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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Annual Research Seminar Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Paradigma JURNAL MEDIA INFORMATIKA BUDIDARMA PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Ilmiah Media Sisfo The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Bulletin of Computer Science Research Jurnal Informatika, Komputer dan Bisnis (JIKOBIS) Journal of Applied Business and Technology Jurnal Informatika dan Rekayasa Komputer Jurnal Manajemen Teknologi dan Sistem Informasi PROCEEDING OF INTERNATIONAL CONFERENCE ON BUSINESS MANAGEMENT AND ACCOUNTING Bulletin of Informatics and Data Science Scientific Journal of Informatics Jurnal Pengabdian Masyarakat Unama
Errissya Rasywir
Universitas Dinamika Bangsa
Aerospace Engineering Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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Perancangan Sistem Informasi Pengadaan Barang Berbasis Web (Studi Kasus : CV. Royal Transindo) Gilliani, Wenny; Errissya Rasywir; Lazuardi Yudha pradana
Jurnal Manajemen Teknologi Dan Sistem Informasi (JMS) Vol 4 No 1 (2024): JMS Vol 4 No 1 Maret 2024
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jms.2024.4.1.1679

Abstract

Royal Transindo is a company engaged in the procurement of goods related to employment needs. Currently the company still uses Microsoft Word and Microsoft Excel which are still commonly used. Every goods procurement activity is made by the administrator and managed by the owner, which is still less effective and requires a long time and there are delays in identifying data information such as selling prices, goods specifications and so on to customers. Therefore, based on existing problems, the author will design and create a goods procurement information system on CV. Royal Trasindo. This research was built using the PHP programming language and MySQL DBMS. Apart from that, we also apply the Agile Software Development method using the UML (Unified Modeling Language) method by creating various kinds of system modeling such as Use Case Diagrams, Activity Diagrams, Class Diagrams and Flowchart Diagrams. With this information system, it is hoped that it will make it easier for system users, both administrators and company owners, to reduce delays in providing data information such as selling prices, product specifications and so on to customers. Apart from that, this web-based system can reduce the risk of losing data that the company does not want and it is hoped that the system built can produce good computerized reports to make it easier to calculate profit/loss.
Perencanaan Arsitektur Sistem Informasi Menggunakan Togaf Adm Pada Kantor Desa Simpang Terusan Dengan Evaluasi Ea-Scorecard Rani Oktavia, Feby; Rasywir, Errissya; Aryani, Lies
Jurnal Manajemen Teknologi Dan Sistem Informasi (JMS) Vol 4 No 1 (2024): JMS Vol 4 No 1 Maret 2024
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jms.2024.4.1.1715

Abstract

The Simpang Terusan Village Office is one of the government agencies tasked with carrying out Village Government activities, community empowerment, serving the community and maintaining public service infrastructure and facilities as well as fostering community institutions at the village level. The Simpang Terusan Village Office, apparently, does not yet have a mature enterprise architecture plan and has the desire to have an Enterprise Architecture. Without an information system strategic plan or mature Enterprise Architecture, the application of IS/IT at the Simpang Terusan Village Office will have an impact on less than optimal services provided to the community. This study aims to make an enterprise architecture plan using TOGAF ADM and test the information system architecture plan using an enterprise architecture score-card to find out whether the EA design that has been made is valid enough, so testing is needed. The research method in collecting data is to conduct interviews, observation, and document analysis. research results are made into research reports that can provide a complete picture of the system being built or the results of information system architecture planning using the designed TOGAF ADM, produce a blueprint as a guide for building an integrated information system consisting of 13 proposed applications and enterprise architecture planning that has been tested for feasibility using the EA-Scorecard method for each score calculation, namely business architecture 69%, data architecture 57%, application architecture 52%, technology architecture 61%. It can be stated that the recommendations for enterprise architecture planning at the Simpang Terusan Village Office are declared valid.
Perancangan Sistem Informasi Perpustakaan Berbasis Web Pada SMK-PP Negeri Jambi Johari, Riyan; Rasywir, Errissya; Rofi'i, Imam
Jurnal Manajemen Teknologi Dan Sistem Informasi (JMS) Vol 4 No 2 (2024): JMS Vol 4 No 2 September 2024
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jms.2024.4.2.1746

