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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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Price Prediction Of Basic Material Using ARIMA Forecasting Method Through Open Data Sumedang District Kusnawi Kusnawi; M Andika Fadhil Eka Putra; Joang Ipmawati
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.v12i2.2282

Abstract

In the era of Industry 4.0, characterized by the abundance of data, there are many opportunities to carry out various data-related processes. One of these is the data forecasting process which has been widely used. By analyzing data, we can make predictions and make decisions automatically. For example, one of the problems that decision-makers, especially in Kabupaten Sumedang, must solve is the changes in the prices of basic commodities that are essential for society's consumption. The prices of these commodities in the market tend to fluctuate in the short or long term. By analyzing the available data, we can predict the direction of changes in the prices of basic commodities in the market. In this study, the ARIMA model is used, which is one of the time series models that can be used to predict the possibility of an increase or decrease in the prices of basic commodities in the market in Kabupaten Sumedang. The ARIMA model uses the previous day's price data as a benchmark to predict the prices of basic commodities in the future. After being analyzed, the results of the model will be in several ARIMA model forms. An efficient ARIMA model will be used to model the prices of basic food commodities. This research produced the three best ARIMA models, namely ARIMA(1-1-1) for broiler chicken meat, ARIMA(0-1-1) for shallots, and ARIMA(0-1-1) for garlic. The accuracy test results percentage error for the best model using MAPE show an average value below 10%. Keywords: Food staples, Forecasting, Time Series, ARIMA, MAPE
Optimizing Uncapacitated Facility Location Problem with Cuckoo Search Algorithm based on Gauss Distribution Mohammad Agung Nugroho; Eto Wuryanto; Kartono Faqih
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.v12i2.2467

Abstract

The objective of this study was to assess the capability of the Gauss distribution-based Cuckoo Search algorithm (GCS) in solving the Uncapacitated Facility Location Problem (UFLP). UFLP is an optimization problem that there are number of locations available to be built a facility so that it can serve number of customers, assuming each facility has no limits to serve customers and only a single facility is allowed to provide services to each customer. The objective function of UFLP is to minimize the combined costs of constructing facilities in an area and providing services to customers. UFLP falls under the category of NP-Hard Problems, where the computation complexity increases with the size of the data. The Cuckoo Search algorithm, which mimics the breeding behavior of Cuckoo birds, has been extensively used to tackle optimization problems. GCS was introduced to overcome the weaknesses of Cuckoo Search algorithm in terms of computational time and search accuracy. GCS used Gaussian distribution instead of Levy Flight which based on Levy distribution. In this study, the GCS algorithm was implemented using JavaScript and the dataset used was obtained from ORLib. The research outcomes showed that the GCS algorithm could achieve optimal result in all dataset.
Development of Web-based Information Media in the Information Systems and Technology Education Study Program at the Indonesian Education University Rasyad Amhar; Nuur Wachid Abdul Majid
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.v13i4.4245

Abstract

The development of information technology is currently progressing quite rapidly, one implementation of this progress is the creation of web pages or what is known as the web. The web makes it easier for people to disseminate information so that it has an impact on people's activities in meeting their needs for information, including information about study programs (prodi). The Information Systems and Technology Education Study Program is one of the study programs at the Indonesian University of Education, Purwakarta regional campus, which currently cannot publish good information related to the study program itself. Therefore, an information media is needed to be able to publish information as a whole to the wider community. The method used in development is the waterfall method, and the technology used during development includes PHP Laravel, MySQL, PhpMyAdmin, Apache Server, and Visual Studio Code. The results of this research are in the form of a web-based information system that can better present information related to Education Systems and Information Technology study programs..
Implementation of Simple Additive Weighting and Profile Matching Methods to Determine Outstanding Students at Universitas Malikussaleh Nurdin, Nurdin; Fikran, Rifzan; Retno, Sujacka
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.v13i4.4176

