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INDONESIA
JURIKOM (Jurnal Riset Komputer)
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma
ISSN : 2407389X     EISSN : 27157393     DOI : http://dx.doi.org/10.30865/jurikom.v7i1.1927
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
JURIKOM (Jurnal Riset Komputer) membahas ilmu dibidang Informatika, Sistem Informasi, Manajemen Informatika, DSS, AI, ES, Jaringan, sebagai wadah dalam menuangkan hasil penelitian baik secara konseptual maupun teknis yang berkaitan dengan Teknologi Informatika dan Komputer. Topik utama yang diterbitkan mencakup: 1. Teknik Informatika 2. Sistem Informasi 3. Sistem Pendukung Keputusan 4. Sistem Pakar 5. Kecerdasan Buatan 6. Manajemen Informasi 7. Data Mining 8. Big Data 9. Jaringan Komputer 10. Dan lain-lain (topik lainnya yang berhubungan dengan Teknologi Informati dan komputer)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,069 Documents
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Implementasi Teorema Bayes Untuk Diagnosa Penyakit Hawar Daun Bakteri (Kresek) Dan Penyakit Blas Tanaman Padi Purwadi Purwadi; Asyahri Hadi Nasyuha
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4350

Abstract

Rice is a plant that has an important role for the majority of the population in Indonesia. Rice plants have a fairly high carbohydrate content. Therefore, rice cultivation is very important to be maintained. The government is targeting rice yields in 2013 to reach 72.06 million tons of dry milled grains and a surplus of 10 million tons in 2015. But in fact, this has not been realized due to disease attacks on rice plants which are quite detrimental to farmers. This is due to the lack of knowledge among Indonesian farmers about the problem of rice plant diseases. Farmers often have difficulty in consulting with an expert because of the travel time to the agricultural office which is quite far. In this expert system research, the Bayes theorem calculation method determines the probability of an event based on the effects obtained through observations. The result of the analysis of this method is an expert system analysis to diagnose diseases in rice plants along with the probability value of the diagnosed disease, which shows the level of system confidence in the disease by Bayes calculation that the conclusion with the highest value of 0.574 is Blast Disease
Perbandingan Metode Moving Average dan Exponential Smoothing pada Peramalan Nilai Tukar Rupiah terhadap Dollar AS Sayyidah Jasinda Amalia; Nunik Oktaviani; Garin Indra Prameswara; Yogo Dwi Prasetyo; M Yoka Fathoni
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4493

Abstract

The currency exchange rate or known as the exchange rate is the price of one unit of foreign currency in the domestic currency or can be referred to as the currency exchange rate against current or future payments between the two currencies of each country or region. The exchange rate of a country's currency is strongly influenced by the flow of capital between countries. The Indonesian economy is heavily influenced by the international economy so that the Rupiah exchange rate is very much needed by the community in their economic life. Exchange rate data has very high volatility and tends not to be stationary. This study discusses the forecasting of the Rupiah exchange rate against the Dollar AS with two methods, namely Moving Averages and Exponential Smoothing. Accuracy analysis using Mean Absolute Deviation (MAD) and Mean Squared Error (MSE) methods. The software used in this research is the Quantitative Method (QM 5.3) software. The results of the study explain that the most appropriate forecasting method is used in analyzing the data. The Exponential Smoothing method forecasts the exchange rate of the Rupiah against the US Dollar with = 1.0 for January 1, 2022, which is Rp. 14,278 with MAD worth 29,105 and MSE worth 1564,619
Klasifikasi Data Penduduk Untuk Menerima Bantuan Pangan Non Tunai Menggunakan Algoritma Naïve Bayes Nurahman Nurahman; Muhammad Mastur Alfitri; Eddy Mashamy
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4678

Abstract

Indonesia's population reaches 273,879,750 people, and it is known that every year it is increasing, so that population movements begin to occur from island to island. The population movement is carried out by everyone with the aim of getting a job to fulfill the necessities of life. However, not all of them can be fulfilled, even though there are still people who fall into the poor category, one of which is part of the population in the village of Bapinang Hulu. In the Bapinang Hulu village there is a Non-Cash Food Aid which is used to help the poor. The Non-Cash Food Assistance Program for the poor should be carried out with the right target. To overcome this, it is necessary to analyze population data. The analysis was carried out using the Nave Bayes Algorithm by dividing the dataset into training data and testing data. Testing the data 9 times to determine the accuracy of the results of research analysis in the search for the Accuracy performance vector value. The results showed that the accuracy performance vector value reached 90.00%. So it is known that the Naive Bayes algorithm is able to analyze population data for determining Non-Cash Food Aid in the upstream bapinang village.
Analisis Peramalan Permintaan Golang-Galing dalam Memaksimalkan Manajemen Rantai Pasok Menggunakan Metode Weighted Moving Average Ajeng Nurdina; Dyah Aryani; Ella Venita; Sarah Astiti
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4551

