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INDONESIA
JURNAL MEDIA INFORMATIKA BUDIDARMA
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma
ISSN : 26145278     EISSN : 25488368     DOI : http://dx.doi.org/10.30865/mib.v3i1.1060
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
Decission Support System, Expert System, Informatics tecnique, Information System, Cryptography, Networking, Security, Computer Science, Image Processing, Artificial Inteligence, Steganography etc (related to informatics and computer science)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 62 Documents
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Search results for , issue "Vol 5, No 4 (2021): Oktober 2021" : 62 Documents clear
Analisis Sentimen Pada Isu Vaksin Covid-19 di Indonesia dengan Metode Naive Bayes Classifier Fitria Septianingrum; Jajam Haerul Jaman; Ultach Enri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3260

Abstract

The Covid-19 pandemic that has occurred in Indonesia and even in the world has not yet ended. Various efforts have been made by the Indonesian government to minimize the spread of this virus, such as the implementation of a lockdown, Large-Scale Social Restrictions (PSBB), a ban on going home during the Eid al-Fitr holiday, and so on. One of the new policies issued by the government is the vaccination program, where the government has started implementing the program since early 2021 for the people of Indonesia, which aims to increase antibodies to avoid exposure to the Covid-19 virus. To find out opinions, comments, or feedback given by the public on this new policy, sentiment analysis can be done. The process of this sentiment analysis includes data collection, namely the crawled tweet data originating from the Twitter social media. The data is then selected for further pre-processing stage so that the data is clean and ready for classification. Furthermore, sentiment weighting is carried out for data labeling using a lexicon dictionary and negative words. Then after that, the terms or words are weighted with tf-idf and followed by the feature selection process using Information Gain. Furthermore, the classification process is carried out using the Naive Bayes Classifier algorithm to classify the data into 3 classes, namely positive, negative, and neutral sentiments. The results of this study are to produce a model accuracy rate of 78%, recall 80%, and an AUC score of 0.904.
Klasifikasi Data Malaria Menggunakan Metode Support Vector Machine Nur Ghaniaviyanto Ramadhan; Azka Khoirunnisa
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3347

Abstract

Malaria is a life-threatening disease, caused by a parasite that is transmitted to humans through the bite of an infected female Anopheles mosquito. In 2019, there were an estimated 229 million cases of malaria worldwide and the death toll reached 409,000. The area most frequently affected by malaria, according to WHO, is the African region. Malaria can be detected beforehand by using the information inpatient data and applying machine learning techniques. This study aims to detect and classify severe malaria based on the history of examining patient data using the Support Vector Machine (SVM) method with a normalization technique using min-max on the dataset and a cross-validation technique with several experiments on the K value of the results. This study also compares the Support Vector Machine method with Naïve Bayes (NB) where the accuracy of the SVM model is superior to Nave Bayes with an average accuracy gap of 25%. The accuracy generated by the application of the proposed method is 92.3%.
Analisis Aritmia (Gangguan Irama Jantung) Menerapkan Metode Certainty Factor Masyuni Hutasuhut; Tugiono Tugiono; Asyahri Hadi Nasyuha
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3289

Abstract

The heart is one of the most important organs for humans that functions to pump oxygenated blood, the heart can experience problems, one of which is arrhythmia, arrhythmia is a heart rhythm disorder or pattern of rapid changes from a normal heart rate. Heart rhythm disturbances (arrhythmias) are patterns of rapid change from the normal heart rate. This becomes a problem when not handled properly and correctly because it can cause disruption of the heart's function, even in more severe cases it can cause sudden death. An expert system is one of the artificial intelligence of humans that studies how an expert thinks in solving a problem, making decisions or drawing conclusions from a number of facts. An expert system is a system that adopts the expertise of an expert that can be used to overcome certain problems, one of which is diagnosing arrhythmias. This study applies Certainty Factor analysis which can provide additional knowledge to the public, especially knowledge on heart disease. So that arrhythmia analysis with this certainty factor method can be applied to a system that helps the general public in preventing and overcoming heart rhythm disorders
Pemetaan Tingkat Kemiskinan di Provinsi Jawa Tengah Berdasarkan Kabupaten/Kota dengan Metode K-Medoids Fitriani Dwi Ratna Sari; Sotya Partiwi Ediwijojo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3278

