Article Per Year (5 Year)
p-Index From 2020 - 2025
5.811
P-Index
This Author published in this journals
All Journal Jurnal Informatika JURNAL SISTEM INFORMASI BISNIS TELKOMNIKA (Telecommunication Computing Electronics and Control) JUITA : Jurnal Informatika Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Jurnal Teknologi dan Sistem Komputer Indonesian Journal of Information System JITK (Jurnal Ilmu Pengetahuan dan Komputer) JMM (Jurnal Masyarakat Mandiri) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan ILKOM Jurnal Ilmiah MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal GERVASI: Jurnal Pengabdian kepada Masyarakat INSIST (International Series on Interdisciplinary Research) Jurnal Informatika Global Jurnal Teknologi Terpadu bit-Tech Jurnal Abdimas Mandiri Indonesian Journal of Electrical Engineering and Computer Science Reswara: Jurnal Pengabdian Kepada Masyarakat Teknosains : Jurnal Sains,Teknologi dan Informatika Journal of Computer Networks, Architecture and High Performance Computing Idealis : Indonesia Journal Information System Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Indonesian Community Journal Jurnal Teknologi Sistem Informasi Jurnal INFOTEL SISFOTENIKA
Rendra Gustriansyah
Universitas Indo Global Mandiri, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 56 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 56 Documents
Search

 2   3   4   5   6 
Improving Information Security with Machine Learning Ahmad Sanmorino; Rendra Gustriansyah; Shinta Puspasari; Juhaini Alie
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3317

Abstract

The study Improving Information Security with Machine Learning explores the fusion of machine learning methodologies within information security, aiming to fortify conventional protocols against evolving cyber threats. By conducting a comprehensive literature review and empirical analysis, this scholarly endeavor highlights the efficacy of machine learning in anomaly detection, threat identification, and predictive analytics within security frameworks. Through practical demonstrations, such as z-score-based anomaly detection in network traffic data and NLP-based email security systems, the study illustrates the practical applications of machine learning techniques. Additionally, it delves into the mathematical underpinnings of predictive analytics and the architecture of neural networks for malware detection. However, while showcasing the transformative potential of machine learning, the study also confronts significant challenges. Ethical, legal, and privacy considerations emerge prominently, emphasizing the need for regulations addressing algorithmic biases, ethical dilemmas, and data protection. Moreover, the study emphasizes the practical challenges of scalability, interpretability, continual adaptation to evolving threats, and the harmonious interaction between human expertise and machine intelligence. By offering practical recommendations and future research directions, this scholarly exploration aims to empower researchers, practitioners, and policymakers in navigating the complex intersection of machine learning and information security, thereby fostering innovation and comprehension in this evolving domain.
Toddlers’ Nutritional Status Prediction Using the Multinomial Logistics Regression Method Rendra Gustriansyah; Nazori Suhandi; Shinta Puspasari; Ahmad Sanmorino; Dewi Sartika
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3372

Abstract

Malnutrition is one of the foremost health problems experienced by children under five in many countries, especially in low and middle-income countries. Meanwhile, the target of Sustainable Development Goals (SDGs) 2.2 is that all forms of malnutrition must end by 2025. Therefore, this study aims to predict the toddlers’ nutritional status (malnutrition, undernutrition, overnutrition, and normal nutrition) based on age, body mass index (BMI), weight, and length using the Multinomial Logistic Regression (MLR) classification method. The dataset consists of two hundred toddlers obtained from the Kaggle site. Following pre-processing, the dataset is divided, with 80 percent of the data for training and the remaining 20 percent for testing. The model was trained using 10-fold cross-validation (CV). In Addition, the MLR model performance was evaluated using the confusion matrix (CM), the area under the curve (AUC), and the Kappa coefficient (KC). The evaluation results using CM show that the accuracy, sensitivity, and specificity values are 0.9412, 0.9375, and 0.9790, respectively. AUC and KC also show excellent results. It indicates that the MLR method is an esteemed and recommended method for predicting the nutritional status of toddlers. Therefore, this research can contribute to providing early information so that the Government can immediately determine the necessary treatment.
Customer Segmentation For Digital Marketing Based on Shopping Patterns Juhaini Alie; Rendra Gustriansyah
Jurnal Aplikasi Bisnis dan Manajemen (JABM) Vol. 10 No. 1 (2024): JABM, Vol. 10 No. 1, Januari 2024
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.10.1.209