Abstract

Forecasting the demand for golang-galing products in the Small and Medium Enterprises (SMEs) industry “Pak Liman” in Kaliori Village, Banyumas District, Banyumas Regency is planning support in production control so as to maximize supply chain management of golang-galing products. Forecasting market demand is very necessary in order to predict market opportunities for future demand for a product. Demand forecasting aims to prevent the risk of sales prediction errors that cause waste such as sales predictions that are too large which can lead to swelling in production costs and vice versa if sales predictions are too small it will result in out of stock out, so consumers need to wait a long time for sales. get the desired product. Based on these problems, an analysis of demand forecasting for golang-galing products is carried out which aims to reduce waste and maximize value for all components in the supply chain. This study uses time series analysis with the moving average method to forecast the demand for golang-galing products for the next five months. The results of the study obtained forecasting in April, May, June, July, August, September, October, November, December 2022 in sequence, namely 3,254.6; 3,254; 3,256.6; 3,254, 6; 3,254.2; 3,253.9; 2,987.3; 3,162,9; 3,156.4. From the calculation of the Mean Absolute Error (MAE) and Mean Square Error (MSE) that has been carried out, it is obtained that the calculation for MAE is 3.44 and MSE is 20.144.
Penerapan Metode Regresi Linear Pada Sistem Peringatan Dini Banjir Berbasis Internet of Things (IoT) Nugra Zurus Pratama; Tedy Rismawan; Suhardi Suhardi
JURIKOM (Jurnal Riset Komputer) Vol 9, No 5 (2022): Oktober 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i5.4849

Abstract

Flood is an event when water inundates an area that is usually not flooded for a certain period of time. Floods usually occur because of continuous rainfall and result in overflow of river. Floods can cause negative impact such as puddles of water that enter homes of those affected. Therefore, we need a system to monitor the weather and can provide flood early warning. In this study the weather monitoring system and flood early warning were made based on internet of things by applying linear regression methods. The system consists of a weather sensor node, a water level sensor node and software in the form of a website. The system measures rainfall, air temperature, humidity, and water level. The process of sending data from the sensor to the server uses ESP32 as a microcontroller which is connected to a wifi network and internet. The system will send a notification if the water level is above the normal level. Based on the test results obtained as many as 45 occurrences of rainfall. The percentage of success in predicting water levels using the linear regression method is 94,4% with an error value of 5,6%. 
Analisis Kepuasan Pengguna Terhadap Sistem E–Raport Menggunakan Metode EUCS dan Model Delone and McLean Hengky Hengky; Satrianansyah Satrianansyah
JURIKOM (Jurnal Riset Komputer) Vol 9, No 5 (2022): Oktober 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i5.4906

Abstract

The problem discussed in this study is the E-Raport System used by SMK Muhammadiyah Lubuklinggau City, since the beginning of 2017 the use has never been evaluated, measuring the performance of the satisfaction of using the application. So that it is not yet known how effectively the application can help its users, so from this problem researchers Measure User Satisfaction from the success of the E - Report System in SMK Muhammadiyah Lubuklinggau City using the EUCS method and the McLean Model. This study is about analyzing the level of satisfaction of E-Raport users at SMK Muhammadiyah Lubuklinggau. This study aims to determine the application of the system that has been used and to determine the level of satisfaction of users of the E-Raport system at SMK Muhammadiyah Lubuklinggau. This study uses 2 methods of End User Computing Satisfaction (EUCS). ) and the Delone and McLean models. The EUCS method emphasizes user satisfaction, by analyzing the system based on content, accuracy, appearance, convenience and timeliness, while the Delone and McLean Model method analyzes system user satisfaction based on System Quality, Information Quality, Service Quality. This type of research is a descriptive type using research instruments in the form of a questionnaire. With 40 respondents, the results are valid and mutually influence user satisfaction. (This study uses a measuring instrument in the form of a questionnaire distributed to 40 respondents who are teachers of SMK Muhammadiyah Lubuklinggau). From the results of the analysis that has been carried out, the following results are obtained for the validity test using the EUCS method that is valid to use, and for the validity test the Delone and Mclean model method is valid to use, for the reliability test of the two reliable methods to be used, and for the results of the T test and test F stated that the two methods mutually influence user satisfaction
Perencanaan Strategis Sistem Informasi Wisata Hutan Pinus Limpakuwus Dengan Menggunakan Metode Ward And Peppard Puji Pangestu; Resad Setyadi
JURIKOM (Jurnal Riset Komputer) Vol 9, No 5 (2022): Oktober 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i5.4932