Abstract

SMK-PP Negeri Jambi, located on the road Jambi-Muara Bulian KM.36, Jembatan Mas Village, Pemayung District, Batang Hari Regency, Jambi, still uses manual records using a library agenda book to manage library administration. However, there are several problems in the process, such as the slow process of borrowing and returning books which results in long queues, and the risk of losing transaction records. In addition, officers also often have difficulty in contacting students who return books late, making it difficult to provide information to members, because they have to search for data first. Therefore, this research aims to find a solution by designing a web-based library system using agile methods and the Unified Modeling Language. This system will be built using PHP programming language with LARAVEL framework and MySQL database. The result is a book catalog menu that allows students to see complete information about the library's book collection, place book orders to reduce queues, as well as contact features via Whatsapp to remind members who return books late and notification features on the system.
Penerapan Algoritma K-Means clustering Untuk Mengelompokkan Provinsi Berdasarkan Banyaknya Desa/Kelurahan Dengan Upaya Antisipasi/Mitigasi Bencana Alam Pratama, Yovi; Hendrawan, Hendrawan; Rasywir, Errissya; Carenina, Babel Tio; Anggraini, Dila Riski
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2549

Abstract

Natural disasters are one of the natural phenomena that threaten human survival. The negative impacts can be in the form of material or non-material losses. However, with the ability to recognize the early symptoms of a disaster, humans can prepare themselves for disaster. Application of the K-Means clustering Algorithm in Grouping Provinces Based on the Number of Villages / Sub-districts with Anticipation / Mitigation Efforts for Natural Disasters Using the WEKA Application. The data sources for this research were collected based on documents describing the Number of Villages/ Urban According to Natural Disaster Anticipation/Mitigation Efforts produced by the National Statistics Agency. The data used in this study is provincial data which consists of 34 provinces. There are 4 variables used, namely Natural Disaster Early Warning System, Tsunami Early Warning System, Safety Equipment, Evacuation Path. The data will be processed by clustering in 2 clusters, namely clusters with high anticipation/mitigation levels and low anticipation/mitigation levels. The results obtained from the assessment process are that there are 5 (14.71 %) provinces with a high level of anticipation/mitigation and 29 (85.29%) other provinces including a low level of anticipation/mitigation. This can be an input for the government to pay more attention to the Village/Kelurahan based on the clusters that have been carried out
Eksperimen Layer Pooling menggunakan Standar Deviasi untuk Klasifikasi Dataset Citra Wajah dengan Metode CNN Pratama, Yovi; Rasywir, Errissya; Fachruddin, Fachruddin; Kisbianty, Desi; Irawan, Beni
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3604

Abstract

Deep Learning, especially the Convolutional Neural Network (CNN) has proven to be reliable in processing data from various programming language platforms by utilizing deep learning. In this study, we modified it by calculating the statistical variance. The modifications made are replacing calculations on the Pooling Layer which generally use two formulas, namely max pooling and average pooling. We use the standard deviation to change the reduced image intensity value. With the research experiments built, it is expected to be able to perform facial recognition as an indicator for testing modifications. The Layer Pooling experiment uses the Standard Deviation for Classifying Face Image Datasets with the CNN Method, including the type of dataset used is the Aberdeen dataset https://pics.stir.ac.uk/2D_face_sets.htm. From the results of the experiments conducted, it was found that the highest value was using the Elu activation function and the Adagrad optimizer worth 77.844% for max pooling and 79.844% for pooling with a standard deviation. The Cellu activation function and the RMSprop optimizer are 77.986% for max pooling and 75.986% for pooling with a standard deviation. The highest score with the Softplus activation function and the Sgd optimizer is 77.844% for max pooling usage and 76.344% for pooling with standard deviation. The Tanh activation function and the Adadelta optimizer are 87.844% for max pooling and 85.844% for pooling with a standard deviation. The Elu activation function and the Adam optimizer are 87.853% for the use of max pooling and 85.285% for pooling with a standard deviation. By using the Elu activation function and the Adamax optimizer, the value is 87.842% for max pooling and 86.242% for pooling with a standard deviation. The highest score is using the Elu activation function and the Nadam optimizer with a value of 87.845% for max pooling usage and 86.345% for using standard deviation calculations as pixel pooling. From all experiments it was stated that the use of pooling with the highest value technique or max pooling still gave a better value than using the standard deviation calculation with the best tuning results using the Elu activation function and Adam's Optimiser, which was 87.853%.
Reduksi False Positive Pada Klasifikasi Job Placement dengan Hybrid Random Forest dan Auto Encoder Pahlevi, M. Riza; Rasywir, Errissya; Pratama, Yovi; Istoningtyas, Marrylinteri; Fachruddin, Fachruddin; Yaasin, Muhammad
Building of Informatics, Technology and Science (BITS) Vol 5 No 4 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i4.4864

