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Jurnal ICT : Information Communication & Technology
Published by STMIK IKMI Cirebon
ISSN : 23020261     EISSN : 23033363     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal ICT : Information Communication & Technology (JICT) (p-ISSN: 2302-0261, e-ISSN: 2303-3363 ) is a scientific journal and open access journal published by Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) of STMIK IKMI Cirebon, Indonesia. Jurnal JICT covers the field of Informatics, Computer Science, Information Technology and Communication. It was firstly published in 2012 for a printed version. The aims of Jurnal JICT are to disseminate research results and to improve the productivity of scientific publications. Jurnal JICT is published two times a year (July and December).
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Articles 268 Documents
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Gamifikasi untuk Meningkatkan Partisipasi Masyarakat Dalam Mendukung Konsep Ketahanan Terhadap Bencana Asep Id Hadiana; Rezki Yuniarti; Agus Komarudin
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

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This study discusses the use of gamification techniques in enhancing community involvement in disaster emergency planning activities. The objective of this study is to explore how gamification can be incorporated into disaster emergency planning programs to enhance disaster resilience in West Bandung Regency. The study was conducted by collecting data from respondents through online questionnaires and structured interviews to evaluate the effectiveness of gamification techniques in motivating community participation in disaster emergency planning. The results show that the use of gamification techniques can increase community participation in disaster emergency planning programs and can also influence the democratic process. Therefore, this study provides evidence that the use of gamification techniques can be an effective tool in enhancing the efficiency and intelligence of disaster emergency planning and can help achieve the goal of disaster resilience in West Bandung Regency.
Pengembangan Sistem Aplikasi Simulasi Arus dan Level Berbasis Website Menggunakan Teknologi Microservice: Pengembangan Sistem Aplikasi Simulasi Arus dan Level Berbasis Website Menggunakan Teknologi Microservice Sela Sela
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

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Abstract

Pemodelan kelautan merupakan salah satu cara dalam melakukan kajian di bidang kelautan. Jurusan Ilmu Kelautan FMIPA UNTAN menjadikan Pemodelan Kelautan sebagai mata kuliah yang wajib diambil oleh mahasiswa. Pemodelan kelautan menuntut penggunanya untuk memiliki perangkat komputer yang memenuhi spesifikasi tertentu. Hal ini dikarenakan, dalam suatu simulasi biasanya diperlukan waktu komputasi yang relatif lama. Selain itu keterbatasan jumlah komputer dan kepemilikan komputer oleh mahasiswa merupakan masalah utama yang terjadi selama kegiatan belajar mengajar pemodelan laut pada mahasiswa Ilmu Kelautan FMIPA UNTAN. Penelitian ini bertujuan untuk melakukan pengembangan dari sistem aplikasi pemodelan kelautan khususnya pada simulasi arus dan level air, sehingga mahasiswa dapat melakukan simulasi dengan mudah tanpa terkendala spesifikasi perangkat komputer tertentu, aplikasi yang akan dikembangkan berbasis website dengan menerapkan teknologi microservice dalam menjalankan beberapa service pada aplikasi. Selain itu, untuk memenuhi infrastruktur kebutuhan komputasi akan menggunakan layanan cloud computing dari Google yaitu Google Cloud Platform (GCP) bertujuan untuk membangun sebuah server, yang mana server dibangun melalui menu Google Compute Engine (GCE). Pengembangan sistem aplikasi ini telah dilakukan pengujian fungsional kepada pihak Jurusan Ilmu Kelautan FMIPA Untan dan memperoleh hasil sesuai dengan rancangan serta dapat melakukan simulasi. Sedangkan pengujian antarmuka sistem memperoleh presentasi sebesar 87,11%.
Analisis Segmentasi Pelanggan Menggunakan Metode K-Means Clustering Khaerul Anam; Dadang Sudrajat; Dian Ade Kurnia
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