Abstract

Planning Information Systems (IS) and Information Technology (IT) today helps an organization's success in its business. Limpakuwus pine forest nature tourism located in Baturaden Purwokerto is a tourist spot that utilizes technology, namely Electronic Ticketing manually to assist visitors in ordering tickets. Limpakuwus Baturaden pine forest tourism which is owned by the Indonesian State Forestry Public Company (PERUM PERHUTANI), the East BANYUMAS Forest Management Unit (KPH) currently does not use SI/IT optimally or comprehensively. This research has a purpose, namely to make IS/IT planning for the Limpakuwus Baturaden pine forest tourism. The method in this study uses qualitative research methods, qualitative methods are research that emphasizes in-depth understanding of a problem, qualitative research usually tends to be descriptive and uses more in-depth analysis. This research uses a strategic planning analysis of Ward And Peppard information systems, Ward And Peppard analysis is the identification of a technology or computer-based application portfolio to support organizations in implementing business plans and realizing business goals, Ward And Peppard has an input stage consisting of business environment analysis. external and internal business environment analysis. The output stage consists of business strategy, IS/IT management strategy, IT strategy and future application portfolio. The method of collecting data in this study is through interviews or interviews with the manager of the Limpakuwus Pine Forest tourist attraction. The data from this research is descriptive in the form of secondary data. The results of this study are in the form of IS/IT planning documents for Limpakuwus pine forest tourism and recommendations for IS/IT proposals for tourism objects in Baturaden Limpakuwus Pine Forest
Analisis Sentimen Opini Pengguna Twitter Terhadap Perusahaan Jasa Ekspedisi Menggunakan Algoritma Naïve Bayes Berbasis PSO Nenden Legiawati; Teguh Iman Hermanto; Yudhi Raymond Ramadhan
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4629

Abstract

Expeditions are used in the process of delivering goods or selling them remotely. Twitter has become a social media for information sharing and opinions, including those on the expeditionary services both negative and positive. The solution for the problem which occurs is that of sentiment analysis, helpful in grouping the data and predicting the tweet. The aim of the research to predict sentient tweeted data using a file classification method, naive bayes's algorithm calculated the value of the tweets of the Anteraja expedition service that had the results accuracy 87,77%, precision 76,67%, recall 52,27%. JNE with accuracy 81,48%, precision 71,43%, dan recall 62,50%. JNT with accuracy 91,46%, precision 48,15%, recall 86,67%. Shopee Express with accuracy 92,68%, precision 9,09%, recall 16,67% and Sicepat with accuracy 91,50%, presision 100,00% dan recall 38,10%. Particle Swarm Optimization (PSO) serves to increase the value of the results of the nave Bayes classification with the results of Anteraja accuracy 91,70%, precision 82,05%, recall 72,73%. JNE accuracy 93,83%, precision 88,00%, recall 91,67%. JNT accuracy 92,18%, precision 70,97%, recall 81,48%. Shopee Express accuracy 94%, precision 20,00%, recall 33,33% and Sicepat accuracy 95,42%, precision 93,75%, recall 71,43%. From the results of naïve bayes research and Particle Swarm Optimization (PSO) it can be compared that Particle Swarm Optimization (PSO) is proven to be able to increase the value of nave Bayes.
Penerapan Metode TOPSIS Pada Sistem Pendukung Keputusan Untuk Pemilihan Pegawai Teladan Fauziyah Fauziyah; Samuel Ramos
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4524

Abstract

An exemplary employee is a person who works in an office or company institution by getting a salary, but has something that can be imitated or good to emulate his actions, behavior, and so on. The problem faced in this study is in the process of selecting exemplary employees. The criteria used by the research in this study are presence, responsibility, cooperation, discipline, and initiative. In selecting exemplary employees, a Decision Support System is needed. The method used in this study is the Technicque For Order Preference By Similarity To Ideal Solution (TOPSIS) which takes into account all the criteria that support decision making to help speed up and simplify the decision-making process. The results of this study will produce a ranking order of several candidates who are appointed as exemplary employee candidates. The highest ranking exemplary employees are; Dermansyah alternate (V8), with a value of 0.6511
Process Mining using Inductive Miner Algorithm to Determine the actual Business Process Model Muhammad Wanda Wibisono; Angelina Prima Kurniati; Gede Agung Ary Wisudiawan
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4769

Abstract

At the beginning of 2019, the COVID-19 pandemic entered the country of Indonesia resulting in all learning activities being carried out online in all cities of Indonesia. Likewise, Telkom University concentrates all teaching and learning activities online using the CeLOE Learning Management System. Learning Management System is a system that helps lecturers in managing teaching and learning activities independently in educational institutions. CeLOE is a learning management system of Telkom University developed based on Moodle. In this study, we analyse the CeLOE event log using the process mining method. The goal is to find out the learning patterns of students using CeLOE during the COVID-19 pandemic. This research case study focuses on the activities of students of the Telkom University S1 Informatics study program for the first semester of 2020/2021 in using CeLOE LMS. The analysis of this study conducted a comparison of the performance of three variants of the inductive miner (IM) algorithm through conformance checking values. The results of the analysis obtained are value of conformance checking from the three variants of the inductive miner (IM) algorithm have an average fitness value of up to 1 prove that the inductive miner (IM) algorithm can make a model based on the event log well. Besides that, it has a fairly high precision value with a value range of 0.750-0.850 shows that the inductive miner (IM) makes a process model with relatively many variations of activities outside the event log and the IM process model is "overfit-ting" for all variants of the IM algorithm. Inductive miner (IM) is the best inductive miner (IM) algorithm variant with a fitness value of 1.0, precision value of 0.750, and the generalization value of this algorithm is relatively high (0.984). It is hoped that this research can contribute to the addition of new perspectives related to the implementation of process mining using inductive miner (IM) algorithm in the field of education

Page 63 of 107 | Total Record : 1069

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