Abstract

Decision support system (DSS) is a computer-based system used to support data analysis and decision modeling, with the aim of increasing the effectiveness of decisions taken. In this research, SPK is needed to determine Outstanding Students. Through this research, it is hoped that the selection process for outstanding students can be optimized by choosing the evaluation method that best suits the student's characteristics and institutional goals. The results of this research also have the potential to improve the quality of graduates by providing fairer and more objective awards to those who excel. The aim of this research is to design and implement the concept of the Simple Additive Weighting (SAW) and Profile Matching methods in a system for determining outstanding students at Universitas Malikussaleh and to find out the ranking results of the two methods (SAW and Profile Matching) in selecting outstanding students at Universitas Malikussaleh. The research methodology used was literature study, data collection, Simple Additive Weighting and Profile Matching calculations, application design, testing and evaluation. The results obtained from this research are the application of the SAW and Profile Matching methods to determine outstanding students resulting in preferences with the highest score of 1 for the SAW method and the highest score of 5 for the Profile Matching method. These two methods can be applied in selecting outstanding students to help decision making because both this method produces the same best alternative
Teacher Presence Application with Geolocation and Self Potrait using Android-based Prototype Method at MTsN Binjai Gunawan, Aldi; 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.v13i4.4353

Abstract

Technological advances are developing just like scientific advances. One example of the latest technological advances is the online attendance system. At MTsN Binjai, attendance currently uses electronic-based technology, namely fingerprints, but still has several weaknesses. For example, the device cannot be used when the electricity fails, and the attendance process must be carried out alternately due to dependence on one device. In addition, fingerprints only record attendance, do not facilitate the submission of permits or illnesses, so the admin must do double work. The thing that was researched was the use of descriptive methods and the development of a system with the prototype method. The purpose of this study is to generate an Android-based absence application that can be accessed through the personal cellphones of teachers and staff who can facilitate attendance and submission of sick permits. The results of the study are expected to be a reference for schools to improve discipline for attendance.
A Model Design of Lesson Learned System (LLS) for Accountability Report: A Case Study of Tourism Promotion Agency Anshari, Ahmad
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.v13i4.3655

Abstract

The tourism industry is one of valuable industries in Indonesia that needs a high level of expertise through the knowledge management systems in order to improve the tourism service delivery quality performance. Problems faced by this institution is the complexity and hardness in defining and enhancing knowledge through an accountability report, this is due to the lack of management through the process of applying an accountability report. This attracts us to make a research about the users’ perception towards the lesson learn system prototype where this study will examine the users’ perception in designing Lesson Learn System based on the requirements in order to enhance employees knowledge through an accountability report.. After examining the perception of the lesson learn system users, we will design Lesson Learn System prototype by using User Centered Design that describe the relationship between the lesson learn system and its users by specifying the context of using the lesson learn system in tourism. This also will specify the requirements needed for the lesson learn system that help for designing the Lesson learn system design solution.
Sentiment Analysis using the Support Vector Machine Algorithm on Covid_19 Nugroho, Adytyo Wahyu; Norhikmah, Norhikmah
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.v13i4.3778

Abstract

This massive development of information technology makes it easier for people's lives in various fields, one of them is social media, social media that people use a lot to get information about news or events that are happening in Indonesia, one of which is social media Twitter which provides a lot of information for the people of Indonesia, one of which is information about Covid-19 which is currently rife in the territory of Indonesia Sentiment analysis is a branch of Natural Language Processing (NLP) which can help determine the sentiments that occur in society. This study uses data in the form of tweets to carry out sentiment analysis obtained on Twitter social media.This research utilizes one of the Supervised Learning algorithms, namely Support Vector Machine. In this study, three (3) kernels are used for the Support Vector Machine, each of which is Linear, Radial basis function and Polynomial, to find which kernel produces the highest accuracy value. From the experiments carried out using data sharing for training as much as 70% and for testing data as much as 30% of the total data of 6000 data, the resulting accuracy value for the Support Vector Machine method on the Linear kernel produces an accuracy value of 89% and for the Radial kernel base function accuracy by 90% and for the Polynomial kernel it produces an accuracy of 88%. So it is concluded for the three (3) kernels for testing the Support Vector Machine method on the Radial basis function kernel to produce the best accuracy value
Texture Features of Aglaonema Leaves with Local Binary Pattern Code Nugroho, Agung Tjahjo; Nursulistyono, Yuda; Cahyono, Bowo Eko; Subekti, Agus
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.v13i4.4180