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Teknologi berbasis computerized dewasa ini dapat diaplikasikan sebagai instrumen pendukung kegiatan pada berbagai bidang usaha dalam rangka mencapai tujuan pekerjaan dengan efektif dan efisien. Teknologi computerized data mining dibutuhkan untuk membantu kegiatan promosi dengan membuat segmentasi pelanggan berdasarkan data transaksi sebelumnya. Segmentasi pelanggan dapat dimanfaatkan sebagai indikator nilai pelanggan (customer value), dalam hal ini perusahaan akan dapat menilai kelompok pelanggan mana yang memberikan keuntungan besar bagi perusahaan. Penelitian ini bertujuan untuk membuat segmentasi pelanggan dari sebuah supermarket dengan K-Means clustering. Hasil eksperimen clustering didapatkan nilai k = 2 sebagai cluster terbaik dengan nilai DBI 0,527 dan nilai centroid distance 1,4821. Kelompok data pada Cluster 0 berjumlah 109 data sedangkan pada cluster 1 berjumlah 231 data dan total semua data adalah 340. Segmen data dari hasil clustering dideskripsikan menjadi segmen konsumen prioritas dan dan konsumen biasa yang dapat menjadi informasi pendukung untuk divisi marketing dalam menentukan strategi pemasaran yang relevan dengan konsumen untuk meningkatkan Customer Lifetime Value.
Pencarian Stasiun Kereta Terdekat dengan Algoritma A Star Berbasis Android di Area Stasiun Wilayah Bekasi Ikhsan Dwikurniawan; Herlawati .; Robertus Suraji
Jurnal ICT: Information Communication & Technology Vol. 21 No. 2 (2021): JICT-IKMI, Desember 2021
Publisher : LPPM STMIK IKMI Cirebon

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Abstract

Transportasi telah menjadi salah satu kebutuhan yang sangat penting dalam kegiatan sehari-hari di kehidupan bermasyarakat. Kemajuan teknologi informasi yang ada saat ini, dapat digunakan sebagai sarana untuk meningkatkan pelayanan umum, salah satunya adalah di bidang perkeretaapian. Dengan adanya kemajuan teknologi informasi dapat memudahkan masyarakat untuk mengetahui informasi secara cepat dan mudah, tetapi masih ada beberapa kendala yaitu kurangnya informasi mengenai rute stasiun terdekat. Penelitian ini bertujuan untuk membuat aplikasi pencarian Stasiun terdekat berbasis android dengan rute terpendek menuju Stasiun tujuan dengan menggunakan Algoritma A-STAR. Algoritma A-STAR ialah algoritma yang mencari rute terpendek untuk mencapai tujuan yang diharapkan. Tahapannya yaitu 1) Memasukkan node awal ke open list. 2) Melakukan looping. 3) Simpan rute secara backward, urutkan mulai dari node goal ke parent-nya sampai ke node awal bersamaan menyimpan node-nya ke dalam sebuah array. Pada penelitian ini Stasiun Kranji, Stasiun Bekasi, Stasiun Bekasi Timur, Stasiun Tambun, Stasiun Cibitung, Stasiun Telaga Murni, Stasiun Cikarang. Pengujian pada penelitian ini dilakukan dengan pengujian black box testing dan pengujian perbandingan antara algoritma A-STAR dengan Google Map, hasilnya diperoleh menunjukan lebih banyak algoritma A-STAR berhasil dengan jarak terpendek, walaupun ada Algoritma A-STAR yang hasil sama dengan Google Maps, dan algoritma A-STAR ada juga yang menunjukkan jarak yang lebih jauh dibandingkan Google Maps
Penerapan Algoritma C4.5 Pada Imbalanced Dataset Untuk Memprediksi Kegagalan Angsuran Properti Devit Setiono; Yodi Susanto; Mohammad Syafrullah
Jurnal ICT: Information Communication & Technology Vol. 21 No. 2 (2021): JICT-IKMI, Desember 2021
Publisher : LPPM STMIK IKMI Cirebon

