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All Journal Information System for Educators and Professionals : Journal of Information System JITK (Jurnal Ilmu Pengetahuan dan Komputer) Tematik : Jurnal Teknologi Informasi Komunikasi Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Ekonomi, Bisnis dan Manajemen Jurnal Sistem Informasi dan Teknologi (SINTEK) AMMA : Jurnal Pengabdian Masyarakat
Bani Nurhakim
STMIK IKMI CIREBON
Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Other

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Implementasi Algoritma K-Means Dalam Pengelompokan Jumlah Wisatawan Akomodasi Di Jawa Barat Neni Lusianah; Ade Irma Purnamasari; Bani Nurhakim
Jurnal Ekonomi, Bisnis dan Manajemen Vol. 2 No. 1 (2023): Maret: Jurnal Ekonomi, Bisnis dan Manajemen
Publisher : FEB Universitas Maritim Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58192/ebismen.v2i1.682

Abstract

Akomodasi merupakan orientasi sosial yang bermakna keutuhan sosial demi menjauhi serta mendamaikan kegentingan, pertikaian yang saling berkaitan. Seumpama bentuk kegiatan akomodasi yang bermanfaat mempersiapkan perlengkapan guna melengkapi keperluan. provinsi jawa barat terdapat tempat wisata yang ramai dikunjungi oleh wisatawan nusantara dan mancanegara oleh sebab itu pengunjung menggunakan fasilitas akomodasi yang tersedia di setiap daerah, wisatawan nusantara ramai menginap di villa sedangkan wisatawan mancanegara lebih memilih hotel berbintang. Penelitian ini memfokuskan bagaimana pengelompokan wisatawan daerah wisata akomodasi dan jenis wisatawan terbanyak yang ramai berkunjung menggunakan algoritma k-means, analisis ini memakai metode Knowledge Discovery in Database (KDD). Teknik pengumpulan data atau pengumpulan data bersumber dari Dinas Pariwisata dan Kebudayaan Provinsi Jawa Barat. Dengan tujuan kiranya menjadi pengetahuan untuk wisatawan serta mampu mempublikasikan wisata di media sosial dan diharapkan akan lebih meningkat jumlah wisatawan yang berkunjung dan meningkatnya pembangunan sarana dan prasarana di setiap daerah akomodas.Hasil dari penelitian ini bahwa daerah akomodasi yang ramai dikunjungi adalah Kota Bandung dengan jenis wisatawan yang datang yaitu pengunjung dalam negeri (Nusantara).
SMART ATTENDANCE TRACKING SYSTEM EMPLOYING DEEP LEARNING FOR FACE ANTI-SPOOFING PROTECTION Bani Nurhakim; Ahmad Rifai; Dian Ade Kurnia; Dadang Sudrajat; Ujang Supriatna
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.5992

Abstract

Conventional attendance systems face challenges in accuracy and efficiency, often vulnerable to spoofing and data manipulation. This study addresses these issues by developing a smart attendance system integrating Deep Learning-based facial recognition with anti-spoofing technology. The system ensures secure and reliable attendance authentication while automating and enhancing management processes. Utilizing a convolutional neural network (CNN) architecture, the system processes raw facial images directly without additional feature extraction, improving accuracy and efficiency. A novel training strategy, termed 50 Random Samples-30 Sub-epochs Count-1 Epoch, is introduced to optimize the training process. This strategy involves random sampling during each forward pass and grouping 30 passes as one epoch, enabling the use of complex CNN architectures and automatic dataset expansion. The system achieves 98.90% accuracy in identifying genuine attendance, maintaining a confidence level above 80%, significantly reducing spoofing risks and errors. This innovative solution has significant implications, particularly for educational institutions. It automates attendance tracking, minimizes manual effort, reduces errors, and supports disciplinary enforcement through accurate data. Moreover, its scalability allows for application across various environments, offering benefits to a wide range of institutions. By enhancing data accuracy and operational efficiency, this system sets a foundation for smarter, more reliable attendance management, strengthening administrative practices in education and beyond.
Penyuluhan Pola Hidup Sehat Dan Literasi Digital Bagi Pelajar Desa Tarikolot Untuk Meningkatkan Kesadaran Teknologi Bani Nurhakim; Cep Lukmanrohmat; Aziz Alma’as; Muhamad Yoni Ardiansah
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 2 : Maret (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

