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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
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Regional Grouping Based on Cubic Water Using K-Means Algorithm at Perumda Air Minum Tirta Silaupiasa Asahan Regency Munawar, Fajar; Nasution, Akmal; Santoso, Santoso
Sistemasi: Jurnal Sistem Informasi Vol 13, No 2 (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.v13i2.4027

Abstract

Perumda Air Minum Tirta Silaupiasa Asahan Regency is a regional company that has the authority to provide clean water consumption needs for the community in Asahan Regency. Currently, clean water needs, especially for households and industries in Asahan Regency, are supplied by Perumda Air Minum Tirta Silaupiasa which is located at Jalan Jend. Ahmad Yani No. 33, Kisaran, Sei Renggas, West Kisaran, Sei Renggas, West Kisaran City District, Asahan Regency, North Sumatra 21213. Currently, the need for clean water for the people of Asahan Regency comes from Perumda Air Minum Tirta Silaupiasa Asahan Regency. However, the amount of clean water provided for people living in areas with high cubic water in Asahan Regency is still relatively small, this is because the Perumda Air Minum Tirta Silaupiasa Asahan Regency does not know which areas have high, medium and low cubic water usage. Therefore, Perumda Air Minum Tirta Silaupiasa Asahan Regency needs to follow up on this problem by grouping areas based on water cubic. To manage the data, a technique is needed that can be used to extract information from the data, the technique is Data Mining. The purpose of this system is to find out how to analyze water cubic data using the K-Means Algorithm and design a website-based system with the PHP programming language and MySQL Database to determine areas with high, medium, and low water cubic. K-means clustering is a data analysis method or data mining method that performs unsupervised modeling and is one of the data clustering methods using a partition system. The data obtained in the recap of cubic water data at Perumda Air Minum Tirta Silaupiasa Asahan Regency for the period 2021-2023. The research method used in this research is quantitative research method. From the results of implementation and testing the results of the calculation of the K-means clustering method are the results of clustering cubic water in the Asahan district area with high water cubic including West Kisaran with a minimum value of 101727.9655 and East Kisaran with a minimum value of 101727.9655. Then in the Asahan district area with medium water cubic including Air Joman with a minimum value of 151144.2025 and Simpang Empat with a minimum value of 151144.2025. Then in the Asahan district area with low water cubic including B.P Mandoge with a minimum value of 66801.4373, Buntu Pane with a minimum value of 105608.8293, Desa Gajah with a value of 59925.2623, Lubuk Palas with a value of 75832.9197, Meranti with a value of 2892.8137, Sei Kamah II with a value of 47997.2206, and Sei Kepayang Barat with a value of 197781.2457.
Text Classification for Analysing Indonesian People's Opinion Sentiment for Covid-19 Vaccination eka miranda; Veronica Gabriella; Sriyanda Afrida Wahyudi; Jennifer Chai
Sistemasi: Jurnal Sistem Informasi Vol 12, No 2 (2023): 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.v12i2.2759

Abstract

The purpose of this study is to implement text mining for sentiment analysis of Indonesian public opinion on COVID-19 vaccination on Twitter social media using text classification techniques Support Vector Machine (SVM) and Random Forest. The research begins with crawling data from Twitter from September 2021 to October 2021; data cleansing; text translation into English; data preprocessing using NTLK performed with and without the lemmatization process; sentiment analysis using TextBlob; distribution of training and testing data with the Hold-Out method of 70:30 and 80:20; hyperparameter tuning with GridSearchCV; text classification with SVM and Random Forest; and testing the classification results by calculating Accuracy, Precision, Recall, F-Measure based on confusion matrix. The results show that text classification Random Forest consistently has a higher accuracy rate than SVM with the highest accuracy value of 90,59% and most of the sentiments indicate neutral to the COVID-19 vaccination program.
Use of Augmentation Data and Hyperparameter Tuning in Batik Type Classification using the CNN Model Auliaddina, Siti; Arifin, Toni
Sistemasi: Jurnal Sistem Informasi Vol 13, No 1 (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.v13i1.3395

Abstract

Batik is one of Indonesia's most recognized artistic cultures in the world and has different motifs and types of traditional batik and each has its own uniqueness. But unfortunately, there are still so many Indonesian people who cannot distinguish the types of batik based on their motifs. That's why we need a way to help people easily be able to distinguish the types of batik based on their motifs. This research was conducted to classify types of batik based on their motifs using the Convolutional Neural Network deep learning model using Data Augmentation and Hyperparameter Tuning. CNN is included in the type of Deep Neural Network because of its high network depth and is widely applied to image data. Besides that, Data Augmentation and Hyperparameter Tuning are also applied to reduce overfitting. The results of this study show that the CNN model that uses Data Augmentation optimization and Hyperparameter Tuning gets a much higher accuracy, precision and recall value of 66.67% compared to the CNN mode that does not use Data Augmentation and Hyperparameter Tuning which has validation accuracy, precision , and recall of 28.15%. Besides that, among Data Augmentation and Hyperparameter Tuning, Data Augmentation is the one that most influences the increase in validation accuracy, precision, and recall compared to Hyperparameter Tuning with an increase in validation accuracy to 64% from a validation accuracy of 28.15%.
Best Student Classification using Ensemble Random Forest Method Mrg, Ricky Aulia; Hasibuan, Muhammad Siddik
Sistemasi: Jurnal Sistem Informasi Vol 13, No 3 (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.v13i3.4101

