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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics Jurnal Pseudocode JITK (Jurnal Ilmu Pengetahuan dan Komputer) International Journal of Computing Science and Applied Mathematics INTECOMS: Journal of Information Technology and Computer Science Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JSAI (Journal Scientific and Applied Informatics) Jurnal Ilmu Teknik dan Komputer RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Jurnal Sistem Informasi Dan E-Bisnis Jurnal Ilmu Komputer Dan Informatika Dedikasi Nusantara: Jurnal Pengabdian Masyarakat Pendidikan Dasar JPMTT (Jurnal Pengabdian Masyarakat Teknologi Terbarukan)
Noprisson, Handrie
Universitas Dian Nusantara
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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Analisis Faktor Kepercayaan dan Kepuasan Pengguna Website Marketplace: Studi Empiris pada E-Commerce Lazada Hari Haji, Wachyu; Ratnasari, Anita; Ayumi, Vina; Noprisson, Handrie; Ani, Nur
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7476

Abstract

This study aims to identify the factors influencing trust and user satisfaction in online marketplaces by applying the DeLone & McLean information system success model. Data were collected through an online questionnaire distributed to Lazada marketplace buyers in Indonesia. The empirical results indicate that trust is a key predictor in determining the quality of sellers and their ability to provide the best services. Statistically, the first hypothesis (H1) shows a significant influence of website reputation on user trust (**T-Stat = 8.50; Sig = *). The second hypothesis (H2), regarding the influence of perceived website size on trust, is not significant (T-Stat = 1.42; Sig = NS). The third hypothesis (H3) demonstrates a significant positive relationship between trust and user satisfaction with the website (**T-Stat = 5.62; Sig = *). The fourth hypothesis (H4) confirms a highly significant positive relationship between trust and perceived website quality (**T-Stat = 14.59; Sig = *). This study recommends that online marketplaces enhance the prestige of sellers and maintain customer trust, as these factors play a critical role in improving user satisfaction when shopping on online marketplaces.
Rancang Bangun Interkoneksi Jaringan Berbasis VPN Menggunakan Metode EOIP Tunnel Verian Nugroho, Dimas; Noprisson, Handrie
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7549

Abstract

This research aims to solve the problem of automatic data backup between the server at the Cyber ​​Data Center and the server at the XYZ Apartment using Ethernet over IP (EoIP) Tunnel technology on the MikroTik network. The main problem faced is that there is no direct path to connect the two servers, so the data synchronization and backup process must be done manually. Experimental research methods using the Network Development Life Cycle (NDLC) approach are used to analyze needs, design new networks, implement and evaluate the designed solutions. EoIP Tunnel implementation is carried out to create an exclusive and secure communication path, equipped with static route configuration and automatic robocopy-based scripts to support regular data backup. Connectivity testing shows optimal results with a stable transfer speed of 49 Mbps, without problems in sending files from the AST server to the QNAP server.
Model Platform Berbasis Mobile Untuk Manajemen Data Rekam Medis di Pos Pelayanan Terpadu Menggunakan Feature Modeling dan Unified Modeling Language Ardianto, Darmawan; Noprisson, Handrie
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7572

Abstract

As one of the Posyandu, Chica II also provides medical record data for the community. However, the management of this data often faces challenges, such as manual recording, unorganized data, and difficulty in accessing information quickly. This study aims to develop a mobile-based platform model for managing medical record data in Posyandu. The system development uses the waterfall methodology, which includes the stages of requirement analysis, design, implementation, and testing. The system is implemented using Java programming with MySQL as the database, developed through Android Studio using a native approach. The results of the study indicate that the developed system includes key features such as registration management, user management, health monitoring, mapping, reporting, and education. The system is also integrated with a previously developed web-based system, enabling comprehensive data management, including managing child data, immunizations, weighing records, and user management, designed to meet the operational needs of Posyandu.
Perancangan Prototipe Aplikasi Prediksi Kematian Akibat Gagal Jantung Menggunakan Metode Machine Learning Berdasarkan Data Heart Failure Clinical Records Jumardin, Jumardin; Noprisson, Handrie
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7574

