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INDONESIA
Sistemasi: Jurnal Sistem Informasi
Published by Universitas Islam Indragiri
ISSN : 23028149     EISSN : 25409719     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Sistemasi adalah nama terbitan jurnal ilmiah dalam bidang ilmu sains komputer program studi Sistem Informasi Universitas Islam Indragiri, Tembilahan Riau. Jurnal Sistemasi Terbit 3x setahun yaitu bulan Januari, Mei dan September,Focus dan Scope Umum dari Sistemasi yaitu Bidang Sistem Informasi, Teknologi Informasi,Computer Science,Rekayasa Perangkat Lunak,Teknik Informatika
Arjuna Subject : -
Articles 1,011 Documents
 58   59   60   61   62 
Implementation of Web-Based Student Achievement Applications in Senior High Schools in Indonesia Hafidz, Mohammad Al; Puspitaningrum, Ari Cahaya; Prasetya, Muhammad Septama; Fitrani, Laqma Dica
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4143

Abstract

Obtaining student achievement provides benefits for schools for accreditation assessment, curriculum determination, feedback and policy. SMA N 1 Waru is a Senior High School in Indonesia in the National Reference School category which almost every year gets achievements. Currently, management of achievement data has not been carried out optimally, accumulated achievement data cannot be displayed, storage of supporting data is not organized, and the accuracy of the information produced is hampered. This research aims to implement a website-based student achievement application. The method used is in two stages, data collection and application development. The application development technique uses the Rapid Application Development (RAD) model. This research produces an application that has functionalities: master data (period, type of achievement, level of achievement/certification, class), teacher data collection, student data collection, achievement data collection (proposal and approval of achievements), user management, achievement reports, and achievement dashboards, as well as manage user user access. All functionalities have passed testing using the black box testing method. Implementation of applications using RAD can be done quickly and effectively so that the school gets the benefits of collecting achievement data at any time, achievement information can be accessed by anyone who needs it, the information produced is accurate, and has storage media for achievement supporting documents that can be well organized.
Application of k-Means Algorithm on Clustering Poor Population Data for Extreme Poverty Elimination Syaharani, Widya; Sriani, Sriani
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4384

Abstract

Poverty is one of the social problems faced by almost every country in the world. One of the factors causing poverty has not been resolved, namely in an implementation of social assistance policies, the government's survey of the community is still carried out manually so that it is not right on target. So, this research aims to identify the criteria possessed by each group of poor people resulting from data grouping using the K-Means clustering algorithm. By applying the K-Means clustering algorithm to the data of the Targeting for the Acceleration of the Elimination of Extreme Poverty (P3KE) of Sei Litur Tasik Village and modeling the data clustering of the poor population of Sei Litur Tasik Village. The results of testing and evaluating the K-Means Clustering model on the data of the Acceleration of the Elimination of Extreme Poverty (P3KE) are determined to be 2 optimal clusters with an interia value of 0.40 using the Silhouette Score testing method where cluster 1 rich category is 366 families and cluster 2 poor category is 60 families. Modeling of the data clustering system design using the K-Means clustering method was carried out on Google Collaboratory and assisted by supporting literature. The results showed the accuracy of K-Means clustering of 85.92% which means that the accuracy of the analyzed data can be correctly grouped into the appropriate cluster category.
Market Basket Analysis using the Frequent Pattern Growth Algorithm at RJ Mart Melaris arrafiq, ubay hakim; Azhar, Yufis; Wicaksono, Galih Wasis
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.3634

Abstract

Marketing strategy in a business is a major factor in the success or failure of a business both micro, medium and macro. With an effective and efficient marketing strategy It is hoped that it can increase income to the maximum. Currently, technological developments are very fast, including carrying out transactions that are directly connected to the database, resulting in very large data growth. The data itself can be used as a source of information to determine the right marketing strategy. The main aim of this research is to maximize the existing marketing strategy at RJ Mart Melaris by utilizing data as a source of information and consideration. The choice of Market Basket Analysis as a method for utilizing data is because these medium-sized businesses need consideration to develop sales by forming effective product packages. Frequent Pattern Growth is used as an effective algorithm to form combinations of product items or what is usually called an association rule. Some of the benefits resulting from this research are knowing how likely a product is to be purchased at the same time as other products, what products are sold the most and the least so that you can maximize stock of goods, and the relationship between products to maximize the placement of goods. This research produced 8 Association Rules or product combinations with 6 different items. The strongest rule that is generated is that if you buy special fried Indomie and chicken curry Indomie, you will definitely also buy special chicken Indomie with an association strength of 8,472. Meanwhile, the item that is most often purchased together with other items is the special fried Indomie, which sells 50% together with the special chicken curry Indomie and special chicken Indomie. Apart from that, this research also produced 2 different groups of items, each item in the group has a sales relationship.
Breast Cancer Classification based on Ultrasound Images using the Support Vector Machine (SVM) Algorithm Aprilia, Nurazmi; Rumini, Rumini
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4113

