Article Per Year (5 Year)
p-Index From 2021 - 2026
4.925
P-Index
This Author published in this journals
All Journal Techno.Com: Jurnal Teknologi Informasi Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JPM (Jurnal Pemberdayaan Masyarakat) Jurnal Eksplora Informatika SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan IJISTECH (International Journal Of Information System & Technology) Informasi Interaktif Jurnal Tekno Kompak JEMMA | Journal of Economic, Management and Accounting Jurnal Teknologi Informasi dan Multimedia Jurnal Manajemen Informatika dan Sistem Informasi Management and Sustainable Development Journal IJISTECH Media Jurnal Informatika ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Interaktif: Warta Pengabdian Pendidikan (JIWPP) Rengganis Jurnal Pengabdian Masyarakat MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Paradigma Journal of Artificial Intelligence and Digital Business Bakti Sekawan : Jurnal Pengabdian Masyarakat
Rifqi Hammad
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 34 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 34 Documents
Search

 1   2   3   4 
Geolocation data incorporation in Mapbox for comprehensive mapping of tourism areas on Lombok Island Rifqi Hammad; Pahrul Irfan; M Thoric Panca Mukti
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 14 No. 1 (2024): Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

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

Abstract

Lombok Island is one of the islands that has many tourist areas. With so many tourist areas spread to various regions on the island of Lombok, an accurate and comprehensive tourist area mapping system is needed. The problem faced is that the existing mapping is still constrained regarding accuracy and data persistence. The solution offered in this research is the incorporation of geolocation data on the Mapbox platform to improve the accuracy and detail of data in mapping tourism areas on the island of Lombok. In this research, there are several stages carried out starting from data collection to testing. This research results in a tourist area mapping information system that applies geolocation data incorporation on Mapbox. The test results show an increase in accuracy of 8% from the previous mapping and a usability test score of 81 which means that the system developed is acceptable or feasible by users.
Optimization of data integration using schema matching of linguistic-based and constraint-based in the university database Rifqi Hammad; Azriel Christian Nurcahyo; Ahmad Zuli Amrullah; Pahrul Irfan; Kurniadin Abd. Latif
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 11 No. 3 (2021): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v11i3.119-129

Abstract

University requires the integration of data from one system with other systems as needed. This is because there are still many processes to input the same data but with different information systems. The application of data integration generally has several obstacles, one of which is due to the diversity of databases used by each information system. Schema matching is one method that can be used to overcome data integration problems caused by database diversity. The schema matching method used in this research is linguistic and constraint. The results of the matching scheme are used as material for optimizing data integration at the database level. The optimization process shows a change in the number of tables and attributes in the database that is a decrease in the number of tables by 13 tables and 492 attributes. The changes were caused by some tables and attributes were omitted and normalized. This research shows that after optimization, data integration becomes better because the data was connected and used by other systems has increased by 46.67% from the previous amount. This causes the same data entry on different systems can be reduced and also data inconsistencies caused by duplication of data on different systems can be minimized.
Comparative Analysis of Stock Price Prediction Using Deep Learning with Data Scaling Method I Nyoman Switrayana; Rifqi Hammad; Pahrul Irfan; Tomi Tri Sujaka; Muhammad Haris Nasri
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2025): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i1.650

Abstract

The dynamic and unpredictable nature of stock prices makes accurate forecasting an important challenge in financial analysis. This study aims to compare the performance of three deep learning models, namely, Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), and Long Short-Term Memory (LSTM) in predicting stock prices on historical daily banking data from Yahoo Finance. The main objective is to determine the model that is best able to capture sequential patterns and temporal dependencies in stock price movements. Each model was trained and op-timized through data scaling, namely MinMax Scaler and Standard Scaler, with performance evaluated using Root Mean Square Error (RMSE) as the primary metric. Results show that while the RNN provides a basic approach, the GRU and LSTM models produce higher prediction accuracy, with GRU achieving the lowest RMSE thanks to its better ability to maintain long-term depend-encies. The RMSE achieved by RNN, GRU, and LSTM were 211.47, 158.89, and 197.45, respectively. The lowest error results were achieved when using MinMax Scaler. The use of MinMax Scaler here shows a better performance improvement with an average improvement of 22.57% compared to using Standard Scaler. This comparative analysis contributes to providing empirical insight into the relative effectiveness of the tested architectures. The findings suggest that the combination of GRU and MinMax Scaler can be a more reliable tool for financial forecasting, with the potential to develop more robust stock prediction applications under fluctuating market conditions.
Penerapan Sistem Informasi UMKM (SI-UM) berbasis web untuk meningkatkan pemasaran dan pengelolaan keuangan sahabat UMKM NTB Kurniadin Abd Latif; Rini Adriani Auliana; Rifqi Hammad
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 8, No 4 (2024): December
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v8i4.26783