Abstract

Poverty describes a condition of lack of ownership and low income, or in more detail describes a condition that basic human needs cannot be fulfilled, namely food, shelter, and clothing. In the last ten years, Central Java's poverty reduction performance has had its ups and downs, with rural poverty still dominating. The purpose of this research is to conduct a mapping analysis in the form of clusters on the number of poverty levels in districts or cities in the province of Central Java using artificial intelligence techniques. Given that Central Java is the third most populous province after West Java and East Java. This needs to be done in order to obtain a macro picture of the poverty level over the last few years through regional mapping. The dataset used is sourced from the Central Java Statistics Agency (BPS) website on the subject of the number of poor people (thousands of people) in 2017-2019. The solution given in conducting mapping in the form of clusters is the K-Medoids method which is part of clustering data mining. The number of clusters used are high and low clusters in mapping the number of poverty levels. The mapping analysis process uses the help of RapidMiner software. The results showed that 6 provinces (17%) were in the high cluster and 29 provinces (83%) were in the low cluster. The final centroid values for each cluster are {293.2, 309.2, 343.5} in the high cluster (cluster_1) and {18.6, 19.4, 20.1} in the low cluster (cluster_0). The results of the mapping can be useful information for tackling the poor where the high cluster (cluster_1) is a priority for the government in the province of Central Java, namely Cilacap Regency, Banyumas Regency, Kebumen Regency, Grobogan Regency, Pemalang Regency, Brebes Regency
Optimization of Piezoelectric Sensor Based Lighting Power Management Using Fuzzy Logic Mamdani Devani Adi Permana; Rahmat Yasirandi; Dita Oktaria
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3248

Abstract

Information is a very important thing from time to time. Lighting is needed by humans to support their daily activities. The problem of the lighting sector today is energy efficiency which is still not resolved. Where the use of electricity for lighting is still using old technology that is not environmentally friendly and costs a lot of money per month. One of the concepts of IoT, namely smart lighting, emerged as a solution to overcome problems in the lighting sector. However, the current smart lighting still requires a direct power source from the government (PLN), In addition, sectors such as tourist attractions in rural areas still need to be considered because there are still many areas that do not have a power source that can be used for street lighting. the tourist attraction. So we need a smart lighting technology that can produce its own power source to reduce the electricity costs that must be incurred. This study aims to build a tool or device that can manage and optimize the energy expended by building an IoT device using a piezoelectric sensor as the main material to generate an electric field that will produce electrical energy for lighting or lighting in rural tourist destinations and using fuzzy algorithms. Mamdani logic is a determinant of the intensity of the light obtained from the light sensor on the IoT device. The overall results of the system that has been built can work properly and the Mamdani fuzzy algorithm can be used properly with an accuracy of 93% power saving at the time of testing. In addition, the monitoring system built is also following the data obtained from the system. The suitability between the fuzzy system and Matlab as a whole is in accordance with the value of 100%
E-Travel Riau Berbasis Mobile Menggunakan Metode Dijkstra Marni, Prina; Asnal, Hadi; Erlinda, Susi; Agustin, Agustin
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3261

Abstract

Travel is one of the transportation that is often used by study tours or tourism in Riau Province. Travel is not only engaged in ordering but also in the field of delivery of goods. But what often happens to travel is that bookings are still done manually. The ordering process is carried out by telephone, then the admin records the address of the passenger to be picked up and the admin immediately confirms to the driver to pick up the passenger. The purpose of this study is to assist passengers in ordering travel online and drivers can monitor and determine the location of prospective passengers. In this study, an android-based online travel booking application was created using the Dijkstra algorithm. The dijkstra algorithm is an algorithm used to solve the shortest path problem for a directed graph with non-negative edge weights. This algorithm is used by drivers to determine the fastest route in the process of picking up prospective passengers. The advantage of this Dijkstra method is that it can find the closest route from the starting point to the end point by comparing the smallest value between points that will be used as a route that will be passed by the travel driver in order to get to the destination faster. The results of this study are a travel application that makes it easier for users to book travel and makes it easier for drivers to determine the fastest route in picking up passengers
Prediksi Jumlah Penjualan Rumah di Bojongsoang ditengah Pandemi Covid-19 dengan Metode ARIMA Kurniawan, Alit Fajar; Pane, Syafrial Fachri; Awangga, Rolly Maulana
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3121