This community service program aims to increase awareness of healthy living habits and digital literacy among students in Tarikolot Village as an effort to improve their well-being and readiness to face challenges in the digital era. Based on initial observations, students in Tarikolot Village still have unhealthy eating habits, lack physical activity, and pay little attention to personal and environmental hygiene. In addition, the use of digital technology among students is still limited to entertainment, such as playing games and accessing social media, without understanding the positive potential and risks of using technology wisely. This program was implemented through interactive counseling, hands-on practice, simulations, and mentoring. The material presented in this activity includes health education such as the importance of balanced nutrition, personal hygiene, and physical activities. Meanwhile, the digital literacy materials cover safe internet usage, ethics in social media, hoax identification, and utilizing technology for learning and digital economic opportunities. The results of this program indicate an increase in students' understanding and behavioral changes. Around 80% of participants began to implement healthy habits such as proper handwashing, choosing nutritious foods, and engaging in regular physical activity. In addition, participants became wiser in using social media, were able to identify hoaxes, and started utilizing the internet for productive purposes such as online learning. The outcomes of this program include educational modules on healthy living and digital literacy, educational videos, infographics, and certificates for participants. This program is expected to create a young generation that is healthy, smart, and wise in using technology so that they can face the challenges of the digital era more effectively and responsibly.
Peningkatan Kapasitas Pemasaran Produk Melalui Marketplace Dan Media Sosial Untuk UMKM Bani Nurhakim; Cep Lukman Rohmat; Gilang Atha Anantyo Putra; Hikmaludin Bakhtiar Ilmi
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2023): AMMA : Jurnal Pengabdian Masyarakat (INPRESS)
Publisher : CV. Multi Kreasi Media

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Abstract

This community service program aims to improve the knowledge and skills of Micro, Small, and Medium Enterprises (MSMEs) in utilizing digital marketing, marketplaces, and social media as effective product promotion strategies. The problems faced by MSME partners include low digital literacy, suboptimal use of marketplaces, difficulties in creating attractive promotional content, limited advertising budgets, and lack of confidence in using digital technology. Therefore, the solution offered in this program was through intensive training on digital marketing, marketplace utilization, social media strategies, and the creation of promotional content. The implementation methods involved identifying partner problems, preparing training modules, conducting hands-on workshops, as well as providing mentoring and monitoring. The results of this activity showed a significant increase in participants' understanding of digital marketing and managing marketplace accounts. Participants were able to independently create marketplace and business social media accounts, upload their products, and produce attractive promotional content. In addition, participants began to understand effective paid advertising strategies and were able to apply them in their product promotions. The outcomes of this program included active marketplace accounts, business social media accounts, quality promotional content, digital marketing training modules, and the formation of a digital MSME community as a platform for sharing experiences and support. This program is expected to encourage MSMEs to be more independent, expand their market reach, increase sales, and compete optimally in the digital era. The sustainability of this program is supported by continuous mentoring and online mentoring groups as a means of consultation and further development for MSME actors.
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.
Peningkatan Kinerja SVM pada Klasifikasi Sentimen Ulasan iPusnas Berbasis Imbalance Handling Akmal Mustafa; Rudi Kurniawan; Bani Nurhakim; Puji Pramudya Marta; Khaerul Anam
Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Vol. 8 No. 1 (2026): Edisi April
Publisher : Universitas Harapan Medan

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Abstract

This study investigates sentiment classification of user reviews on the iPusnas digital library application to provide an objective overview of service quality and user experience. Numerous complaints related to login failures, application crashes, and issues in accessing digital books indicate the need for a computational approach capable of processing large volumes of user feedback. The proposed method integrates Natural Language Processing (NLP) techniques with the Support Vector Machine (SVM) algorithm. The workflow consists of collecting 2,000 reviews, applying text cleaning and normalization, tokenization, stopword removal, stemming, rating-based sentiment annotation, and feature extraction using TF-IDF. The dataset was divided using a train–test split for model training and evaluation. Experimental results show that the SVM model achieves 90.1% accuracy, demonstrating strong performance in detecting negative sentiments and moderate performance for positive sentiments due to class imbalance. These  findings highlight the effectiveness of NLP and SVM for extracting user perceptions and indicate the potential of this model as a decision-support tool for improving iPusnas application services. Overall, the study contributes to the advancement of digital service innovation in Indonesia.
Klasifikasi Tingkat Kesejahteraan Masyarakat Desa Cikuya Berdasarkan Data Sosial Ekonomi Menggunakan Algoritma Nive Bayes Ramdan Irawan; Rudi Kurniawan; Bani Nurhakim; Arif Rinaldi; Fathurrahman
Jurnal Sistem Informasi dan Teknologi Vol 6 No 1 (2026): Jurnal Sistem Informasi dan Teknologi (SINTEK)
Publisher : LPPM STMIK KUWERA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56995/sintek.v6i1.203