Abstract

Customer segmentation is the customer grouping based on similar shopping behavior or patterns. Inappropriate customer segmentation can have negative impacts, such as lost marketing opportunities, resource inefficiencies, loss of potential customers, and decreased performance, and business profits, especially in customer satisfaction. Therefore, this study aims to develop a customer segmentation model for digital marketing. This model is based on customer shopping patterns using the Recency-Frequency-Monetary (RFM) model and the Partitioning Around Medoids (PAM) method. The research data is historical customer purchase data consisting of 18,535 transactions and 541,909 transaction details from 4,339 customers for 3,665 product items over two years. The research variables focus on the model used: recency, frequency, and monetary. The five customer segments generating from this study are main, potential, general, minimum, and prospective customer. The internal validation results show that the minimum C-Index value is 0.1429 (close to zero), and the maximum Calinski-Harabasz Index value is 512.9553. It shows that the quality of customer segmentation results is good. In other words, the model can identify correlations between customer segments and shopping patterns and preferences. In this way, marketers can optimize services, adjust strategies, and offer the right products for each customer segment. Further research can be directed at product segmentation. Keywords: partitioning around medoids, digital marketing, shopping pattern, recency-frequency-monetary, customer segmentation
Pendampingan Pemanfaatan Mikroskop Digital dalam Konservasi Koleksi Kain Songket Museum Sultan Mahmud Badaruddin II Shinta Puspasari; Rendra Gustriansyah; Ahmad Sanmorino; Ditho Hersilava; Ade Fathurahman
I-Com: Indonesian Community Journal Vol 4 No 2 (2024): I-Com: Indonesian Community Journal (Juni 2024)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/icom.v4i2.4234

Abstract

Conservation of Palembang Songket woven cloth is carried out at SMBII Museum. The thread fibers woven into Songket cloth are small in size and require a microscope to see the thread fibers clearly before determining the appropriate conservation mechanism for fabric damage. Community service activities are carried out by assisting in the use of digital microscopes in the conservation of Songket cloth collections. A digital microscope is used to magnify the appearance of the gold thread fibers of the Songket cloth, whether there is damage or not. The activity began with setting up a digital microscope device to be used in the study of Songket cloth conservation and continued with assistance in using the microscope by participants. The results of the assistance show that users can easily use digital microscope devices to display Songket fabric fibers that are damaged and require conservation. Hopefully, this community service will make it easier for the SMBII museum to carry out conservation and learning tasks at the museum and have an impact on ensuring the resilience of the Palembang Songket cloth cultural heritage in the digital era.
Pelatihan Penggunaan Aplikasi Reservasi Kamar Hotel Untuk Meningkatkan Layanan Konsumen Nazori Suhandi; Rendra Gustriansyah
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol 7, No 2 (2024): April 2024
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v7i2.2938

Abstract

The travel and tourism sectors are closely related to the hospitality sector. The success of a hotel in this digital era is strongly supported by customer service that utilizes information technology-based applications. However, using these applications effectively requires proper training and understanding. Therefore, this service activity aims to train Swarna Dwipa hotel staff in operating a web-based hotel room reservation application. It is one way for hotel staff to provide optimal service and assist in driving business success in the hospitality sector. Many studies show that operating hotel room reservation applications can increase customer satisfaction and efficiency in the hotel business. However, proper and systematic training is necessary to maintain competitiveness. The stages of this activity include observation, interviews, sharing knowledge, training in application use, and evaluation. The simulation results show that participants can use the reservation application in a structured and systematic manner with a significant level of user acceptance of applications. Keywords: application; hotel; training; reservation
Comparison of naive Bayes and decision tree algorithms to assess the performance of Palembang City fire and Disaster management employees Dewi Sartika; Rendra Gustriansyah
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 11 No 1 (2024): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK-Sekolah Tinggi Teknologi Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v11i1.843

