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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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Model Extreme Gradient Boosting Berbasis Term Frequency (TFXGBoost) Untuk Klasifikasi Laporan Pengaduan Masyarakat Vina Ayumi; Desi Ramayanti; Handrie Noprisson; Yuwan Jumaryadi; Umniy Salamah
JSAI (Journal Scientific and Applied Informatics) Vol 6 No 1 (2023): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v6i1.6089

Abstract

Various algorithms and machine learning techniques are being applied to improve the efficiency and effectiveness of the process of automatically classifying complaint reports from the public in Indonesia. One machine learning algorithm that has recently gained benchmarks in the state of the art of various problems in machine learning is eXtreme Gradient Boosting (XGBoost). This study aims to develop an extreme gradient boosting model based on term frequency (TFXGBoost) to predict whether a text is classified as a complaint or not a complaint based on the data studied. Based on the experimental results, TFXGBoost achieved 92.79% accuracy with eta / learning rate hyperparameters of 0.5, gamma of 0, and max_depth of 3 and the computation time required to adjust the hyperparameters was 13870.012468 seconds.
Pengaruh Tuning Parameter dan Cross Validation Pada Klasifikasi Teks Komplain Bahasa Indonesia Menggunakan Algoritma Support Vector Machine Vina Ayumi; Desi Ramayanti; Handrie Noprisson; Anita Ratnasari; Umniy Salamah
JSAI (Journal Scientific and Applied Informatics) Vol 6 No 3 (2023): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v6i3.6117

Abstract

Text classification aims to group text data, for example, to find some information from a large social media text dataset so that it can be used by the data owner. Manual text classification is time-consuming and difficult, so some researchers try to research text classification automatically. This study attempts to classify Indonesian text datasets using the SVM algorithm. The research was conducted in two stages, namely the first experiment without cross validation parameters and parameter tuning, then the second experiment was carried out with cross validation parameters and parameter tuning. Experiments without cross validation parameters and parameter tuning for support vector machines (SVM) obtained 89.47% accuracy with precision and recall values of 0.90 and 0.89 respectively. The second experiment used cross validation with k-5 and k-10 and tuning parameters with C constant and gamma values. Cross validation results with k-10 obtained the best accuracy with a value of 96.48% with a computation time of 40.118 seconds. Next, kernel functions in tuning parameters namely sigmoid, linear and radial basis functions are analyzed and it is found that sigmoid kernel functions achieve the best accuracy and computational time.
Evaluasi Usability pada Portal Basis Data Tanaman Obat Indonesia Menggunakan Metode System Usability Scale (SUS) Wachyu Hari Haji; Anita Ratnasari; Vina Ayumi; Handrie Noprisson; Nur Ani
JSAI (Journal Scientific and Applied Informatics) Vol 6 No 3 (2023): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v6i3.6263

Abstract

Previous research discussed valuable recommendations for the development of an Indonesian medicinal plant database portal. However, previous research has not discussed usability evaluation on the Indonesian medicinal plant database portal. One usability evaluation technique that is quite popular is the system usability scale (SUS). This study aims to analyze the portal database of medicinal plants using the usability scale (SUS) system to find out the next portal improvement. The SUS method allows researchers to collect data from users through surveys and calculate usability scores, providing recommendations for improving the design and functionality of web-based systems. From the experimental results in the form of calculation results using SUS measurement, it is known that the implementation of the medicinal plant database portal received an assessment of 72.14. This value if interpreted using the measurement level of the final value of SUS can be said that the implementation of the medicinal plant database portal can be accepted (acceptable) with a good category (good).
MODEL OF INDONESIAN CYBERBULLYING TEXT DETECTION USING MODIFIED LONG SHORT-TERM MEMORY Mariana Purba; Paisal Paisal; Cahyo Pambudi Darmo; Handrie Noprisson; Vina Ayumi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 1 (2024): JITK Issue August 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i1.5239