Abstract

Penentuan tingkat kesejahteraan masyarakat memiliki peran penting dalam proses penyaluran bantuan sosial di tingkat desa. Namun, pendataan berbasis observasi manual masih menghadirkan potensi bias subjektif dan ketidakkonsistenan dalam pengambilan keputusan. Penelitian ini bertujuan mengembangkan model klasifikasi tingkat kesejahteraan masyarakat Desa Cikuya menggunakan algoritma Naïve Bayes sebagai pendekatan berbasis data yang lebih objektif. Tahapan penelitian meliputi pengumpulan data sosial ekonomi, pra-pemrosesan, encoding variabel kategorik, normalisasi variabel numerik, pelatihan model Gaussian Naïve Bayes, serta evaluasi menggunakan metrik akurasi, precision, recall, dan f1-score. Hasil penelitian menunjukkan bahwa model menghasilkan akurasi sebesar 98,33%, yang menunjukkan performa klasifikasi yang sangat baik. Analisis lebih lanjut mengindikasikan bahwa variabel pendapatan dan kondisi fisik rumah memiliki peranan paling dominan dalam membedakan kategori kesejahteraan. Model yang dikembangkan tidak hanya berfungsi sebagai alat klasifikasi, tetapi juga dapat dimanfaatkan sebagai sistem pendukung keputusan bagi pemerintah desa untuk menilai status kesejahteraan masyarakat secara lebih cepat, konsisten, dan bebas bias subjektif. Penelitian ini memberikan kontribusi pada pemanfaatan teknologi pembelajaran mesin dalam pemetaan kesejahteraan masyarakat, meskipun masih memiliki keterbatasan pada jumlah variabel dan cakupan data lokal. Temuan ini diharapkan dapat menjadi dasar pengembangan sistem penyaluran bantuan yang lebih tepat sasaran dan transparan.
Analisis Sentimen Ulasan by.U dengan Pelabelan Rating dan Leksikon Menggunakan Multinomial Naïve Bayes Fatihanursari Dikananda; Bani Nurhakim; Dian Ade Kurnia; Ahmad Rifai; Mugi Praseptiawan
TEMATIK Vol. 13 No. 1 (2026): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2026
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v13i1.2996

Abstract

Perkembangan layanan telekomunikasi digital mendorong bertambahnya jumlah ulasan pengguna yang digunakan sebagai bahan informasi guna mendukung pengambilan keputusan berbasis data. Penelitian ini bertujuan menganalisis sentimen ulasan aplikasi by.U menggunakan dua metode pelabelan data, yaitu rating-based labeling dan lexicon-based labeling, menggunakan algoritma Multinomial Naïve Bayes (MNB). Metode penelitian menerapkan framework Knowledge Discovery in Databases yang meliputi tahapan selection, preprocessing, transformation, data mining, dan evaluation. Dataset penelitian diperoleh dari Google Play sebanyak 8.000 ulasan berbahasa Indonesia. Tahap prapemrosesan mencakup cleaning, case folding, normalisasi, tokenisasi, stopword removal, serta stemming. Representasi fitur dilakukan menggunakan TF-IDF, sedangkan penyeimbangan data diterapkan melalui metode SMOTE. Evaluasi model dilakukan menggunakan metrik accuracy, precision, recall, dan F1-score dengan skema 10-fold cross validation. Hasil penelitian menunjukkan bahwa pendekatan lexicon-based labeling memberikan performa yang lebih baik dibandingkan rating-based labeling. Pendekatan rating-based menghasilkan accuracy sebesar 82,59%, precision 83,79%, recall 82,59%, dan F1-score 82,43%. Sementara itu, pendekatan lexicon-based memperoleh accuracy sebesar 88,96%, precision 89,69%, recall 88,96%, serta F1-score 88,91%. Temuan tersebut menunjukkan bahwa strategi pelabelan memiliki pengaruh terhadap performa klasifikasi sentimen. Pendekatan berbasis leksikon dinilai lebih efektif karena mampu memahami konteks linguistik dan ekspresi emosional pengguna secara lebih baik dibandingkan pendekatan berbasis rating.
Application of Support Vector Machine for Classification of Toddlers Nutritional Status Based on Anthropometric Data Mohamad Alif Subhi; Rudi Kurniawan; Bani Nurhakim
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1844

Abstract

Stunting remains a major health issue in Indonesia, especially among toddlers. This study aims to classify the nutritional status of toddlers (stunted and non-stunted) using anthropometric data from the Kaggle public dataset with the Support Vector Machine (SVM) algorithm. This dataset includes data on the height, weight, age, and gender of toddlers. It should be emphasized that the data does not originate from the Ciherang Bandung Posyandu, but rather the Posyandu is used only as a context for the potential application of the developed model. The process includes data acquisition, preprocessing (including normalization and data balancing using SMOTE), SVM model training, and evaluation with accuracy, precision, recall, F1-score, and ROC-AUC. The model was trained with an 70:30 data split and optimal parameters (C=1.0, gamma=0.01, kernel=RBF). The results showed high performance, indicating that this model can support early detection of stunting and the implementation of decision support systems in public health services.
Co-Authors Ade Irma Purnamasari Ahmad Rifai Akmal Mustafa Arif Rinaldi Arif Rinaldi Dikananda Aziz Alma’as Cep Lukman Rohmat Cep Lukmanrohmat Dadang Sudrajat Dian Ade Kurnia Fathurrahman Fatihanursari Dikananda Gilang Atha Anantyo Putra Hikmaludin Bakhtiar Ilmi Khaerul Anam Mohamad Alif Subhi Muhamad Yoni Ardiansah Muhammad Khoerul Ikhwan Neni Lusianah Praseptiawan, Mugi Puji Pramudya Marta Putri Indah Lestari Ramdan Irawan Revan Faturochman Reza Saputra Rifki Hermawan Rio Harsadino Rudi Kurniawan Ryan Hamonangan Ryan Ryan Agung Prasetyo Suteja Syaiful Imanudin Ujang Supriatna Willy Prihartono