Abstract

Education at Madrasah Aliyah Negeri 1 Medan considers religious values, ethics, leadership, and participation in extracurricular activities as an integral part of student character building. Therefore, it is necessary to develop a classification system that integrates these various aspects to ensure that the best students not only excel in academic exams but also have strong social, leadership, moral and extracurricular abilities. The purpose of this research is to implement the Random Forest Ensemble method in predicting the best students of MAN 1 Medan and build a system in predicting the best students of MAN 1 Medan using the Random Forest Ensemble method. The data used is 550 divided into 385 data as Training data and 165 Testing data. In the implementation of Random Forest with three decision trees formed from entropy calculations on 385 training data, followed by testing using 10 testing data from a total of 165 existing data, the results show that the model predicts 8 data as class 1 (best students) and 2 data as class 0 (normal students) from a total of 10 testing data. From the test results using 385 training data and 165 testing data, the Random Forest model predicted 70 data as the best students (class 1) and 95 data as normal students (class 0) with high precision for both classes (0.94 for class 0 and 0.99 for class 1), as well as high recall for both classes (0.92 for class 0 and 0.99 for class 1) The overall accuracy reached 0.96, confirming the model's ability to classify the data well overall.
Comparison of Phishing Detection Tests using the SVM Method with RBF and Linear Kernels Rumini, Rumini; Norhikmah, Norhikmah; Mustofa, Ali; Pradana, Sulistyo
Sistemasi: Jurnal Sistem Informasi Vol 12, No 3 (2023): 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.v12i3.2882

Abstract

Phising adalah sebuah tindakan kriminal untuk mencuri informasi pribadi orang lain menggunakan entitas electronic, salah satunya adalah website. Informasi ini dicuri dari website yang telah diakses yang mengandung phising atau dengan kata lain masuk ke dalam kategori website phising. Tujuan dari web phising adalah membuat pengguna percaya bahwa mereka berinteraksi dengan situs resmi. Umumnya informasi yang dicari phisher (pelaku phising) adalah berupa username, password, baik itu akun media sosial atau akun nomor kartu kredit dengan cara diarahkan ke sebuah situs website palsu. Maka dari itu perlu adanya deteksi web phising yang berguna untuk melindungi user dari tindak pencurian informasi pengguna. Penelitian ini membahas dua kernel dalam metode SVM (Support Vector Machine) untuk deteksi web phising yaitu kernel RBF (Radial Basis Function) dan kernel linear. Akurasi yang didapatkan dengan ketiga kernel menghasilkan nilai akurasi yang berbeda-beda. Hasil akurasi pengujian sistem deketksi web phising dengan Kernel Linear sebesar 92.582 % dan Kernel Radial Basis Function sebesar 96.426 %. Akurasi paling tinggi dengan metode SVM untuk deteksi web phising yaitu menggunakan kernel RBF (Radial Basis Function).
Public Service Performance Analysis using Servqual Method in Bandar Pasir Mandoge Village Rahmadhani, Dhea; Ramdhan, William; Syaputra, Abdul Karim
Sistemasi: Jurnal Sistem Informasi Vol 13, No 2 (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.v13i2.4002

Abstract

Improving service in an agency cannot be separated from several aspects that must be possessed, such as assurance, empathy, responsiveness, reliability and physical evidence. However, there are several obstacles in improving services at the Bandar Pasir Mandoge Village Head's Office, such as lack of information and transparency. The aim of this research is to create a decision support system using the servqual method to improve the quality of public service performance. This research applies the waterfall model to build a system with stages of analysis, design, implementation and testing. Analysis is carried out to find needs regarding the system being created. Meanwhile, the design consists of entity relationship diagrams and interface design. Next, the implementation stage was carried out at the Bandar Pasir Mandoge Village Head Office using 201 questionnaires. The aspects in this research consist of concern, physical service, responsiveness, physical reliability, and guarantee. System testing uses a black box to see the extent of the functionality of this system. Our findings are that improvements need to be made to guarantee services (communication, courtesy, communication and security). Apart from that, our system is also running well based on the results of black box testing. So this system can be used by the Bandar Pasir Mandoge Village Head's Office as a policy in making decisions to improve the performance of public services.
User Interface Design of Property Sale Application using the Design Thinking Method Ria Andriani (SCOPUS ID: 57208011426); Muhammad Iqbal Shodikin; Rizki Tri Puji Wanggono
Sistemasi: Jurnal Sistem Informasi Vol 12, No 2 (2023): 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.v12i2.2454

