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CLUSTERING KEJADIAN BENCANA ALAM di JAWA BARAT BERDASARKAN JENIS BENCANA MENGGUNAKAN K-MEANS Indah Rosaliyah; Bani Nurhakim
E-Link: Jurnal Teknik Elektro dan Informatika Vol 18 No 1 (2023): Mei 2023
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/e-link.v18i1.5318

Abstract

Jawa barat merupakan salah satu wilayah dengan potensi bencana alam tinggi. Hampir semua jenis bencana sudah terjadi di setiap wilayahnya, seperti gempa bumi, tanah longsor, banjir, dan masih banyak lagi. Oleh karena itu, informasi mengenai tingkat terjadinya bencana alam di berbagai wilayah harus diteliti lebih lanjut agar lebih waspada kedepannya. Penelitian ini bertujuan untuk mengelompokkan kejadian bencana alam di Jawa Barat berdasarkan jenis bencana dengan memanfaatkan teknik clustering pada data mining. Proses pengelompokan data dilakukan menggunakan metode algoritma K-Means dan tahap perancangan yang digunakan yaitu Knowledge Discovery in Database (KDD). Dengan menggunakan tools RapidMiner diperoleh 6 cluster dengan nilai Davies Bouldin Index yaitu 9.20. Cluster 3 merupakan daerah dengan kejadian bencana alam sangat rendah, cluster 1 daerah dengan kejadian bencana alam rendah, cluster 4 daerah dengan kejadian bencana alam sedang, cluster 0 daerah dengan kejadian bencana alam tinggi 1, cluster 5 daerah dengan kejadian bencana alam tinggi 2, dan cluster 2 merupakan daerah dengan kejadian bencana alam sangat tinggi.
Analisis Tingkat Penggunaan Gadget pada Anak Usia Dini dengan menggunakan K-Mean Khaerul Anam; Rizal Rusyana; Bani Nurhakim; Denni Pratama
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10317

Abstract

The use of gadget devices in early childhood has become an increasing concern in recent years. influence on human thinking patterns because devices can find data quickly for children. Research on the consequences of using gadgets in early childhood has its own significance in understanding its impact on their development. In this study, an analysis was carried out on the level of gadget use in early childhood by applying the K-Means algorithm. The K-Means algorithm is used to group the level of gadget use in children, allowing the identification of groups that have similar characteristics. The aim of this research is to evaluate and understand the level of gadget usage by young children in response to technological developments, as well as to develop an effective method or approach in classifying their gadget usage patterns by utilizing the K-Means algorithm. Thus, this research aims to provide in-depth insight into gadget use patterns in young children, which can be the basis for developing better strategies or policies regarding technology use in this age group. From a total of 332 questionnaire responses, 14 groups were found based on the best DBI scores with different category distributions, namely "very often", "often", "sometimes", "rarely", and "never" with each percentage of 1 % (2 people), 24% (80 people), 0%, 71% (235 people) and 5% (15 people).
Implementasi Data Mining FP-Growth Untuk Analisis Pola Pembelian Pada Transaksi Penjualan Komariyah, Siti; Saeful Anwar; Bani Nurhakim
JURNAL MANAJEMEN DAN BISNIS EKONOMI Vol. 1 No. 2 (2023): April : JURNAL MANAJEMEN DAN BISNIS EKONOMI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (405.814 KB) | DOI: 10.54066/jmbe-itb.v1i2.128