Abstract

This research aims to develop a prototype of the Heart Failure Death Prediction Application using machine learning methods based on clinical data from the Heart Failure Clinical Records. The application utilizes clinical patient data, such as age, blood pressure, ejection fraction, creatinine levels, and other attributes, to build a predictive model for mortality risk. Several machines learning algorithms, including Random Forest, Logistic Regression, and K-Nearest Neighbors (KNN), were employed to model and analyze the data. The dataset used in this study consists of 299 clinical records with 13 attribute columns. The target attribute is Death Event, while other attributes, such as age, gender, medical history (anemia, diabetes, high blood pressure), and laboratory test results (creatinine, sodium, and ejection fraction), were used as predictors. The application is equipped with several main menus to support its functionality, such as the Dashboard, which provides a summary of statistical prediction information and related reports, and Blog/News, which offers heart health education. The Data Master menu allows for the management of supporting data, while the Diagnosis menu is used to perform predictions based on patient input data. The Diagnosis History menu stores previous prediction results, while the Patient Data menu facilitates the management of patient information.
Forest Fire Detection Using Transfer Learning Model with Contrast Enhancement and Data Augmentation Ayumi, Vina; Noprisson, Handrie; Ani, Nur
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 1 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i1.75692

Abstract

Forest damage due to fire is unique of the catastrophes that can disrupt and damage the existing ecosystem. There needs to be a quick response to fires because disaster management takes longer, and the impact of the damage will be more severe. To process images to detect fire in the forest, we need to build a suitable deep-learning model. This study proposed research on forest fire detection using an Xception and MobileNet model. Moreover, this research optimizes the accuracy of the model by applying Contrast-Limited-Adaptive-Histogram-Equalization (CLAHE) and data augmentation to tackle the problem of the forest fire image dataset. Based on the experiment, MobileNet with CLAHE obtained 99,66% accuracy in the test phase. In the same phase, MobileNet with CLAHE obtained a value F1-score of 1.00, a value of precision of 0.99, and a value of recall of 1.00. If compared to other model performances, MobileNet with CLAHE obtained the best result.
Model GHT-SVM for Traffic Sign Detection Using Support Vector Machine Algorithm Based On Gabor Filter and Top-Black Hat Transform Noprisson, Handrie; Ayumi, Vina; Dwika Putra, Erwin; Utami, Marissa; Ani, Nur
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 3 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i3.75778

Abstract

A factor that can hinder the detection and recognition of traffic signs is the variation in lighting in the image of traffic signs. This study aims to detect traffic symbols using Gabor Filter (GFT), Top Hat Transform (THT), and Black Hat Transform (BHT) methods on the Support Vector Machine (SVM) algorithm for traffic sign dataset images with data problems that tend to have dark backgrounds at night and bright backgrounds during the day. From the experimental results, GHT-SVM gets the highest accuracy compared to HSV-SVM, HSV-RF, HSV-KNN, and H2T-SVM models. Based on experimental results, H2T-SVM from HOG ⊕ ENT ⊕ BHT ⊕ SVM results get the best accuracy of 86.42%. The Gabor Filter (GFT) parameters used are the number of filters with a value of 16, ksize with a value of 30, sigma with a standard deviation value of 3.0, lambd with a sinusoidal factor value of 10.0, gamma with a spatial aspect ratio value of 0.5 and psi with a phase offset value of 0 while the Top Hat Transform (THT) and Black Hat Transform (BHT) methods use filterSize sizes with values (3, 3).
Transformasi Social Interaction, Trust, dan Norm Untuk Mendukung Pengembangan Knowledge Management System Noprisson, Handrie
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7905

Abstract

The success of a Knowledge Management System (KMS) is not solely determined by technological aspects but also by social factors such as social interaction, trust, and norm of reciprocity, which influence the process of explicit knowledge sharing. This study aims to analyze the role of these three factors in supporting KMS development in higher education institutions. This research employs a descriptive and exploratory approach, utilizing a survey method involving 420 student respondents from various universities in Indonesia. Data were collected through an online questionnaire and analyzed using SMART PLS (Partial Least Squares-Structural Equation Modeling). The analysis results indicate that all indicators have good validity (loading factor > 0.7) and meet the reliability criteria (Cronbach’s Alpha and Composite Reliability > 0.7). Hypothesis testing using the bootstrapping method shows that Social Interaction (P = 0.002) and Norm of Reciprocity (P = 0.003) significantly influence Explicit Knowledge Sharing, while Trust (P = 0.062) remains an acceptable contributing factor. These findings suggest that the successful implementation of KMS in higher education institutions must consider the social aspects that shape the academic environment. Enhancing social interaction, strengthening trust, and fostering a culture of knowledge sharing are essential factors in optimizing KMS utilization.
Analisis Faktor Identification, Shared Language, dan Shared Vision Untuk Penerapan Knowledge Management System Untuk Mahasiswa Perguruan Tinggi di Indonesia Noprisson, Handrie
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7906