Abstract

The Aglaonema type and quality is difficult to identify due to leaf pattern variety. For this reason, a technique is developed to classify Aglaonema types from leaf images. The Aglaonema is identified using the Local Binary Pattern (LBP) technique. The LBP recognizes objects in the form of pixel neighbor patterns in binary code, which is sensitive to the radius (R) and the number of neighbors (P) pixels. In this article we will study the appropriate radius and number of neighbors so that the LBP code becomes an accurate abject texture attribute. Experimentally, R is varied from 1 to 5 while P is varied from 4 to 24 pixels. Two types of Aglaonema with two varieties taken from each type were used to test the accuracy of the LBP code. The accuracy of the classification results is carried out with the help of K-Nearest Neighbors (KNN). The results show that the greater the number of neighbors in determining the LBP code, the more accurate the classification results. Neighbors with a total of 18 have a stable accuracy reaching a total of 79%. Increasing the number of neighbors does not significantly affect accuracy. The neighbor radius affects the batik type of Aglaonema, the wider the neighbor area, the accuracy increases up to 84%, but for the Lipstick type, the best accuracy is obtained when R=3. By choosing the right R and P, the types of Aglaonema batik and Lipstick can be differentiated well.
Phishing Website Detection Using Machine Learning Classification Method Mahmud, Azzam Fawwaz; Wirawan, Setia
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.v13i4.3456

Abstract

Phishing website merupakan mekanisme kriminal yang menggunakan social engineering serta dalih teknis untuk mengambil data identitas personal dan kredensial akun keuangan dari pelanggan. Di Indonesia sendiri menurut laporan Pengelola Nama Domain Internet Indonesia (Pandi), tercatat jumlah phishing dalam kurun waktu 5 tahun terakhir mencapai 34.622. Jumlah serangan phishing unik yang dilaporkan pada Q3 2022 sebanyak 7.988. Penelitian ini bertujuan untuk mencari algoritma machine learning klasifikasi dengan performa terbaik untuk mendeteksi phishing website menggunakan fitur-fitur URL. Algoritma klasifikasi yang akan dibandingkan adalah decision tree, random forest, dan KNN. Hasil dari penelitian ini adalah model pertama yang menggunakan decision tree didapat akurasi sebesar 0.833, presisi sebesar 0.86, recall sebesar 0.83, dan F1-score sebesar 0.83. Model kedua yang menggunakan algoritma random forest mendapat akurasi sebesar 0.834, presisi sebesar 0.86, recall sebesar 0.83, dan F1-score sebesar 0.83. Model terakhir yang menggunakan algoritma K-Nearest Neighbors mendapat akurasi sebesar 0.482, presisi sebesar 0.24, recall sebesar 0.50, dan F1-score sebesar 0.48. Maka, dari ketiga algoritma tersebut random forest merupakan algoritma terbaik untuk mendeteksi phishing website.
Development of Android Education Application for Arabic Alphabet with Artificial Intelligence for Children Pamungkas, Brian Aji; Dharmawan, Alexander; Yusup, Yusup
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.v13i4.4122

Abstract

Seventy-two percent of the Muslim population in Indonesia is illiterate in Arabic script, thus requiring early childhood education. Young children often struggle to directly learn Arabic script, necessitating the role of instructors. However, most instructors in madrasahs do not teach Arabic script intensively, prompting the need for interactive and engaging learning media for children. Therefore, the development of an Android application for teaching Arabic script to young children is crucial. By employing the Rapid Application Development (RAD) method, an Android application can be developed, incorporating gamification for interactive learning and the AI Life Cycle for developing a 3D Arabic script object detection model useful for automatic correction systems. The AI model is developed using SSD MobileNet v2 FPN Lite 640x640. Sixteen trials are conducted for separate letter modeling and two for connected letters. The separate letter modeling yields the best result in the 8th trial with a total loss of 0.182882 out of 1, using parameters of 16 batch size, 30,000 num steps, and checkpoint from the 7th trial. Connected letter modeling yields the best result in the 2nd trial with parameters of 8 batch size, 14,000 num steps, and checkpoint from the 1st trial. The output is an offline Android application integrating gamification and AI technology, featuring two categories of questions, each with 20 items.

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