHP programming language and PostgreSQL database with Slony which is open source at all, so it will reduce the cost of installation and maintenance.
Clustering Profil Pengunjung Perpustakaan Menggunakan Algoritma K-Means Fauziah Mahmuda; Maya Armys Roma Sitorus; Hilda Widyastuti; Dwi Ely Kurniawan
Journal of Applied Informatics and Computing Vol 1 No 1 (2017): Juli 2017
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (893.435 KB) | DOI: 10.30871/jaic.v1i1.476

Abstract

Business Entity library Batam (BP Batam) is a public library located in Batam city with thw number of visitors. Every visitor who comes to do the charging guest book manually by writing system. It causes a buildup of data which are not organized. Data mining is one of the analytical tools that can be used to address the backlog of data. The method of Clustering with the K-Means Algorithm used in analyzing the data library visitors BP Batam. Library visitors using the data processing method of Elbow to get the best number of clusters K i.e., K = 3, and by using the center point (centroid) initial i,e, P1 = (4,1), P2 = (2,4), P3 = (4,2). The purpose of this research is to apply the algorithm for K-Means clustering in the data library visitors (case study library BP Batam). K-Means clustering results obtained from 1556 dataset data library visitors are grouped into three clusters, Clusters 1 is dominated by a college student and visitor located at Batam Center, Cluster 2 is dominated by a college student and visitor located at Bengkong, Cluster 3 is dominated by public and visitor status in Batam Center.
Rancang Bangun Lab Komputer Virtual Berbasis Cloud Computing Menggunakan Openstack Pada Jaringan Terpusat Nelmiawati Nelmiawati; Nur Cahyono Kushardianto; Ahmad Hamim Tohari; Yan Prada Hasibuan; Dwi Ely Kurniawan
Journal of Applied Informatics and Computing Vol 2 No 1 (2018): Juli 2018
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (922.577 KB) | DOI: 10.30871/jaic.v2i1.821

Abstract

Politeknik Negeri Batam is one college that gives higher priority to practicum activity. Students are therefore faced with a larger practical task than theory, making it more laboratory than practicum sessions. While access to the lab is quite limited. Virtual computer labs using Cloud Computing technology can be a solution to overcome this limitation. The author has been doing research on the design of Cloud Computing's virtual computer lab using OpenStack on a centralized network and has got some results. Tests are performed with specific server specifications and use the OpenStack platform. And the results of testing of the virtual computer lab with case studies of object-based programming courses show the server used during testing can run virtual computer lab with 9 computers well. While in the case study there are 30 computers per lab. This is due to hardware resources that are not good enough.
Rancang Bangun Aplikasi WebGIS untuk Pemetaan Kondisi Sosial Ekonomi Kota Batam Ariyanto Ariyanto; Dwi Ely Kurniawan; Agus Fatulloh
Journal of Applied Informatics and Computing Vol 2 No 1 (2018): Juli 2018
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (935.112 KB) | DOI: 10.30871/jaic.v2i1.904

Abstract

Kondisi sosial ekonomi suatu wilayah kepulauan merupakan suatu hal yang perlu disampaikan secara publik, mengingat ketererbatasan dan ketersedian kebutuhan dasar dari kehidupan dan kemampuan ekonomi masyarakat lokal. Penelitian ini mencoba untuk melakukan survey terkait kondisi sosial ekonomi Kepuluan Riau dengan teknik penggalian sumber data BPS dan survey lokasi. Hasil survey kemudian diolah dan divisualkan dalam bentuk WebGIS untuk memudahkan dalam menampilkan informasi spasial. Digitasi peta menggunakan QuantumGIS berupa titik, garis dan polygon. Layanan server map menggunakan ArcGIS Online. WebGIS dikembangkan menggunakan CSS Bootstrap dengan menggabungkan data peta sehingga peta dapat mudah diakses dan menampilkan informasi dari berbagai perangkat dan platform. Harapannya memudahkan pihak CSR atau pemerintah dalam membuat keputusan terhadap kondisi sosial masyarakat.
Classification of COVID-19 Aid Recipients in Kasomalang District Using the K-Nearest Neighbor Method Permatasari, Ismi Aprilianti; Dermawan, Budi Arif; Maulana, Iqbal; Kurniawan, Dwi Ely
Journal of Applied Informatics and Computing Vol. 8 No. 1 (2024): July 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i1.3279

