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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 40 Documents
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Search results for , issue "Vol 13, No 3 (2024): Sistemasi: Jurnal Sistem Informasi" : 40 Documents clear
Implementing QR Codes on Student ID for Transactions: TAM Testing Approach Noviany, Caroline; Daniawan, Benny; Suwitno, Suwitno
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.v13i3.3922

Abstract

The rapid advancement of technology has had a significant impact on contemporary life. One of the technologies commonly encountered is the Quick Response Code (QR-Code) and Barcode, both of which serve a similar function, that is, to store information represented in the form of squares and lines. Three squares at the corners of the QR-Code are key to ensuring accurate scanning. Universities are educational institutions that provide Student ID Cards as a means of student identification. This research aims to design a transaction system by utilizing QR-Code technology on Student ID Cards for parking and library transactions, as well as creating a transaction system using digitized Student ID Cards. This study employs the Technology Acceptance Model (TAM) testing method to measure the factors influencing users in utilizing the application. The system design successfully incorporates QR-Codes and can be used as a transaction tool. The TAM testing results from 75 respondents regarding system acceptance conclude that the Perceived Ease of Use (PEOU) variable will influence the Perceived Usefulness (PU) variable by 67.4% and affect the Behavioral Toward Using (BITU) variable by 55.1%.
Air Quality Index Classification for Imbalanced Data using Machine Learning Approach Jayadi, Bryan Valentino; Lauro, Manatap Dolok; Rusdi, Zyad; Handhayani, Teny
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.v13i3.3503

Abstract

Air pollution is one of the problems in society. Air pollutions affect human health and environment. In Indonesia, air quality index is measured by the level of particulate matter 10 (PM10), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3), and nitrogen dioxide (NO2). This research is conducted to evaluate the performance of machine learning algorithms, e.g., Support Vector Machine (SVM), Naïve Bayes, Logistic Regression, Decision Tree, and AdaBoost, to classify air quality index based on the level of PM10, CO, SO2, O3, and NO2 with imbalanced samples. The air quality index is classified into Good, Moderate, and Unhealthy. The dataset is downloaded from Open Data Jakarta from 2010 -2021. The data containing 4383 samples consist of 1155 samples of Good, 3087 samples of Moderate, and 141 samples of Unhealthy. The experimental results show that Decision Tree outperforms other methods. Decision Tree produces accuracy, precision, recall, and F1-score of 99%, 98%, 99%, and 98%, respectively.
Sentiment Analysis of the Minister of Education and Culture using Vader and RBF, Polynomial, Linier Kernels SVM Based on Binary Particle Swarm Optimization Sinaga, Rutlima; Ashari, Ilham Firman; Yulita, Winda
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.v13i3.2186

Abstract

Comments from social media can be analyzed further. Social media is used to interact from one person to another, as well as with the government. This Issue Was Raised Because Of Debate And Public Opinion From The Community, Institutions And Ngos Regarding Ministerial Regulation No. 30 Of 2021 Concerning Prevention And Handling Of Sexual Violence. In The Higher Education Environment, Therefore In This Research We Want To Examine What Is The Main Root Of The Problem Using A Methodical Approach Using Natural Language Processing. The pre-processing applied is case folding, tokenization, elimination of stop words, stemming using literature. The model implementing PSO failed to improve accuracy on all kernels. Best performance before applying PSO to twitter dataset using linear kernel. This study conducted sentiment analysis regarding the issuance of ministerial regulation no. 30 of 2021. The data obtained was then preprocessed. The performance measured is accuracy and f1-macro in the model without PSO and accuracy in the model using accuracy. The model to be formed uses linear kernels, RBF and polynomials of order 1 and order 2. Sentence analysis is a field that analyzes sentiment, attitudes and emotions of entities and their attributes in text form. The aim of this research is to compare the performance of the Support Vector Machine classification algorithm without Particle Swarm Optimization feature selection and the performance of the Support Vector Machine classification algorithm using Particle Swarm Optimization feature selection. The data obtained is then pre-processed. The data set was automatically labeled using VADER (Valence Dictionary for Sentiment Reasoning). The kernels that succeeded in increasing accuracy were the RBF kernel and polynomials on the Twitter dataset. Keywords: SVM, Vader, PSO, Sentiment Analysis, Government Policy
Sentiment Analysis of Air Pollution on Social Media: Systematic Literature Review Permana, Yandi Dwi; Gofur, Abdul; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
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.v13i3.3679

Abstract

The need for a healthy and pollution-free environment is the basis of the problem that this study examines. Social media has become an integral aspect of daily existence for the majority engaged in the digital realm. It enables individuals from various backgrounds to utilize these platforms to stay updated on the latest information, such as the current state of pollution in Jakarta. This research explores the attitudes of social media users regarding their perspectives on air pollution in Jakarta. The method used includes conducting a Systematic Literature Review of academic papers released from 2020 to 2023. The results of this research can unveil the types of social media platforms utilized, the quantity of datasets, the procedures for data collection, data preprocessing techniques, and the commonly employed methods in sentiment analysis studies concerning the subject of air pollution.
Analysis and Design of a Food Price Prediction System using the Iconix Process Method Arisandi, Desi; Anjelie, Mega Karina; Sutrisno, Tri
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.v13i3.3952

Abstract

The need for food is very important for human survival. Therefore, food prices have a very big influence. Several factors cause unstable food prices, including increased demand during major holidays, and seasonal or weather factors that result in crop failure. Because of these factors, price increases can occur at any time and have an impact on society if prices rise unexpectedly. Based on these problems, a system was designed to predict food prices using the Iconix system development method, and to calculate price predictions using the Least Square method. In this system, analysis and system design is carried out to predict food prices. The predicted food ingredients will be limited to ten food ingredients, namely rice, shallots, garlic, red chilies, cayenne peppers, beef, chicken, granulated sugar, cooking oil and purebred chicken eggs. The process design used to describe information systems is the design of system flow diagrams, use case diagrams, sequence diagrams, activity diagrams. Black Box testing provides results that each feature in the food price prediction system has been successfully created and functions well.
Requirements Engineering for Integrated Social Assistance Distribution Information Systems Using a Microservices Architecture Approach Angelini, Siski; Bangkalang, Dwi Hosanna
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.v13i3.4140