Abstract

Abstrak Sahabat UMKM NTB merupakan salah satu komunitas UMKM yang ada di provinsi Nusa Tenggara Barat. Sahabat UMKM NTB sebagai mitra dalam kegiatan pengabdian ini memiliki anggota lebih dari 50 yang terlibat pada kegiatan tersebut. Permasalahan yang diahadapi oleh mitra adalah permasalahan dalam bidang pemasaran dan pengelolaan keuangan. Solusi yang ditawarkan oleh tim pengabdi adalah penerapan sistem informasi UMKM yang dapat membantu dalam pemasaran dan pengelolaan keuangan. Sehingga tujuan dari kegiatan pengabdian ini adalah membantu mitra dalam menerapkan sistem informasi UMKM yang dapat membantu mitra dalam pemasaran produk UMKM dan juga pengelolaan keuangannya. Metode yang dilakukan dalam kegiatan ini terdiri dari 6 tahapan yaitu sosialisasi, pengembangan sistem infromasi, pelatihan pendapingan, evaluasi dan keberlanjutan program. Hasil dari kegiatan ini adalah berupa penerapan sistem informasi UMKM yang dapat digunakan oleh mitra dalam memabntu mengatasi permasalahan di bidang pemasaran dan pengelolaan keuangan. Kata kunci: sahabat UMKM; pengabdian; sistem informasi umkm; pemasaran; pengelolaan keuangan Abstract Sahabat UMKM NTB is one of the MSME communities in West Nusa Tenggara province. Sahabat UMKM NTB as a partner in this service activity has more than 50 members involved in the activity. The problems faced by partners are problems in marketing and financial management. The solution offered by the service team is the implementation of an MSME information system that can assist in marketing and financial management. So that the purpose of this service activity is to assist partners in implementing MSME information systems that can help partners in marketing MSME products and also managing their finances. The method carried out in this activity consists of six stages, namely socialization, information system development, mentoring training, evaluation and program sustainability. The result of this activity is the implementation of an MSME information system that can be used by partners in overcoming problems in marketing and financial management. Keywords: sahabat UMKM; devotion; MSME information system; marketing; financial management
DIGITALISASI PEMBAYARAN KOS DAN HOMESTAY BERBASIS WEB MENGGUNAKAN VIRTUAL ACCOUNT DAN CONTENT-BASED FILTERING Yusril Mahenra Mahenra; Husain; Rifqi Hammad
Jurnal Manajemen Informatika dan Sistem Informasi Vol. 9 No. 2 (2026): MISI Juni 2026
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/misi.v9i2.1995

Abstract

Perkembangan pesat teknologi informasi dan komunikasi telah membawa perubahan signifikan pada berbagai sektor layanan, termasuk layanan akomodasi sementara seperti kos dan homestay. Namun demikian, proses pemesanan dan pembayaran masih sering dilakukan secara manual, yang mengakibatkan keterlambatan verifikasi pembayaran, ketidakakuratan pencatatan transaksi, serta kurangnya transparansi. Selain itu, pengguna kerap mengalami kesulitan dalam memilih hunian yang sesuai akibat banyaknya pilihan yang tersedia tanpa dukungan sistem rekomendasi yang memadai. Penelitian ini bertujuan untuk mengembangkan sistem pemesanan kos dan homestay berbasis web yang terintegrasi dengan pembayaran digital menggunakan Virtual Account, serta dilengkapi dengan sistem rekomendasi berbasis Content-Based Filtering yang memanfaatkan metode TF-IDF dan Cosine Similarity. Pengembangan sistem dilakukan menggunakan model Waterfall, dengan PHP dan JavaScript untuk implementasi web, Python Flask sebagai layanan rekomendasi, serta MySQL sebagai basis data. Sistem rekomendasi bekerja dengan mengolah konten hunian seperti fasilitas, lokasi, dan deskripsi untuk menghitung tingkat kemiripan dan menghasilkan rekomendasi Top-N. Hasil penelitian menunjukkan bahwa sistem berhasil mengintegrasikan fitur pemesanan, rekomendasi, dan pembayaran digital. Pengujian fungsional menunjukkan seluruh fitur sistem berjalan dengan baik, sementara pengujian sistem rekomendasi membuktikan kemampuannya dalam memberikan saran hunian yang relevan sesuai preferensi pengguna. Penggunaan Virtual Account memungkinkan verifikasi pembayaran secara otomatis serta meningkatkan transparansi transaksi. Secara keseluruhan, sistem yang dikembangkan mampu meningkatkan efisiensi dalam proses pemesanan dan pembayaran, sekaligus membantu pengguna dalam memilih hunian yang tepat melalui rekomendasi yang dipersonalisasi. Penelitian ini memberikan kontribusi dalam integrasi sistem pembayaran digital dan sistem rekomendasi dalam satu platform berbasis web untuk layanan akomodasi sementara.
Local Wisdom-Based Treatment Recommendation System for Tropical Diseases Using Bayesian Network and Association Rule Mining Muhammad Haris Nasri; Rifqi Hammad; Pahrul Irfan; I Nyoman Switrayana; Rahayun Amrullah Husaini
Media Jurnal Informatika Vol 18 No 1 (2026): Media Jurnal Informatika
Publisher : Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v18i1.6290