Abstract

The emergence of various new business fields which are dominated by trade is a sign that the Indonesian economy is progressing rapidly, the property business is one example, the property business opportunity is very promising apart from being a place to live, the purpose of people buying property is as an investment. Currently, the tendency of prospective buyers to find information about a property to be purchased is still dominated by brochures, newspapers and other information media such as Facebook, media like this are considered less attractive and less effective because sometimes the information presented is incomplete regarding the specifications of the property. which is available. Based on these problems, this research will design a prototype user interface design for buying and selling and renting property applications with a 360 view using the design thinking method. As for the results of the assessment using SEQ and feedback from respondents getting an average score of 6.4 out of an average passing score of 5.5, the usability testing of the OHome Application prototype can be said to be successful.
Usability Evaluation of Pekanbaru dalam Genggaman Application using System Usability Scale (SUS) Putera, Thariq Pratama; Angraini, Angraini; Saputra, Eki; megawati, Megawati; Fronita, Mona; Marsal, Arif
Sistemasi: Jurnal Sistem Informasi Vol 13, No 2 (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.v13i2.3782

Abstract

One of the e-Government applications that has been implemented at the Pekanbaru City Statistics and Information Communication Service is the Pekanbaru Application in Your Hand. This application has been running for approximately 2 years since it was launched on September 2, 2021 and has not undergone any assessment using specific standard methodologies to gauge end-user satisfaction levels. The purpose of this research is to assess the user-friendliness of the Pekanbaru In Hands Application website through the utilization of the System Usability Scale (SUS) method. The SUS method, known for its validity and reliability, offers a straightforward application. It comprises ten questions formulated by John Brooke, and the outcomes are presented as scores ranging from 0 to 100.. The 65 respondents consisted of ASN and non-ASN employees from the Pekanbaru City Communications, Statistics and Informatics Service. The result obtained from the SUS calculation is 59, for the adjective assessment category including ok, with a scale value of F, and including marginally low for the acceptability range category where the application can be accepted but the level of acceptance is still low. This indicates that enhancements are required for the application to achieve a higher acceptance rate. This research produces 4 suggestions for enhancing solutions, serving as valuable references in forthcoming application development.
Website-Based Customer Relationship Management Modeling At Ar-Rasyid Islamic Hospital Palembang Alzena Aisha Shakira; Ali Ibrahim (SCOPUS ID: 57203129436); Ken Ditha Tania; Ari Wedhasmara; Pacu Putra Suarli
Sistemasi: Jurnal Sistem Informasi Vol 12, No 2 (2023): 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.v12i2.2892

Abstract

Ar-Rasyid Islamic Hospital is an organization in the health sector that supports the health of the people of Palembang City. The increase in hospitals causes stakeholders to choose the best choice among other hospitals. Therefore, hospitals must have a strategy to provide maximum service to stakeholders by implementing a customer relationship management model. With the website-based CRM modeling at the Ar-Rasyid Palembang Islamic Hospital, this is a recommendation for maintaining and increasing patient loyalty. One of them is modeling at the CRM level, where market segmentation is carried out for all groups of patients by means of service automation such as customer service, FAQs, criticism of suggestions, questionnaire polling data using the Community Satisfaction Index, and parts of it, so that it can survive during business competition. After conducting research, it was found that there was an increase in the quality of hospital services because the average per element was on the verge of 80–90%, which had a very good A value. In the context of CRM, this index helps identify the success or failure of CRM modeling in meeting customer needs and expectations. Through CRM modeling with SMIs, companies can identify factors that contribute to customer retention. By understanding customer needs and preferences through the Community Satisfaction Index. With this CRM modeling, it can maintain the existence of the hospital business in the long term and ensure that patients do not switch to competitors.
DDoS Protection System for SDN Network Based on Multi Controller and Load Balancer Ulfa, Husnul; Basuki, Akbari Indra; Suranegara, Galura Muhammad; Fauzi, Ahmad
Sistemasi: Jurnal Sistem Informasi Vol 13, No 2 (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.v13i2.3802

Abstract

DDoS attacks on SDN networks can create a single point of failure that has the potential to disrupt the overall network performance. In a single controller scheme, there is a potential risk of experiencing buffer overload, leading to traffic congestion as switches must wait for responses from the controller before forwarding network packets. To address this challenge, this research implements security measures using a multi-controller and load balancer approach, aiming to enhance SDN network resilience against DDoS attacks. The system operates by distributing the workload from the main controller to a backup controller through a load balancer when indications of a DDoS attack are detected. These attack indications are determined based on the miss rate value of unique forwarding requests exceeding a specific threshold. The results of this approach have proven effective in improving the reliability, responsiveness, and quality of SDN network traffic during DDoS attacks. The testing parameters involved in this research include controller response time and network traffic quality, comprising latency, bandwidth, throughput, and jitter. Based on the test results, the multi-controller and load balancer-based approach successfully enhanced network quality and controller responsiveness by 66.51% compared to the longer single controller scenario, specifically 202.49% during DDoS attacks. In terms of controller responsiveness, there is a very slight increase of around 0.01% in latency between the two. While Multi Controller demonstrated a remarkable 43.21% increase in throughput compared to Single Controller, this improvement in throughput is accompanied by a significant 204% increase in jitter.

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