Abstract

The False Positive (FP) interpretation shows a negative prediction result and is a type 1 error answer with an incorrect positive prediction result. Based on this, we try to reduce type 1 errors to increase the accuracy value of the classification results. A low FP rate is critical for the use of Computer Aided Detection (CAD) systems. In this research proposal, to reduce FP, we use a Random Forest (RF) evaluation result design which will be reinterpreted by the Auto Encoder (AE) algorithm. The RF algorithm was chosen because it is a type of ensemble learning that can optimize accuracy in parallel. RF was chosen because it performs bagging on all Decision Tree (DT) outputs used. To suppress TP reduction more strongly, we use the Auto Encoder (AE) algorithm to reprocess the class bagging results from RF into input in the AE layer. AE uses reconstruction errors, which in this case is Job Placement classification. From the test results, it was found that combining the use of a random forest using C4.5 as a decision tree with an Autoencoder can increase accuracy in the Job Placement Classification task by a difference of 0.004652 better than without combining it with an autoencoder. Apart from that, in testing using a combination of RF and AE, fewer False Positive (FP) values ​​were produced, namely 11 items in the Cross Validation-5 (CV-5) Test, then 13 items in the Cross Validation-10 (CV-10) test and in testing split training data of 60%, the FP was only 12. This value is less than the false positives produced by testing without Autoencoder, namely 12 items on CV-5, 15 items on CV-10, and 13 on split training data
Public complaint tweet data feature analysis for sentiment classification Rasywir, Errissya; Pratama, Yovi; Irawan, Irawan; Istoningtyas, Marrylinteri
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7172

Abstract

The perception of the public regarding a government's performance significantly impacts a city's advancement. This research involved analyzing complaint tweets from Jambi City residents directed at the government to gauge sentiment. In the testing phase, 500 Twitter accounts were examined to categorize sentiment as positive, negative, or neutral. Training data was prepared by extracting tokens through feature selection techniques such as information gain (IG) and mutual information (MI). For testing, all tokens are entered as data in the input layer in the recurrent neural network (RNN). From the tests carried out, the average use of feature selection can achieve a good value compared to no feature selection. But more specifically the use of IG produces better accuracy compared to the use of MI. From the research conducted, Twitter data is classified using a RNN and several tests by adding feature selection to produce differences. The results are proven to improve classification performance. With a recall value of 92.243%, it shows the system's success rate in sentiment classification and a precision of 92% indicates a level of accuracy that is sufficient to support the government's sentiment assessment.
Workshop Pembuatan Konten Media Sosial Untuk Publikasi Objek Budaya Dan Wisata Pada Desa Muaro Pahlevi, M.Riza; rasywir, errissya; Hussaein, Ahmad; Rosario B, Maria; Nurhadi, Nurhadi; Setiawan, Roby; Pratama, Yovi
Jurnal Pengabdian Masyarakat UNAMA Vol 3 No 1 (2024): JPMU Volume 3 Nomor 1 April 2024
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jpmu.2024.3.1.1614