Abstract

According to statistics from the Global Burden of Cancer Study (Globocon) of the World Health Organization (WHO), cancer, particularly breast cancer, is a severe health issue in Indonesia with 68,858 new cases and 22,000 deaths recorded in 2020. Ultrasonography (USG) technology is acknowledged as one of the potentials to support early detection, which is vital in reducing mortality from breast cancer. This study focuses on classifying ultrasound images using the Support Vector Machine (SVM) algorithm, GLCM feature extraction, Min-Max normalization, and Mutual Information with SelectKBest Feature Selection. From several experiments using the SVM algorithm with various combinations of parameter values that have been set and different Tests, namely using a Train/Test Split with a proportion of 80/20 and K-Fold Cross Validation, it shows that the SVM algorithm is capable of classifying ultrasound images of breast cancer. into two categories (Benign Tumor and Malignant Tumor) with the same maximum accuracy of 79% after applying the SMOTE Balancing Data technique or without using the Balancing Data technique. As a result, the Support Vector Machine (SVM) algorithm has the potential to be an effective model for identifying breast cancer ultrasound images, both on data from the original set that has not been balanced and data from the set that has been balanced.
Distribution Information System at Rani Motor Workshop with DRP Method to Improve Sparepart Delivery Timeliness Gunawan, Haris; Fakhriza, Muhammad
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4346

Abstract

Rani Motor Workshop in North Sumatra faces several problems in its operations, such as inefficient inventory management, late delivery of spare parts, and unstructured distribution planning. This research aims to overcome these problems by integrating the Distribution Requirement Planning (DRP) method in its distribution information system using a research and development (R&D) approach and a waterfall development model. By detailing the flow of data input, distribution planning, parts delivery, and distribution performance recording, this research proposes a framework that integrates the research & development method and the waterfall system development method. Through these steps, this research aims to improve the efficiency and timeliness of delivery. The results of this research are expected to make a positive contribution to the operations of Bengkel Rani Motor, by proving that the implementation of a distribution information system using the DRP method can optimize stock, reduce delays, and increase customer satisfaction.
Evaluation of Tenderplus.id Application User Experience using USE Questionnaire Anggraini, Nadia Rahmi Nur; Wahyuni, Elyza Gustri
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4199

Abstract

E-procurement is a process of procuring goods and services that utilizes information and communication technology. Service providers usually access the Electronic Procurement Service (LPSE) website to carry out the e-procurement process. The LPSE website displays hundreds to thousands of government and non-government tenders, which can often reduce the effectiveness of the tender process due to the amount of information that must be managed. To address this issue, the Tenderplus.id application was developed, which is designed to monitor the latest tender packages in the Indonesian government's LPSE. The app features real-time notifications sent via WhatsApp and Email to service providers according to their company preferences and qualifications. The Tenderplus.id application user experience was measured using the USE Questionnaire (Usefulness, Satisfaction, and Ease of Use Questionnaire) method, which evaluates four main variables: usefulness, ease of use, ease of learning, and satisfaction, using a Likert Scale from one to five. The evaluation results show that the overall user experience obtained a percentage value of 83.6%, which is categorized as very feasible. The percentage details for each variable are usefulness of 87.8%, ease of use of 83.3%, ease of learning of 77.5%, and satisfaction of 84%. Implementation and testing of this application showed very positive results, strengthening the conclusion that Tenderplus.id is an effective solution to the problems faced in managing electronic tenders.
ETLE Sentiment Analysis Performance Increasement with TF-IDF, MDI Feature Selection, and SVM Syiarul Amrullah, Muhammad; Putrada, Aji Gautama; Nurkamal Fauzan, Mohamad; Alamsyah, Nur
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.2701