Abstract

The impact of the Coronavirus, also known as COVID-19, which emerged in 2019, has not only threatened public health but also affected the global economy, including Indonesia. The government has initiated various aid programs to assist the community during the COVID-19 pandemic. These aids are expected to alleviate the economic burden on the affected population. One such aid program is the Direct Cash Assistance (Bantuan Langsung Tunai/BLT) from the Village Fund, which has been distributed since the onset of COVID-19 in Indonesia. However, the distribution of BLT has encountered several issues, including misidentification of recipients and double or excessive distribution beyond the established criteria. To address these issues, data mining for the classification of aid recipients can be employed. This study uses the K-Nearest Neighbor (KNN) method for data mining classification to classify residents' data with new patterns, ensuring aid distribution aligns with the criteria and eliminating double recipients. The application of K-Nearest Neighbor to the population data in Kasomalang District yields optimal performance, with evaluation results showing an accuracy of 96%, precision of 0.98, recall of 0.96, and F1 score of 0.97 using the confusion matrix method.
Sales Analysis Using Apriori Algorithm in Data Mining Application on Food and Beverage (F&B) Transactions Marselina, Sonia; Jaman, Jajam Haerul; Kurniawan, Dwi Ely
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.v7i2.5026

Abstract

The current business landscape has compelled many companies to compete in boosting their company's revenue, particularly in the F&B sector. Existing sales transaction data has not been fully maximized in determining the business strategy of companies. Therefore, the implementation of data mining is necessary to analyze and explore available data to discover new information that is more beneficial for the company. In this study, we analyze sales transaction data using the a priori algorithm method because this algorithm efficiently handles the data mining process on a large scale with a substantial amount of data. The results of this study indicate that the formed association rules can determine patterns of product purchases that are frequently bought together. The established association rules successfully combine sales transaction data into two-item combinations, namely green tea latte and french fries, with a support value of 16% and a confidence level of 83%. These rules can be used as a reference in determining the company's business strategy.
Analisis Sentimen Twitter Terhadap Opini Publik Atas Isu Pencalonan Puan Maharani dalam PILPRES 2024 Vonega, Defangga Aby; Fadila, Aminudin; Kurniawan, Dwi Ely
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4300

Abstract

Twitter can be seen as a platform for candidates and users to gain substantial reach to show their views on who the president will be elected to in 2024. The aim of this study is to explore contrasting information over time regarding whether Puan Maharani can be one of the candidates. The best according to the Indonesian people. In this study, sentiment analysis was carried out using the text mining method and several libraries such as TextBlob, VaderSentiment, and SentiWordNet to retrieve and classify the polarity of opinions from data that had been crawled. In the dataset generated with the keyword "Puan Maharani" The average negative sentiment is only 0.1%, neutral sentiment is 97.25, and positive sentiment is 2.55%. It can be concluded that Twitter users tend to be neither aggressive nor defensive in discussing issues leading to the candidacy of Puan Maharani in the upcoming 2024 Indonesian presidential election.
Scenario-Based Association Rule Mining in Veterinary Services Using FP-Growth: Differentiating Clinical and Customer-Driven Patterns Rafi Dio; Aulia Agung Dermawan; Dwila Sempi Yusiani; Rifaldi Herikson; Andikha, Andikha; Dwi Ely Kurniawan; Adyk Marga Raharja
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9698

Abstract

Veterinary clinics routinely generate transactional data that contain valuable information about both operational workflows and customer preferences. This study aims to differentiate between procedural and customer-driven service patterns by applying the FP-Growth association rule mining algorithm to 1,000 anonymized transactions comprising 94 unique items, collected from a veterinary clinic in West Java, Indonesia, during 2023. Two distinct analytical scenarios were constructed: Scenario 1 includes all services (procedural and customer-driven), while Scenario 2 excludes procedural items such as “Vet” and “Visit Dokter” to focus solely on client-initiated behaviors. Data preprocessing involved aggregating transaction items into a market basket format suitable for frequent pattern mining. The FP-Growth algorithm was employed to extract association rules, evaluated using support, confidence, and lift metrics. Results from Scenario 1 revealed rule patterns reflective of standard clinical protocols and operational dependencies, informing bundled service packages and inventory management. In contrast, Scenario 2 uncovered customer-driven associations, highlighting opportunities for personalized promotions and service innovation. The comparative analysis demonstrates the utility of scenario-based association rule mining for both operational optimization and customer engagement. While the findings provide actionable insights for clinic management, further validation with practitioners and implementation in multi-clinic settings are recommended to confirm real-world applicability and enhance generalizability.
Development of an IoT-Based Smart Cane with Non-Invasive Health Monitoring for Elderly Care in Batam Putera, Dimas Akmarul; Adi, Roni; Kurniawan, Dwi Ely; Leman, Abdul Mutalib; Raynold, Raynold
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.11107