Abstract

Cyberbullying, in its essence, refers to the deliberate act of exploiting technological tools to inflict harm upon others. Typically, this offensive conduct is perpetuated repeatedly, as the perpetrator takes solace in concealing their true identity, thereby avoiding direct exposure to the victim's reactions. It is worth noting that the actions of the cyberbully and the responses of the individual being cyberbullied share an undeniable interconnection. The main objective of this study was to identify and analyze Instagram comments that contain bullying words using a model of WLSTML2 which is an optimization of a long short-term memory network with word-embedding and L2 regularization. This experiment using dataset with negative labels as many as 400 data and positive as many as 400 data. In this study, a comparison of 70% training data and 30% testing data was used. Based on experimental results, the WLSTMDR model obtained 100% accuracy at the training stage and 80% accuracy at the testing stage. The WLSTML2 model received an accuracy of 99.25% at the training stage and an accuracy of 83% at the testing stage. The WLSTML1 model obtained an accuracy of 97.01% at the training stage and an accuracy of 80% at the testing stage. Based on the experimental results, the WLSTML2 model gets the best accuracy at the training and testing stages. At the testing stage of 132 data, it was found that the positive label data predicted to be correct was 56 data and the negative label data that was predicted to be correct was 53 data.
Implementasi Metodologi Agile Software Development pada Proyek Perangkat Lunak handrie noprisson
Jurnal Sistem Informasi dan E-Bisnis Vol 5 No 2 (2023): Juli
Publisher : LPPMPP Yayasan Sejahtera Bersama Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54650/jusibi.v5i2.521

Abstract

This research is a systematic literature review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) as a method to gather literature on agile software development methodology from Google Scholar. The result of this study is a summary of 11 articles related to Agile software development. The recommendation of this study is the use of the GLUX framework. GLUX framework integrates Lean UX into Scrum to improve the sustainability of the rapid software development process. It aims to promote a user-centric mindset and collaborative UX activities during the development process using gamification techniques. GLUX is about self-reliant teams, creating a motivating environment, and fostering teamwork.
Metode Image Processing dan Deep Learning Untuk Pengembangan Automatic Number-Plate Recognition (ANPR) di Indonesia Handrie Noprisson
JUKOMIKA (Jurnal Ilmu Komputer dan Informatika) Vol. 7 No. 1 (2024): Juni 2024
Publisher : LPPMPP Yayasan Sejahtera Bersama Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54650/jukomika.v7i1.548

Abstract

Penelitian ini bertujuan untuk menganalisis informasi tentang analisis sentimen tentang terkait sentimen masyarakat pada lebih khusus pengguna platform media sosial tentang sentimen negatif atau positif terhadap pemilihan presiden di Indonesia dan menghasilkan ide-ide baru untuk penelitian model analisis sentiment selanjutnya. Metode systematic literature review (SLR) digunakan untuk meninjau dan mensintesis data penelitian. Penelitian ini mengusulkan model analisis sentimen untuk teks bahasa Indonesia dengan menggunakan metode long short-term memory network (LSTM) dengan metode praproses yaitu transformation, tokenization, stop word removal, lemmatization, dan pos tagging.
Palembang songket fabric motif image detection with data augmentation based on ResNet using dropout Ermatita, Ermatita; Noprisson, Handrie; Abdiansah, Abdiansah
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6883

Abstract

A good way to spread knowledge about Palembang songket woven cloth patterns is to use information technology, especially artificial intelligence technology. This study's main goal is to develop a ResNet model with dropout regularization methods and find out how dropout regularization affects the ResNet model for detecting Palembang songket fabric motif with more data. Data was collected in places like tujuh saudara songket, Zainal songket, songket PaSH, AMS songket, and batik, Ernawati songket, Nabilah collections, Ilham songket, and Marissa songket. We used eight class of data for this research. A dataset of 7,680 data for training, 960 data for validation, and 960 data for testing is a dataset that has been prepared to be implemented in experiments. In the final results, the experimental results for DResNet demonstrated that accuracy at the training stage was 92.16%, accuracy at the validation stage was 78.60%, and accuracy at the submission stage was 80.3%. The experimental results also show that dropouts are able to increase the accuracy of the ResNet model by adding +1.10% accuracy in the training process, adding +1.80% accuracy in the validation process, and adding +0.40% accuracy in the testing process.
Identifikasi Penyakit Kelainan Tulang Belakang Berdasarkan Pengolahan Dataset Spine X-ray Mengunakan Algoritma LBP dan CNN Noprisson, Handrie
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 2 (2024): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i2.6422