Abstract

In the business world, efforts are needed as much as possible in gaining profits. The accuracy of marketing strategies can be seen from the consumer spending pattern database obtained from sales transactions on fashion products that are usually purchased simultaneously by customers. Information about the Pattern of Purchasing Customer Shopping that is Inaccurate at the Ayu Collection Online Shop Shop has caused promotional policy to be one of the causes of the store to suffer losses. One way to get an accurate customer shopping pattern is to use data mining. One of the methods contained in data mining is the association analysis method, in the association analysis there are several algorithms, one of which is the FP-Growth algorithm. In this study several association rules were found by applying the Frequent Pattern (FP-Growth) algorithm from the transaction database Fashion sales at Ayu Collection Online Shop. This association rules will later be used as decision making material to develop successful marketing and sales strategies. The findings of this study are in the form of product recommendations, namely the proposal of two or more items based on the findings of the FP-Growth algorithm using a 50% confidence value and a minimum support of 40%, this study uses assistance from the rapidminer tools version 9.9.
Bibliometrik Analisis: Brand Awareness Program Studi Diploma 3 Pada Database Scopus Bani Nurhakim; Dadang Sudrajat
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research aims to analyze the factors influencing brand awareness in the Diploma 3 program and to develop effective marketing strategies to enhance that awareness. The background of this study is based on the importance of brand awareness in influencing prospective students' decisions and public perception of the quality and reputation of educational institutions. This research employs survey and interview methods involving students, prospective students, and marketing staff from several higher education institutions in Indonesia. The data obtained were analyzed using statistical methods to identify the main factors affecting brand awareness. The results indicate that digital marketing and social media marketing play a significant role in increasing brand awareness of the Diploma 3 program. Consistent, innovative, and effective marketing strategies through social media have been proven to enhance recognition and appeal of the study program in the eyes of prospective students. This research makes an important contribution to the development of educational marketing strategies and offers new approaches to enhancing brand awareness of the Diploma 3 program. Thus, the results of this study are expected to assist educational institutions in increasing enrollment and retaining students by improving effective brand awareness
Edukasi Literasi Digital dan Anti Hoaks bagi Pelajar dan Masyarakat di Era Informasi Bani Nurhakim; Cep Lukman Rohmat; Reza Saputra; Rio Harsadino
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 03 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

The development of information and communication technology has brought significant impacts on society, particularly in terms of access to information, communication, and online learning. However, this progress also comes with various challenges, especially concerning digital security, the spread of hoaxes, and the low level of digital literacy among students and the general public. The lack of ability to distinguish between valid and invalid information, as well as limited awareness of online ethics and safety, has become an urgent issue that must be addressed through proper education. This Community Service Program (PKM) aims to improve digital literacy through training on internet safety and anti-hoax education for students and the local community in the partner area. The method used involves a participatory educational approach through seminars, interactive discussions, case studies, and simulations of information source verification. The training materials cover recognizing hoaxes and disinformation, using credible information sources, maintaining digital privacy, and practicing ethical communication on social media. The results of the program showed a significant increase in participants’ knowledge regarding hoax characteristics, fact-checking techniques, and the importance of maintaining a responsible digital footprint. Participants also became more critical in consuming information and demonstrated behavioral changes in using the internet safely and responsibly. This training not only enhances individual capacity but also strengthens social resilience in facing the flow of information in the digital era. This program is expected to serve as a sustainable effort in fostering a culture of healthy and wise digital literacy, and it can be replicated in schools and other communities to broaden its impact.
Pelatihan Analisis Bibliometrik Berbasis Vosviewer dan Publish or Perish Bagi Dosen Kopertip Indonesia Dadang Sudrajat; Bani Nurhakim; Suteja; Syaiful Imanudin
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 03 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Strengthening the research capacity of university lecturers is a crucial aspect of improving the quality of higher education in Indonesia. One relevant skill to support research development and scientific publication is the ability to conduct bibliometric analysis. This analysis is useful for mapping research trends, identifying scientific collaborations, and determining potential research topics through the study of references and citations. This Community Service Program (PKM) aims to provide training in bibliometric analysis using the software tools VOSviewer and Publish or Perish for lecturers affiliated with Kopertip Indonesia (Coordinator of Indonesian Private Universities). The training was conducted both online and offline, using a combination of theoretical and practical approaches. The materials covered included basic bibliometric concepts, methods for accessing scholarly publication data (e.g., from Google Scholar and Scopus), and hands on practice using Publish or Perish to extract bibliometric data and VOSviewer to visualize the analysis results in the form of term maps and author collaboration networks. The training was also complemented by case studies from various fields of science. Evaluation results indicated that the training improved participants’ understanding and skills in using both tools. Participating lecturers reported increased confidence in mapping research topics, selecting relevant journals, and planning more targeted publication strategies. This activity not only enhanced digital research competencies but also encouraged lecturers to be more productive in contributing to national and international scientific outputs. In the future, this type of training can be replicated across other higher education environments as part of efforts to strengthen a data-driven academic ecosystem.