Abstract

The rapid growth of the elderly population requires assistive technologies that support mobility, health, and safety. This study presents the development of an IoT-based smart cane designed to enhance elderly independence and health monitoring in Batam, Indonesia. The prototype integrates non-invasive health sensors (MAX30102 for heart rate and SpO₂, MLX90614 for temperature, and a non-invasive glucose sensor), a GPS module, a mini-CCTV with two-way audio, and a solar-powered energy system, all controlled by an ESP32 microcontroller connected to the Blynk IoT platform. Ergonomic design was guided by anthropometric data of Indonesian elderly to ensure user comfort and usability. Experimental results demonstrated stable performance of the integrated modules. Heart rate values ranged from 86–103 BPM (mean 89.5 ± 6.2 BPM), blood glucose estimations from 110–112 mg/dL (mean 111 ± 0.9 mg/dL), and body temperature from 36.9–37.1 °C (mean 37.0 ± 0.1 °C), all of which aligned closely with clinical references. Oxygen saturation readings, however, averaged 89 ± 0.8%, slightly below the clinical norm (≥95%), highlighting the need for sensor calibration. Dynamic testing of the GPS module across a 500-meter route achieved positional accuracy within 3–5 meters, while the CCTV system successfully streamed live video but was dependent on WiFi stability.The novelty of this research lies in the unique combination of locally adapted ergonomic design, multi-sensor non-invasive health monitoring, two-way visual and audio communication, GPS tracking, and renewable energy integration within a single portable device. These contributions not only enrich IoT-based healthcare research but also provide practical solutions tailored to elderly care in Indonesia. Future work will focus on clinical-grade validation of sensors, extended field trials, and the integration of predictive analytics using Machine Learning and Fuzzy Logic.
Co-Authors Abie Pratama Adi, Roni Adian Fatchur Rohim Afdhol Dzikri Agung Riyadi Agus Fatulloh Agus Fatulloh Ahmad Hamim Thohari Ahmad Hamim THohari Ahmad Hamim Tohari Andikha, Andikha Ari Novriansyah Arnomo, Sasa Ani Atalarik Ramli Aulia Agung Dermawan Aulia Agung Dermawan Azis Saputra Bagus Wardana Bisma Khairunnas Budi Arif Dermawan condra antoni Defriyanuar Dhining Desi Ratna Sari Dian Nurdiansyah Dimas Akmarul Putera Dodi Prima Resda Dodi Prima Resda Dwila Sempi Yusiani Eka Mutia Lubis Evita S.Tr.Kom Fadila, Aminudin Fadli Suandi Fauziah Mahmuda Finkye Priya Gunadi Firmal Firmal Hamdani Arif Hamdani Arif Handry Elsharry Adriyanto Hartadi, Nanda Rachmat Herman, Nanna Suryana Heru Wijanarko Hilda Widyastuti Iqbal Maulana Jaman, Jajam Haerul John Friadi Jorvick Steve Kerobaganet Kerobaganet Kusworo Adi Leman, Abdul Mutalib M. Yudha Putra Maidel Fani Maidel Fani Marga Raharja, Adyk Marselina, Sonia Maryani Septiana Maya Armys Roma Sitorus Mira Chandra Kirana Mirza Oktanizar Muchammad Fajri Amirul Nashrullah Muchammad Fajri Amirul Nashrullah Muhamad Naharus Surur Muhammad Agus Muljanto Muhammad Idris Muhammad Nashrullah Muhammad Zainuddin Lubis Narupi Narupi Narupi Narupi, Narupi Nelmiawati Nelmiawati Nelmiawati Nelmiawati Nur Cahyono Kushardianto Nur Cahyono Kushardianto Nur Imma Aulia Astori Permatasari, Ismi Aprilianti Prasetyawan, Purwono Pujiyono Pujiyono Rafi Dio Raynold, Raynold Resda, Dodi Prima Ridho Hafiedz Rifaldi Herikson Rina Yulius Riwinoto, Riwinoto Rizky Pratama Hudhajanto Rizky Pratama Hudhajanto Rokhayati, Yeni Satriya Bayu Aji Selly Tri Amanda Siahaan, Arta Uly Sudra Irawan Supardianto Supardianto Syafarudin Fani Thohari, Ahmad Hamim Tian Havwini Ummatin, Kuntum Khoiro Uuf Brajawidagda Vonega, Defangga Aby Wenang Anurogo Wirabuana Sakti Yan Prada Hasibuan Yosi Handayani