Abstract

Distribution of social aid on target is important to help the welfare of people in need. In Bugel Subdistrict, Salatiga, this distribution has several problems, namely, data discrepancies, the application process is not transparent, and there is no distribution monitoring, resulting in social assistance recipients not being on target and affecting decisions on providing assistance for the next period. Therefore, a social assistance distribution information system is needed to assist in managing integrated data collection and monitoring distribution and application status. The information system requirements engineering method uses the system engineering life cycle method developed by Alexander Kossiakoff with a focus on the concept development stage. This research aims to identify the initial needs for a data management information system for social assistance recipients by producing a distribution of coordinate points as well as new distribution and submission monitoring features using a microservices architecture approach and visualizing with a design display using mobile first design technology referring to a responsive mobile display, containing detailed information, images , location routes to improve the performance of social assistance administrators with real-time data access
Creating Android-based System Aiding Tebuireng Waste Bank Management using Looker Studio sukmo, guruh; Wira Ghani, Sulung Rahmawan
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.v13i3.3960

Abstract

Due to the growing influx of visitors in the Tebuireng area, there has been a substantial rise in the accumulation of waste. Bank Sampah Tebuireng (BST) has been established as a concrete effort to address the negative consequences arising from the increasing accumulation of waste. However, the BST still relies on manual data management, which is prone to errors and lacks efficiency. Therefore, the development of an efficient and effective information system becomes crucial. This research aimed to develop an Android-based information system using Kodular and utilize Looker Studio for dashboard visualization for waste bank management in the Tebuireng area. The development methodology included requirement analysis, system design, implementation, and testing. The Android-based information system encompassed features such as transportation, sorting, waste sales, as well as data reporting and analysis. Users could access this system through a user-friendly Android application. Data visualization using Looker Studio displayed interactive graphs, diagrams, and tables for monitoring and analyzing waste bank management data in Tebuireng. The system testing involved evaluation through black box testing. This research has created a user-friendly Android system for Bank Sampah Tebuireng. The system streamlines waste transportation, sorting, and sales processes. Furthermore, this research utilizes Looker Studio for data visualization and interactive reporting, making it user-friendly for day-to-day use and an effective tool for waste management data analysis. Keywords: Bank Sampah Tebuireng, Android, Kodular, Looker Studio, Black Box Testing.
Web-Based Decision Support System for Best Employee Selection in Government Institutions using Analytical Hierarchy Process (AHP) Method Prapto, Dwi Atmodjo Wismono; Sipahutar, Rosen; Purwaningsih, Mardiana
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.v13i3.2796

Abstract

Government institutions are often constrained when making decisions regarding selecting the best employees due to the unavailability of an adequate decision support system. In fact, with this system, determining the best employees can be done easily and quickly. One method that can be used is the Analytical Hierarchy Process (AHP) which supports multi-criteria selection. This web-based decision support system designed has six criteria. From the calculation results of the priority weight value for each standard, the Court Punishment criteria have the highest priority value compared to other measures. Thus the requirements for this Court Punishment will be the primary consideration in calculating the value of outstanding employees. These criteria are then used for the simulation of 10 ministry employees. The simulation results show that the designed AHP technique is proven to prepare data for high achieving employee candidates accurately.
Comparison of XGboost, Extra Trees, and LightGBM with SMOTE for Fetal Health Classification Kartika Handayani; Badariatul Lailiah
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.v13i3.3646

Abstract

Cardiotocography (CTG) is widely used by obstetricians to physically access the condition of the fetus during pregnancy. This can provide data to the obstetrician about fetal heart measurements and uterine duration which helps determine whether the fetus is pathological or not. Determining the pathological classification or not can be done using machine learning methods. In this research, there is a problem of unbalanced data or data imbalance. To overcome data instability, testing using SMOTE is used. Then a comparison was made with the classifications, namely XGboost, Extra Trees and LightGBM. XGboost, Extra Trees and LightGBM testing results using SMOTE obtained the best results at 91.52% accuracy, 90.49% recall and 89.12% f1-score produced by LightGBM. Meanwhile, the best results were 89.07% precision and AUC 0.9800 produced by Extra Trees.
Sentiment Analysis of pegipegi.com Review on Google Play Store with Naïve Bayes Balit, Muhamad Naufal Burhanuddin; Utomo, Fandy Setyo
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.v13i3.3913

Abstract

In the current era, a shift in consumer behavior is evident in the use of online platforms for booking tickets, involving various services such as flights, hotels, trains, buses, and entertainment. PegiPegi.com, as a rapidly growing online travel agent in Indonesia, demonstrates success by understanding the value of technology and maintaining strong partnerships. This phenomenon also impacts sentiment analysis, where users of this platform often provide reviews. This research aims to apply the Naïve Bayes classification method in sentiment analysis of PegiPegi.com reviews, focusing on understanding customer satisfaction and service improvement. By combining these approaches, the study contributes to a deeper understanding of user responses to OTA services and presents the evaluation results of the Multinomial Naive Bayes classification model with an accuracy rate of 89.5%. The high precision in the Negative class indicates the model's ability to identify negative reviews. However, there are challenges in classifying the Neutral class, suggesting potential for further improvement. Nevertheless, the F1-score of 0.522 reflects a good balance between overall precision and recall.

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