Abstract

The employee performance assessment at the Palembang City Fire and Disaster Management Service (DPKPB) is applied to other than the employee performance assessment implementation team based on the Decree of the Head of the Palembang City DPKPB Number 146 of 2021 concerning the employee performance assessment implementation team and awards for exemplary employees. Subjective assessments are avoided to obtain assessment results that are by the achievements of each employee. The application of data mining can be an alternative to avoid subjectivity in performance assessment. In this research, a comparison of the Naive Bayes and Decision Tree algorithms was carried out to assess the performance of Palembang City DPMPB employees. The results of further research will be used as an alternative solution in conducting performance assessments that are more objective than previous assessments. Both algorithms were evaluated for model performance using the Confusion Matrix. Based on the results of the evaluation carried out, it was stated that the Decision Tree algorithm had better accuracy, namely 91.74% compared to Naïve Bayes which had an accuracy of 88.99% with a test size of 0.4
ANALISIS USER EXPERIENCE UNTUK MENGOPTIMASI APLIKASI PRODESKEL DI KOTA PALEMBANG Sari, Nursella; Gustriansyah, Rendra; Mair, Zaid Romegar
IDEALIS : InDonEsiA journaL Information System Vol 7 No 1 (2024): Jurnal IDEALIS Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v7i1.3126

Abstract

Prodeskel is a site-based application and used as an information center for data related to Villages and Subdistricts. All villages and sub-districts in Indonesia use Prodeskel, so the large number of users of Prodeskel causes frequent errors in application which give rise to complaints from users, likewise the city of Palembang, to overcome this problem it’s necessary to improve the quality of Prodeskel through user experience. Therefore, this study analyzes user experience on Prodeskel using three methods, namely, SUS, UEQ and Heart Metrics. SUS method can be used easily and helps in evaluating a system,UEQ provides analysis tools that are accurate and easy to interpret, and Heart Metrics can easily identify goals and success of the application. Dapil 4-6 of Palembang City became the research location because this area was easy to cover, by distributing questionnaire forms via WhatsApp to users, with a total of 45 respondents. SUS, the calculation results obtained a total score of 65. UEQ obtained an average value of >0.8, which means variables had positive values. Meanwhile, Heart Metrics, it was found that there were two variables that had a high level of usefulness, namely engagement and retention, while the other three variables had a very high level of usefulness. Based on the analysis results, obstacles received by users in using this application are the level of active use and ease of application. With this research, it’is hoped that in quality of the application will be improved so that there will be no complaints from users.
KLASTERISASI PIXEL CITRA KOLEKSI FOTO MUSEUM MONPERA DENGAN METODE K-MEANS PADA APLIKASI AUGMENTED REALITY Haversyalapa, Ditho; Puspasari, Shinta; Gustriansyah, Rendra
IDEALIS : InDonEsiA journaL Information System Vol 7 No 2 (2024): Jurnal IDEALIS Juli 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v7i2.3175

Abstract

Museum Monpera Palembang adalah sebuah museum yang memiliki koleksi foto-foto pahlawan nasional Indonesia. Koleksi foto tersebut memiliki nilai historis dan makna yang mendalam bagi masyarakat Indonesia, tetapi beberapa di antaranya sudah terlihat samar dan kabur sehingga informasi yang tergambar menjadi tidak jelas. Penelitian ini bertujuan untuk menerapkan metode klasterisasi pixel yang digabungkan dengan metode K-Means pada aplikasi Augmented Reality untuk melakukan pengujian kualitas citra pada koleksi foto pahlawan museum Monpera. Penelitian ini menggunakan algoritma K-Means yang merupakan salah satu algoritma partitional yang didasarkan pada penentuan jumlah awal kelompok dengan mendefinisikan nilai centroid awalnya. Penelitian ini juga menggunakan teknologi Augmented Reality berbasis Android untuk memberikan pengalaman interaktif kepada pengunjung museum. Hasil pengujian citra menggunakan metode K-Means menunjukkan data evaluasi yang melibatkan Silhouette Score, Calinski-Harabasz, dan Dunn Index. Hasil pengujian ini menunjukkan bahwa metode K-Means belum mampu meningkatkan kualitas citra hasil klasterisasi pixel, tetapi penelitian ini berhasil mengembangkan aplikasi AR dan memberikan kontribusi penting dalam memahami dan mengatasi tantangan dalam mempertahankan integritas visual dari koleksi foto pahlawan nasional Indonesia melalui pengembangan teknik pengolahan citra yang lebih efektif dan inovatif menggunakan metode Clustering pixel dan K-Means dalam konteks Augmented Reality.
Klasifikasi Penyakit Daun Pisang menggunakan Convolutional Neural Network (CNN) Pratama, M Duta; Gustriansyah, Rendra; Purnamasari, Evi
Jurnal Teknologi Terpadu Vol 10 No 1 (2024): Juli, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i1.1167