Abstract

In Indonesia, the government, through the Indonesian National Police (POLRI), has just released a new regulation, the Electronic Traffic Law Enforcement (ETLE). A traffic ticket policy is carried out electronically through camera monitoring connected directly to the vehicle registration certificates (STNK) database. The government can measure people's likes or dislikes of these public policies through sentiment analysis. There have been studies that have applied sentiment analysis to find out people's responses to ETLE. However, in terms of performance, this model only has an accuracy of 0.42. This study proposes the use of a support vector machine (SVM), term frequency-inversed document frequency (TF-IDF), and mean decrease in impurity (MDI) to evaluate polarization sentiment analysis on ETLE policies. First, we retrieve tweets about ETLE from Twitter. Then we do text analysis pre-processing and the remove stop words process. The next step is to carry out the TF-IDF process. We apply two feature selection methods for our comparison: MDI and recurrent feature elimination (RFE). Next, we compare two classification models, namely naïve Bayes and SVM. Some  of the metrics that we use to evaluate the pre-processing stage are the probability density function (PDF) and the t-test. We use the bag of words (BoW) to evaluate the remove stop words stage. Finally, sensitivity, specificity, and the receiver operating curve (ROC) are for evaluating feature selection methods and classification methods. The test results show that TF-IDF produces 1,022 new features. The combination of the methods we used resulted in the six models we compared. SVM+TF-IDF+MDI is the model with the best performance compared to the other five models. Accuracy and area under curve (AUC) scores are 0.99 and 0.97, respectively.
Comparison of Decision Trees, Naïve Bayes and Random Forest in Detecting Heart Disease Erni, Erni; Sa'adah, Rabiatus
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4163

Abstract

The leading cause of human death is heart disease (HD) worldwide which generally occurs when the heart is unable to push enough fresh, oxidized blood to the rest of the body. This disease makes it more difficult for the heart muscle to pump blood efficiently and causes chest pain, chest pressure, shortness of breath, pain in the neck and jaw. The aim of this research is to compare and obtain the best accuracy results from the three methods used, namely Random Forest, Extra Trees Classifier and Naïve Bayes. The results of this research prove that the Extra Trees Classifier method with an accuracy of 86.93% has higher results compared to the Naïve Bayes method with an accuracy of 84.21%, and the Random Forest Classifier method with an accuracy of 84.21%. Meanwhile, the AUC results obtained by the Extra Trees Classifier method are higher than other methods with an AUC of 93.81%.
Analysis of User Acceptance of The 2013 Curriculum E-Report from a Gender Perspective using UTAUT Model Megawati Megawati; Rimet Rimet; Tita Alisya
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.3902

Abstract

SMK IT Al-Izhar Pekanbaru has implemented an Information System for Managing Report Values to make it easier for teachers to manage student report cards. This report card system has been used since 2015. The behavioral aspect is a very important aspect, because it relates directly to users. The thing that underlies this research is that there are still teachers who do not understand how to input student grades, so they tell other teachers to input grades into the system. The purpose of this study was to determine the factors that most influence user behavior interest based on the UTAUT variable consisting of performance expectancy, effort expectancy, social influence, facilitating conditions and moderated by gender, age and experience variables. The results of this study indicate that the factors that most influence user behavior interest are performance expectancy, effort expectancy, and facilitating conditions. while the moderator variable gender affects user interest by 79.0%. As well as the finding of a gap (GAP) between the expectations of the school and the perception of users. To overcome the GAP, the school must evaluate and monitor the implementation of the report card value management information system at SMK IT Al-Izhar Pekanbaru.
Implementation of the User Centered Design Method in the Android-Based Digital Financial Literacy Media Interactive Education Application (Case Study: Medan City MSMEs) Aprilia, Annisa; Ikhwan, Ali
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4403

Abstract

The existence of information and communication technology in this digital era has changed the way people interact with money and finance, especially with the emergence of internet developments such as mobile banking, e-commerce, and fintech which have brought great progress in the way people transact and manage finances. Financial transactions that are increasingly related to digital technology bring new benefits and challenges for UMKM business actors, the introduction of digital financial literacy in the context of UMKM is an important step in facing technology-driven business transformation. However, until now there are still many UMKM who still lack understanding of digital financial literacy. Lack of understanding about online transaction security, selection of appropriate services, and digital data management can hinder growth and potentially increase risks for UMKM later. This makes the need for digital financial literacy for UMKM even more real, this research will focus on helping to provide understanding to UMKM actors, especially Medan City about digital financial literacy through interactive educational applications by applying the User Centered Design Method for the development of their user interface, it is hoped that through this application UMKM actors in the city of Medan can optimize their understanding of digital financial literacy so that they can Take full advantage of financial technology to improve operational efficiency, grow businesses, and participate in the digital economy more effectively.

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