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In this research, the data collection carried out by studying the patterns of consumers who fail to pay, which aimed to build a model so that it could be used in predicting customers who have the potential to fail to pay. The research used the Cross-Industry Standard Process for Data Mining (CRISP-DM) method with details of the business understanding process, data understanding, data preparation, modeling, evaluation and deployment / interpretation. The dataset in this research was taken from sales, cancellation and consumer data from January 2016 to December 2019. Because the dataset in this research was an imbalanced dataset, the researchers tried to use Synthetic Minority Oversampling Technique (SMOTE) in handling the imbalanced dataset. The research conducted a comparison of the value of accuracy, precision, recall, f measure and Area Under the ROC Curve (AUC) between the original dataset and the dataset for the addition of the SMOTE technique to several algorithms including C4.5, K-NN and Naïve Bayes. The attributes used in this research were source of funds, purpose of purchase, age, selling price, occupation, total installments, percentage of total installments, monthly installments, percentage of late installments and status. From the comparison, it was found that the C4.5 algorithm with the SMOTE 480% dataset had the highest accuracy value of 97.62%, precision of 0.976, recall of 0.976, f measure of 0.976 and AUC of 0.986 which meant Excellent Classification. From the research conducted, it was expected that the model formed on the imbalanced dataset with the C4.5 and SMOTE algorithms could be used to predict consumer installment failures.
Analisis Sentimen Data Twitter Tentang Ekonomi Sirkular Menggunakan Algoritma Neural Network Berbasis Particle Swarm Optimization Fatihanursari Dikananda; Ahmad Rifa'i; Gifthera Dwilestari
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

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The circular economy is a renewable and resilient industrial system that "eliminates" the end product cycle by implementing new procedures and business models, using renewable energy and chemicals. Develop use-based products for waste elimination and minimization. Some activities in the circular economy in people's lives include innovative solutions in plastic waste management, supply chain management, and charcoal briquettes from dry leaves. One application of the principles of a circular economy, such as waste management, is to classify, manage and develop plastic waste into a circular economy of valuable plastic waste. This means that it can support the economic life of the community. This study aimed to find out public opinion regarding the circular economy, which was conveyed through social media Twitter. Based on the reviews and public opinion about the circular economy that was shared through the Twitter media, sentiment analysis was conducted by classifying these opinions into positive, negative, and neutral reviews. The method used in this research is a machine learning technique with a neural network algorithm based on particle swarm optimization (PSO). The results of this research on Twitter data sentiment analysis on circular economy obtained a population size of 4 for particle swarm optimization parameters so that the accuracy rate reaches 75%. Using the neural network+PSO algorithm, while using the neural network algorithm alone, it gets an accuracy rate of 71.67%.
Penentuan Kelayakan Pembiayaan Pada Koperasi Syari'ah Mitra Insan Mandiri Menggunakan Metode Simple Additive Weighting; Yusuf Sumaryana; Gea Aristi
Jurnal ICT: Information Communication & Technology Vol. 21 No. 1 (2021): JICT-IKMI, Juli 2021
Publisher : LPPM STMIK IKMI Cirebon

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Abstract

The assessment of the feasibility of financing carried out by the Cooperative for Savings and Loans and Syari'ah Partners Insan Mandiri is still using the manual method, which is carried out by cooperative officers. In this case, there needs to be an effort to improve services in providing financing, so a decision support system is made to determine the feasibility of using the Simple Additive Weighting Method. The scoring system is carried out using the 5C Criteria, namely Character, Capacity, Capital, Collateral, Condition of Economy. This decision support system results in a more precise and accurate creditworthiness assessment. The results can certainly minimize the risk of bad credit or other problems that can harm the Savings and Loans Cooperative and Syari'ah Mitra Insan Mandiri financing. The process of determining the feasibility of this financing goes through 5 (five) stages, namely (1) Determining criteria and alternatives, (2) Determining the weight of each criterion, (3) Creating a matrix of each criterion, (4) Normalizing the Matrix, (5) Ranking the results alternative recommendations.
Perancangan Sistem Informasi Pengelolaan Bank Sampah Sebagai Implementasi Sirkular Ekonomi Menggunakan Metode Waterfall Ahmad Rifai; Fatihanursari Dikananda; Raditya Danar Dana
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