Abstract

Bananas are a fruit with promising economic value in Indonesia. They are an essential commodity for farmers, but diseases affecting banana plants can harm their livelihoods. Banana diseases initially attack the leaves, and in the early stages, they are difficult to differentiate with the naked eye due to farmers’ limited knowledge of pathogens. This research utilized the Convolutional Neural Network (CNN) method with transfer learning assistance using Google Colab to facilitate the classification of banana leaf diseases. The trained model experienced overfitting, so regularization was applied using dropout. The best model achieved an accuracy of 92%, precision of 92%, sensitivity of 91%, and an F1-score of 91% at a 70:20:10 ratio on epoch 80, as evaluated and validated using a confusion matrix. This study produced a reliable model for classifying banana leaf disease.
Sosialisasi Aplikasi Augmented Reality MONPERA untuk Pengenalan Pahlawan Nasional dr. AK.Gani Puspasari, Shinta; Haversyalapa, Ditho; Gustriansyah, Rendra; Sanmorino, Ahmad
Jurnal Abdimas Mandiri Vol. 8 No. 2
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jam.v8i2.4088

Abstract

Museum merupakan lembaga yang bertugas menyimpan koleksi benda bernilai sejarah untuk tujuan edukasi maupun rekreasi. MONPERA adalah museum yang memiliki koleksi foto pahlawan terutama berjasa pada perang lima hari lima malamdi Palembang. Koleksi foto disajikan secara tradisional tanpa keterangan yang memberikan informasi bagi pengunjung museum sehingga memerlukan media alternatif untuk mendukung edukasi sejarah pahlawan pada koleksi foto MONPERA. Salah satu pahlawan nasional sekaligus pejuang perang lima hari lima malam di Palembang adalah dr.AK.Gani. Beliau juga memiliki museum yang menyimpan koleksi foto dan benda bernilai sejarah lainnya di Museum dr.AK.Gani. Pengembangan media berbasis teknologi Augmented Reality (AR) foto pahlawan koleksi MONPERA juga dapat dimanfaatkan untuk memperkenalkan sejarah perjuangan dan koleksi foto Musuem dr.AK.Gani. Tujuan kegiatan PkM sosialisasi aplikasi AR foto pahlawan dr.AK.Gani dan koleksi foto lainnya adalah untuk mengenalkan cara pemanfaatan aplikasi yang diharapkan efektif meningkatkan motovasi dan pengetahuan mahasiswa dan pelajar sebagai mayoritas pengunjung museum. Hasil evaluasi kegiatan menunjukkan bahwa aplikasi AR bermanfaat untuk pembelajaran sejarah pahlawan dan memotivasi pengguna untuk belajar sejarah lewat koleksi foto koleksi Museum MONPERA khususnya tentang dr.AK.Gani. Aplikasi AR tersebut diharapkan dapat diperluas dengan penambahan fitur bukan hanya terbatas koleksi foto pahlawan tetapi koleksi benda lainnya di museum sehingga memberikan pengalaman lebih menarik bagi pengunjung museum MONPERA dan dr.AK. Gani serta berdampak pada peningkatan jumlah pengunjung museum.
Co-Authors Abel Destria Ade Fathurahman Adhe Suryani Agung Prakesakwa Ahmad Sanmorino Ahmad Sanmorino Aminuyati Andri Agus Agus S Arief Ramadhan Cahyani, Septa Dana Indra Sensuse Darius Antoni Destria, Abel Dewi Sartika DEWI SARTIKA Dhamayanti Dhamayanti Dhamayanti, Dhamayanti Ditho Hersilava Dwi Asa Verano Ermatita - Febrianty Fery Antony Fery Antony Filian Falanda Hartini Hartini Hartini Hartini Hastha Sunardi Haversyalapa, Ditho Isabella, Isabella Juhaini Alie M. Ricky Hikmawan Marshanda Amalia Megat Norulazmi Megat Mohamed Noor Mitha Sofiana Muhammad Farhan Nazori Suhandi Nazori Suhandi Nazori Suhandi Nining Ariati Pratama, M Duta Purbasari, Nadira Putri Purnamasari, Evi Reza Iman Pribadi Rudi Heriansyah Ryan Ramanda Putra Sari, Nursella Sartika, Dewi Shinta Puspasari Shinta Puspasari Shinta Puspasari Suryati Suryati Suryati Suryati Terttiaavini, Terttiaavini Verano, Dwi Asa Via Kris Wilza Nadia Wiyanto, Ari Zulkifli Zulkifli