Abstract

This study aims to determine the accuracy of the ARIMA method with the Carmer matrix in forecasting or predicting the number of house sales in the Bojongsoang area which is still experiencing a period of crisis. The data used in this study is secondary data in the form of time series data on the number of house sales. In the ARIMA method, we perform stationary data, then look for autoregressive (AR), moving average (MA), and ARMA (Autoregressive and Moving Average) values. From the available data, the number of house sales has decreased, therefore forecasting is carried out using the ARIMA (1,1,1) model for future home sales to assist property developers in estimating future development projects. the results of the forecasting carried out using the ARIMA (1,1,1) method, which shows that the prediction of the number of house sales in the Bojongsoang area in the June - December period experienced a stable number of house sales
Evaluasi Pelayanan Terpadu Satu Pintu (PTSP) Menggunakan Decision Tree Anggono, Sigit Umar; Manongga, Danny; Iriani, Ade
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3073

Abstract

Various ways are carried out by each agency to win the trust of the public, among others, by increasing customer satisfaction. One of the government agencies that is committed to increasing customer satisfaction is the Regional Office of the Ministry of Religion of Central Java Province. This study aims to measure the suitability of service quality and recommend alignment of the gap between public perception and management perception which is then used as material for evaluating service quality at the Regional Office of the Ministry of Religion of Central Java Province using Decision Tree with the ID3 algorithm. Attributes of customer satisfaction input in this study using Servqual, including tangibility, reliability, responsiveness, assurance and empathy. In this study, it was found that there is a gap between the perception of service users and the perception of management. Where the improvement of service quality that must be prioritized is the assurance attribute. This research is expected to assist the management in finding the weaknesses of their services and increase customer satisfaction to maintain and increase public trust in government agencies
Analisis Risiko Teknologi Informasi Menggunakan Metode FMEA dan SAW dengan COBIT 5 Pinem, Anjar; Panjaitan, Erwin Setiawan; Andri, Andri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3275

Abstract

The use of Information Technology (IT) in a university raises various problems, one of which is the understanding of risks its use. Universitas Quality Medan was identified as having no IT risk documents. This study aims to analyze and rank risks provide recommendations for improvements. Risk assessment is carried out on 9 business processes use COBIT 5 framework in domains APO12 and EDM03, the risk level assessment uses FMEA, for rank and recommendations using SAW. The current risk management process is still level 1 with the APO12 capability value of 1.36 and to be conditions at level 2 a capability value of 2.32 a gap of 0.96. EDM03 current condition is at level 1 a capability value of 1.19, while the expected condition at level 2 a capability value of 2.11 a gap value of 0.91. The results of the identification of risk levels in the APO12 have 3 risk level processes on a scale of 6, 1 process a scale of 7, and 2 processes a scale of 8. For EDM03, have 2 risk level processes a scale of 9 and 1 process level of risk on a scale 8. Priority of risks and recommendations for APO12 is subdomains APO12.06 (Respond to Risk) the most priority to improve management process, and for EDM03 subdomains is the priority for improvement in EDM03.03 (Monitor Risk Management)
Perancangan Aplikasi Fuzzy Logic Untuk Prediksi Kasus Positif Covid-19 Menggunakan Metode Tsukamoto Vani Maharani Nasution; Graha Prakarsa
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3338

Abstract

COVID-19 is a virus that attacks the respiratory system which was first discovered in the Chinese city of Wuhan. This virus spreads very quickly and spreads throughout the world, including Indonesia. West Java is the province with the most positive cases of COVID-19, on May 4, 2020, 193 positive cases were added, and on 28 June 2020 there were 1,396 confirmed cases with an additional 18 patients. The unpredictable increase in positive cases of COVID-19 has led to the unpreparedness of officers in handling this outbreak. The West Java Provincial Health Office acknowledged the lack of Covid-19 handling facilities in 52 regional general hospitals in West Java Province to monitor positive COVID-19 patients, one of which was the lack of isolation rooms. In addition, the quality of the isolation room and personal protective equipment does not meet the standards. Predicting an increase or decrease in cases of positive COVID-19 patients needs to be done, so that there is readiness from the task force team for COVID-19 to deal with the problem of lack of facilities including isolation rooms and personal protective equipment. Fuzzy logic is one of the derivatives of artificial intelligence that is able to predict something. The research was conducted using the fuzzy logic of the Tsukamoto method through several stages including fuzzification, formation of rules, inference, and defuzzification. The results showed an error rate of 4.5% which indicated that predicting covid-19 using the fuzzy logic of the Tsukamoto method showed a high success rate

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