Abstract

Abstrak Dalam era digital dan globalisasi, konten budaya dan wisata berperan penting dalam mempromosikan serta melestarikan warisan budaya suatu daerah. Desa-desa memiliki potensi besar dalam hal ini, namun seringkali belum tereksplorasi. Melibatkan generasi muda dalam penciptaan konten budaya dan wisata menjadi krusial. Perkembangan teknologi dan digitalisasi mengubah cara kita berinteraksi dan berkomunikasi. Desa-desa juga terpengaruh oleh perkembangan ini. Melalui program Pengabdian kepada Masyarakat berjudul "Mengajak Generasi Muda Berkontribusi dalam Menciptakan Konten Budaya dan Wisata", tujuan program ini adalah menginspirasi generasi muda desa dan pokdarwis (kelompok sadar wisata) agar terlibat aktif dalam pembuatan konten berfokus pada budaya dan keindahan wisata di sekitar mereka. Pengabdian kepada Masyarakat yang melibatkan generasi muda dan PokDarWis (Kelompok Sadar Wisata) dalam workshop pembuatan konten budaya dan wisata, seperti vlog, video dokumenter, dan cerita interaktif. Dengan melibatkan generasi muda, diharapkan akan tercipta konten yang lebih segar dan relevan pada Desa Muaro Pijoan. Kata kunci: Konten, Sosial, Media, Wisata, Teknologi. Abstract In the era of digital and globalization, cultural and tourism content plays an important role in promoting and preserving a region's cultural heritage. Villages have great potential in this regard, but it is often unexplored. Involving the younger generation in creating cultural and tourism content is crucial. Technological developments and digitalization are changing the way we interact and communicate. Villages are also affected by this development. Through the Community Service program entitled "Inviting the Young Generation to Contribute in Creating Cultural and Tourism Content", the aim of this program is to inspire the young generation of villages and pokdarwis (tourism awareness groups) to be actively involved in creating content focused on the culture and beauty of tourism around them. Community Service involving the younger generation and PokDarWis (Tourism Awareness Group) in workshops on creating cultural and tourism content, such as vlogs, documentary videos and interactive stories. By involving the younger generation, it is hoped that fresher and more relevant content will be created in Muaro Pijoan Village. Keywords: Content, Social, Media, Travel, Technology.
Increasing the Accuracy of Brain Stroke Classification using Random Forest Algorithm with Mutual Information Feature Selection Fachruddin, Fachruddin; Rasywir , Errissya; Pratama, Yovi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 4 (2024): August 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i4.5795

Abstract

Brain stroke stands out as a leading cause of death, distinguishing it from common illnesses and highlighting the critical need to utilize machine learning techniques to identify symptoms. Among these techniques, the Random Forest (RF) algorithm emerged as the main candidate because of its optimal accuracy values. RF was chosen for its ensemble learning properties that optimize accuracy while simultaneously, bagging all outputs (DT), thus increasing its efficacy. Feature Selection, an important data analysis step, which is mainly achieved through pre-processing, aims to identify influential features and ignore less impactful features. Mutual Information serves as an important feature selection method. Specifically, the highest level of accuracy was achieved by cross-validating the test data - 10, resulting in 0.7760 without feature selection and 0.7790 with mutual information. Most of the attributes in the brain stroke dataset show relevance to the stroke disease class, but the resulting decision tree shows age as a particularly important node. So, the research results show that the selection feature (Mutual Information) can increase the accuracy of brain stroke classification, although it is not significant, namely an increase of 0.0030%. With an increase, where there is no significant difference, it can be said that almost all the attributes contained in the brain stroke dataset used have an influence on their relevance to the stroke disease class.
Enhancing Areca Nut Detection and Classification Using Faster R-CNN: Addressing Dataset Limitations with Haar-like Features, Integral Image, and Anchor Box Optimization Pratama, Yovi; Rasywir, Errissya; Suyanti; Siswanto, Agus; Fachruddin
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6496