Abstract

This research will use deep learning in conducting spinal x-ray image analysis but computational time problems are a problem of this study. Computations on deep learning across multiple nodes can increase training time and longer computation time compared to machine learning models. Based on experimental results, the best spine x-ray image classification results when using the CNN model with accuracy at the training stage, evaluation stage and test stage were 69.00%, 83.33% and 81.16% respectively. CNN models optimized with LBP get the lowest accuracy, with results at the training stage of 62.64%, validation stage of 75.00% and testing stage of 65.22%. LBP feature extraction turns out to have several drawbacks when combined with the CNN model, one major drawback is its inability to process global spatial information while retaining local texture information which causes LBP to be unable to capture the entire structure or context of the image, focusing only on local patterns so that many features of the image are lost. Another issue is the sensitivity of CNNs to image data, which can affect classification accuracy.
Evaluasi Aplikasi Pemesanan Tiket Menggunakan Metode System Usability Scale (SUS) dan Model D&M IS Success Purba, Mariana; Dianing Asri, Sri; Noprisson, Handrie; Utami, Marissa; Iryani, Lemi
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 1 (2024): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i1.6444

Abstract

Software product development not only focuses on features but also usability aspects. User experience is very important in the evaluation of reusability to understand the user's interaction with the product or system. Reusability factors include user satisfaction, efficiency, and effectiveness to achieve specific goals. The main purpose of this study is to evaluate the usability aspect of online ticket booking applications. This evaluation process is important to identify development and improvements to user views and application usage satisfaction. In this study, the object studied was an online travel booking application in Indonesia. The research instrument uses a quantitative and qualitative mixed-method approach. For the quantitative approach, the System Usability Scale (SUS) is used and as a basis for a qualitative approach, the D&M IS Success Model approach is used. Based on the evaluation results, there are several points that should be improved including the interface design should be simple, the reduction in the size of memory used by applications, features to communicate with customer service easily, data integration, and time notifications to complete payments.
Analysis of Travel Ticket Booking Application Services Based on Supporting Factors for Purchase Intention Purba, Mariana; Dianing Asri, Sri; Noprisson, Handrie; Utami, Marissa; Iryani, Lemi
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 1 (2024): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i1.6446

Abstract

Aplikasi pemesanan tiket perjalnan ini harus memiliki kualitas dari segi perspektif produk agar dapat meningkatkan purchase intention oleh pengguna. Purchase intention dari layanan aplikasi dapat dilihat dari beberapa faktor antara lain usabilitas (usability), harga (price), kemudahan penggunaan (ease of use), complementarity dan hiburan (entertainment). Penelitian ini akan mengusulkan model penelitian untuk identifikasi kualitas layanan aplikasi online travel booking berdasarkan perspektif produk untuk meningkatkan purchase intention berdasarkan analisis dataset yang dikumpulkan dari sampel responden. Dari hasil pengumpulan data, dari total 1267 kuesioner yang dikumpulkan hanya memperoleh 1029 kuesioner yang valid. Model diuji menggunakan skor tingkat signifikan two-tails sebesar 0,05 untuk pengujian hipotesis. Menurut analisis data, faktor complementary memiliki pengaruh terbesar purchase intention dengan nilai uji-t sebsar 6,771. Selain itu, faktor entertainment memiliki pengaruh terbesar kedua dengan t-nilai 5.334. Faktor usability memiliki pengaruh terhadap purchase intention terbesar ketiga nilai uji-t 4.620. Faktor ease of use memiliki pengaruh terbesar keempat dengan nilai uji-t 3.641.
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