Abstract

Tropical diseases remain a major public health problem in Indonesia, particularly in regions with limited access to healthcare facilities, leading communities to rely on traditional medicine based on local wisdom. However, the integration of traditional and modern treatment knowledge in intelligent recommendation systems remains limited. This study aimed to develop a tropical disease treatment recommendation system by integrating Bayesian Network (BN) and Association Rule Mining (ARM). Traditional and modern treatment knowledge were collected from scientific literature and expert interviews, validated by medical practitioners and traditional medicine experts, and incorporated into the system. A quantitative and experimental approach was conducted using a dataset of 150 tropical disease cases comprising dengue fever (42 cases), malaria (35), leptospirosis (28), tuberculosis (30), and leprosy (15). The dataset included 47 symptom attributes, 34 traditional treatment attributes, and 12 modern treatment attributes. Bayesian Network was used to model probabilistic relationships among symptoms, diagnoses, and treatments, while the Apriori algorithm in ARM was applied with minimum support and confidence thresholds of 0.3 and 0.7, respectively. Experimental evaluation on 30 testing cases showed that the integrated BN-ARM model achieved 86.7% accuracy and an F1-score of 86.0%, outperforming standalone BN (82.0% accuracy; F1-score 82.5%) and ARM (79.0% accuracy; F1-score 78.8%). The system generated accurate and contextually relevant treatment recommendations by combining local wisdom and modern medical knowledge.
Rice Leaf Disease Classification Based on ResNet50 and MobileNetV3 Feature Extraction Using Random Forest Gede Yogi Pratama; Rahayun Amrullah Husaini; Muhammad Haris Nasri; Rifqi Hammad
Media Jurnal Informatika Vol 17 No 2 (2025): Media Jurnal Informatika
Publisher : Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.5939

Abstract

Diseases in rice plants are one of the main factors contributing to decreased agricultural productivity. Early and accurate disease identification is crucial to support effective decision-making in plant disease management. This study aims to compare the performance of deep learning models based on Convolutional Neural Networks (CNN), namely ResNet50 and MobileNetV3, as well as their integration with the Random Forest (RF) algorithm for rice leaf disease classification. The dataset used consists of rice leaf images categorized into several disease classes. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics with a macro-average approach. The results show that the standalone ResNet50 and MobileNetV3 models achieved accuracies of 62.5% and 65.7%, respectively, with macro F1-scores below 0.65, indicating moderate classification performance. However, combining CNN models with Random Forest significantly improved classification performance. The ResNet50 + RF model achieved an accuracy of 99.6%, while the MobileNetV3 + RF model attained the highest accuracy of 99.8%, along with equally high macro-averaged precision, recall, and F1-score values. These findings demonstrate that integrating CNN-extracted features with the Random Forest algorithm enhances the model’s ability to distinguish disease classes more accurately and consistently. Therefore, the hybrid CNN–Random Forest approach shows strong potential as an effective solution for image-based rice plant disease detection systems.
Peningkatan Kompetensi Digital Siswa melalui Pelatihan Pengembangan Aplikasi Web dalam Mendukung Kualitas Sumber Daya Manusia Mohammad Najib Roodhi; Rahayun Amrullah Husaini; Gede Yogi Pratama; Rifqi Hammad; I Nyoman Switrayana; Muhammad Haris Nasri; Gilang Primajati
Rengganis Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2026): Mei 2026
Publisher : Pendidikan Matematika, FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/rengganis.v6i1.1102