Abstract

The classification and detection of areca nuts are essential for agriculture and food processing to ensure product quality and efficiency. The manual classification of areca nuts is time-consuming and prone to human error. For a more accurate and efficient automated approach, a deep learning-based framework was proposed to address these challenges. This study optimizes the Faster R-CNN by integrating Haar-like features and integral images to enhance object detection. However, dataset limitations, including low image quality, inconsistent lighting, cluttered backgrounds, and annotation inaccuracies, affect the model performance. In addition, the small dataset size and class imbalance hindered generalization. The Faster R-CNN model was trained with and without Haar-like Features and Integral Image enhancement. Performance was evaluated based on training loss, accuracy, precision, recall, F1-score, and mean average precision (mAP). The effects of the dataset limitations on detection performance were also analyzed. The optimized model achieved better stability, with a final training loss of 0.2201, compared to 0.1101 in the baseline model. Accuracy improved from 62.60% to 73.60%, precision from 0.6161 to 0.7261, recall from 0.3094 to 0.4194, F1-score from 0.2307 to 0.3407, and mAP from 0.1168 to 0.2268. Despite these improvements, dataset constraints remain a limiting factor. While the integration of Haar-like features and integral images into faster R-CNN contributes to detection accuracy, the study also reveals that high-resolution images, precise annotations, and dataset scale significantly amplify model performance.
Co-Authors Abdul Haris Abdul Harris Abdurrahman Abidin, Dodo Zaenal Abrani, Sauti Ade Saputra Agus Siswanto Akwan Sunoto Anggraini, Dila Riski Anita Anita Nurjanah Annisa putri Anton Prayitno Arya Atmanegara Aryani, Lies asih asmarani Athalina, Ghita Bayu saputra Beni Irawan Betantiyo Prayatna Borroek, Maria Rosario Briyan Chairullah Candra Adi Rahmat Carenina, Babel Tio Clara Zuliani Syahputri Defrin Azrian Desi Kisbianty, Desi Despita Meisak desy ayu ramadhanty Dimas Pratama Dodo Zaenal Abidin Dwi Rosa Indah Elsa Charolina L Siantar Evan Albert Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin, Fachruddin farchan akbar Feranika, Ayu Fernando Fernando fiqri ansyah Fradea Novi Ramadhayanti GILLIANI, WENNY Hani Prastiwi Hartiwi, Yessi Hendrawan Hendrawan Hendrawan Hendrawan Hendrawan Hendrawan Hilda Permatasari Hussaein, Ahmad Ilham Adriansyah Ilham Fahrozi ilham permana Imelda Yose Iqbal Pradibya Irawan Irawan Irawan Irawan Irawan, Beni Istoningtyas, Marrylinteri Jasmir Jasmir Jeny Pricilia Johari, Riyan Jopi Mariyanto khalil gibran ahmad Kholil Ikhsan Lazuardi Yudha Pradana Li Sensia Rahmawati Lies Aryani Luthfi Rifky M.Rizky Wijaya Macharani Raschintasofi Maliyatul Khasanah Maria Rosario Borroek Marrylinteri Istoningtyas Marrylinteri Istoningtyas Marrylinteri Istoningtyas Mayang Ruza Mgs Afriyan Firdaus Migi Sulistiono Muhammad David Adrilyan Muhammad Diemas Mahendra Muhammad Ismail Muhammad Ismail Muhammad Riza Pahlevi Muhammad Satria Mubin Muhammad Wahyu Prayogi Mulyadi Mulyadi Mumtaz Ilham S Mumtaz Ilham Syafatullah Muttaqin Nabila Khumairo Najmul Laila Nanda Ghina Nasrul Ahlunaza Nasutioni, Wahyudi Nilu Widyawati Nungky Septia Kurnicova Nur Aini Nur Azmi Nurhadi Nurhadi Nurul Aulia OPHELIA, CHANDY Pahlevi, M. Riza Pahlevi, M.Riza Pareza Alam Jusia Pareza Alam Jusia Pareza Alam Jusia, Pareza Alam Putri Ratna Sari, Putri Ratna Rani Oktavia, Feby Renita Syafitri Reza Pahlevi Rio Ferdinand ROBY SETIAWAN Rofi'i, Imam Rohaini, Eni Rosario B, Maria Rosario, Maria Rts CiptaNingsi Rudolf Sinaga Sandi Pramadi Saparudin, Saparudin Satria Oldie Versileno Sri Wahyuni Nainggolan Sulistia Ramadhani Suyanti Tasya Basalia Sihombing Tedy Hardiyanto Tondy Maulana Tambunan Verwin Juniansyah virginia casanova andiko andiko Wahid Hasyim Yaasin, Muhammad Yessi Hartiwi Yessi Hartiwi Yoga Rizki Yovi Pratama Yuga Pramudya Zahlan Nugraha