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Abstract

Polusi yang dihasilkan dari proses produksi dan konsumsi manusia telah menimbulkan dampak negatif terhadap lingkungan. Maka itu, pemerintah kini mencanangkan sebuah konsep ekonomi sirkular atau konsep yang lebih baru dari ekonomi linier tradisional. Berdasarkan hasil observasi melalui proses wawancara di Dinas Lingkungan Hidup Kabupaten Cirebon diidentifikasi permasalahan berupa sulitnya nasabah bank sampah dalam mendapatkan informasi berkenaan dengan harga standar jual sampah. Permasalahan lain yang ditemukan adalah sistem pencatatan yang tidak sinkron antara pencatatan saldo dan deposit di sisi Nasabah dan pencatatan disisi pengelola Bank dari hasil penjulan sampah yang dilakukan oleh nasabah. Oleh karena itu, tujuan penelitian ini bertujuan untuk mengembangkan sistem pengelolaan sampah berbasis Teknologi Informasi agar pencatatan keuangan dan distribusi informasi lebih optimal dan mudah diakses dengan menggunakan metode Waterfall karena beberapa kelebihan yang ditawarkan diantaranya proses pengembangan dengan pendekatan secara bertahap mulai dari fase identifikasi kebutuhan pengembangan perangkat lunak, design, pengujian hingga perawatan system. Hasil dari penelitian Perancangan Sistem Informasi Pengelolaan Bank Sampah Sebagai Implementasi Sirkular Ekonomi Menggunakan Metode Waterfall ini
Peningkatan Keamanan Aplikasi Web Menggunakan Web Application Firewall (WAF) Pada Sistem Informasi Manajemen Kampus Terintegrasi Randi Rizal; Yusuf Sumaryana
Jurnal ICT: Information Communication & Technology Vol. 21 No. 2 (2021): JICT-IKMI, Desember 2021
Publisher : LPPM STMIK IKMI Cirebon

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Increasing the security of web applications on the integrated campus management information system needs to be done because the application is accessed by public networks so that there are many attacks and attempts to prevent threats from attackers. This study applies a Web Application Firewall (WAF)-based application security using ModeSecurity and Core Rules Set from Owasp which aims to improve the security system of the web application by using a firewall.This study uses an experimental method by implementing a Web Application Firewall (WAF) as a web-based protection system, then the process of analysis and testing to obtain accurate advice on firewall implementation. The results of this study indicate that the firewall used with Web Application Firewall (WAF)-based ModeSecurity has succeeded in stopping attacks from attackers using Cross Site Scripting (XSS) and SQL Injection methods.
Penerapan Strategi Promosi Kampus Menggunakan K-Means Di STMIK IKMI Cirebon Bani Nurhakim; Khaerul Anam; Iin
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

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Abstract

Admission of new students is an essential activity for universities. As the functional process of student admissions progresses, data on student admissions increases from one year to the next. However, the new student admission data has not been used by universities for decision-making, the potential for promotion, and consideration of the admission path. This study aims to classify student data into several groups considering the proximity of the data has similarities. So that student data who have the exact attributes are collected in one group, and those with different features are contained in another group, using a data mining process, namely the k-means smart clustering strategy. The business intelligence system in this study expands institutional excellence by using various data and information driven by institutions as an ingredient in the decision-making cycle. The method used by the author is knowledge discovery in databases (KDD) which consists of Data, Data Cleaning, Data transformation, Data mining, Pattern evolution, and knowledge. Tests are carried out using RapidMiner tools to help find the right results to overcome these problems. Finally, the results of this study are used as a reason to pursue choices in decision-making and determine promotion strategies based on groups formed from institutions.

Page 18 of 27 | Total Record : 268

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