Abstract

This study aims to analyze the factors influencing Knowledge Sharing in the implementation of the Knowledge Management System (KMS) among university students. The three main variables examined are identification, shared language, and shared vision. Data were collected through online surveys and questionnaire distribution to students from various universities in Indonesia. A total of 420 questionnaires were distributed, and after validation, 400 questionnaires were used for analysis. Data analysis was conducted using SmartPLS version 3.2.7 with the Structural Equation Modeling (SEM) approach. The study results indicate that shared language has a significant influence on knowledge sharing, while identification shows a near-significant effect. Conversely, shared vision does not have a significant impact on knowledge sharing. The validity and reliability values confirm that all variables strongly contribute to the research model. The research implications suggest that a common language understanding plays a crucial role in enhancing knowledge sharing within academic environments
Analisis Faktor Explicit Knowledge dan Tacit Knowledge Untuk Penerapan Human Capital Management System Noprisson, Handrie
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7908

Abstract

In the era of a knowledge-based economy, Human Capital Management System (HCMS) has become increasingly important, particularly in the context of higher education. This study aims to analyze the influence of tacit knowledge sharing and explicit knowledge sharing on the human capital of university students. A quantitative approach was used by collecting data from 430 students through an online survey, with 420 valid responses analyzed using the Structural Equation Modeling (SEM) method. The results indicate that tacit knowledge sharing has a more significant impact on Human Capital than explicit knowledge sharing, with a t-statistics value of 6.777 and a P-Value of 0.000, demonstrating a strong and significant relationship. Meanwhile, the relationship between explicit knowledge sharing and human capital showed a t-statistics value of 1.777 with a p-value of 0.076, which remains within the hypothesis acceptance threshold but is less dominant. The implications of this study suggest that universities should design HCMS strategies that focus more on strengthening tacit knowledge sharing, such as mentoring, group discussions, and experiential learning programs. Additionally, technology-based learning management systems remain essential for documenting and distributing explicit knowledge.
Pemodelan Jaringan Komputer Berbasis LAN dan WLAN di Perusahaan Ekspedisi Menggunakan Metodologi PPDIOO Brahmana, Zone Tryando Gemenio; Noprisson, Handrie
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8303

Abstract

Network models are the primary infrastructure supporting smooth operations, ranging from managing shipment data to inter-branch communication and real-time package tracking. With an optimally designed network, companies can maintain stable connections between devices and systems, accelerate information processing, and enhance responsiveness to customer needs. This study aims to develop and optimize the LAN (Local Area Network) and WLAN (Wireless Local Area Network) at PT APZ using the PPDIOO (Prepare, Plan, Design, Implement, Operate, Optimize) method adapted from Cisco’s approach. Considering the limitations in adding network devices, the study designs an efficient and reliable network using hardware such as the ASUS RT-AC68U router, Procurve Switch 1800-24g, Engenius EAP300 wireless devices, and Vascolink UTP (Unshielded Twisted Pair) CAT 6 cables. Network simulation and design were conducted using Cisco Packet Tracer version 8.2.2 on a system powered by an Intel Core i3-6006U processor with 8 GB of RAM (Random Access Memory) and Windows 10 Pro 64-bit operating system. Test results showed a significant improvement in network performance, with a download speed of 33.82 Mbps, upload speed of 33.38 Mbps, and a low ping response time of 7 ms, indicating a stable network operation.
Co-Authors Abd Rahman Abdiansah, Abdiansah Anita Ratnasari Ardianto, Darmawan Ayumi, Vina Bagus Priambodo Brahmana, Zone Tryando Gemenio Budiyarti Budiyarti Budiyarti, Budiyarti Cahyo Pambudi Darmo Desi Ramayanti Devi Fitrianah Dianing Asri, Sri Dwi Wanda Ramadhan Ermatita - Erzi Hidayat Eva Putri Nandayani Faizal, Fritzen Febrianto Pratama, Arif Hong Wei Ida Farida Ida Nurhaida Ida Nurhaida Iryani, Lemi Jumardin, Jumardin Jumaryadi, Yuwan Mariana Purba Novi Purnautari Handayani Nur Ani Nur Ani Purba, Mariana Putra, Erwin Dwika Rah Mah Wati Remmy A. M. Zen Salamah, Umniy Saputra W, Inyoman Septianita, Septianita Septitina Gulo, Fifiyani Simanungkalit, Simon Andika Sri Indah Darmawanti SRI RAHAYU Syamsiar, Syamsiar Verian Nugroho, Dimas Vina Ayumi Vina Ayumi Vincentius Krisna Aditya Wachyu Hari Haji Wachyu Hari Haji