Abstract

The rapid development of digital technology demands an increase in the quality of human resources (HR) that are adaptive to change, especially in the field of information technology. One of the competencies needed is the ability to develop web-based applications, which are increasingly relevant to industry needs. This community service activity aims to improve students' digital competencies and reduce the dynamic skills gap through web application development training. The partners in this activity were grade X students of SMKN 2 Mataram with a total of more than 20 participants. The training method used was a learning-by-doing approach, which included material delivery, demonstrations, direct practice, and evaluation. The results of the activity showed an increase in the average score of participants from 65 in the pre-test to 85 in the post-test, indicating a significant increase in participant understanding. In addition, participants were also able to develop simple web applications and demonstrated improved problem-solving skills and self-confidence. This activity contributes to improving digital competencies and strengthening the quality of human resources who are better prepared to face technological developments in the digital era.
Selection of Outstanding Students Using AHP and Profile Matching Muhammad Haris Nasri; Rifqi Hammad; Pahrul Irfan
Paradigma - Jurnal Komputer dan Informatika Vol. 26 No. 1 (2024): March 2024 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v26i1.3189

Abstract

The determination of outstanding students is the giving of awards to those who excel in academic and non-academic fields, aimed at motivating increased achievement. However, this process is often hampered by various criteria that must be considered, such as English language skills, work results, awards, and so on. The solution offered to overcome this problem is the development of a decision support system for selecting outstanding students using the AHP and Profile Matching methods. So, the aim of this research is to develop a decision support system for selecting outstanding students using a combination of the AHP and Profile matching methods, where later the system developed can assist decision makers in determining outstanding students. The results obtained from this research are a decision support system that uses 8 criteria and 26 alternative sample data which shows that "Mahasiswa F" is an outstanding student with a score of 4.09. The results of manual calculations with the system show similarities, which shows that the system developed is in accordance with expectations.
Implementasi Kurikulum Merdeka Melalui Media Pembelajaran Berbasis Augmented Reality Matapelajaran Ilmu Pengetahuan Alam dan Sosial Rifqi Hammad; Apriani; Abdul Muhid
Jurnal Pemberdayaan Masyarakat Vol 10 No 1 (2025): Mei
Publisher : Direktorat Penelitian dan Pengabdian kepada Masyarakat (DPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/jpm.v10i1.10730

Abstract

SLBN 2 Mataram is a special needs school with elementary, junior high and high school education levels. Currently the problem faced by SLBN 2 Mataram is the limited learning media for children with disabilities, the learning media used is still less attractive to students, the SLBN 2 Mataram teacher has never developed Augmented Reality-based learning media, the SLBN 2 Mataram school website has not seen the content and content.  Whereas making the content and content of the school website is very important for the existence of the organization's existence especially in the education environment. The solution offered from these problems is training in making Augmented Reality-based teaching media and training in making website content and content. There are several stages of activities carried out related to the solutions offered, starting from the stages of socialization, training, application of technology, mentoring and evaluation, and program sustainability. From the results of training activities obtained that there are 95.8% of teachers who can make Augmented Reality-based learning media and there are 90% of teachers who are able to manage and content the school website.
Co-Authors Abdul Muhid Ade irmayanti Ahmad Ahmad Ahmad Ahmad Zuli Amrullah Ahmad Zuli Amrullah Andi Sofyan Anas Apriani Apriani Dwinda Etika Profesi Eka Wahyu Sholeha Fatimatuzzahra Fatimatuzzahra Gede Yogi Pratama Gede Yogi Pratama Gilang Primajati Gilang Primajati Habib Ratu Perwira Negara Hairani Hairani Hany Pebrianti Hasan, Nur Fitrianingsih Hasbullah Hasbullah Husain Husain Husain I Nyoman Switrayana I Nyoman Switrayana Kaharuddin Khairan marzuki Kurniadin Abd Latif Kusrini Lalu Erwin Jannata Arhaditya Listra Frigia Missianes Horhoruw M Thoric Panca Mukti M. Adam Hawary Saputra M. Aswin Syarif M. Rasyid Ridho Mohammad Najib Roodhi Muhammad Arfa Muhammad Azwar Muhammad Haris Nasri Muhammad Haris Nasri Muhammad Innuddin MUHAMMAD TAJUDDIN Muhammad Zulfikri Muhammad Zulfikri Musthofa Galih Pradana Nanang Samudra Naufal A. Furqan Nurcahyo, Azriel Christian Pahrul Irfan Pahrul Irfan Pahrul Irfan Pahrul Irfan Pahrul Irfan Rahayun Amrullah Husaini Ria Rismayati Rini Adriani Auliana Rukmin Ulfa Ayu Lestari Suriyati ., Suriyati Syahrir, Moch. Tomi Tri Sujaka Tomi Tri Sujaka Triwijoyo, Bambang Krismono Veny Cahya Hardita Veny Cahya Hardita Yunita, Selviana Yusril Mahenra Mahenra