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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 1,182 Documents
 88   89   90   91   92 
Analisis Perbandingan Teorema Bayes dan Case Based Reasoning Dalam Diagnosis Penyakit Myasthenia Gravis Bagas Triaji; Azanuddin Azanuddin; Ibnu Rusydi; Ita Mariami; Asyahri Hadi Nasyuha
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6436

Abstract

The medical industry faces several obstacles due to illness. Treatment of any condition, including myasthenia gravis, relies heavily on an accurate and precise diagnosis. Myasthenia gravis is an autoimmune disease that affects the neuromuscular junction and is characterized by sudden muscle weakness and fatigue due to the loss of acetylcholine receptors (AChRs) at the neuromuscular junction. Successful treatment planning and providing a good prognosis to the patient is highly dependent on accurate and rapid diagnosis. To diagnose Myasthenia Gravis, this study compares and contrasts Case Anthology with Bayes' Theorem. The neuromuscular condition called myasthenia gravis is characterized by a variable decrease in muscle strength. Correct and timely diagnosis is essential to start a successful course of therapy. Data from patients with Myasthenia Gravis symptoms and clinical indicators were collected for this study. To obtain an accurate diagnosis, the dataset was analyzed using Bayes' Theorem and Case Anthology techniques. Based on the current symptoms, Bayes' Theorem is used to estimate the probability of the condition, while Anthology of Cases is used to diagnose the patient. Based on symptoms, Bayes' Theorem predicts disease outcome probabilistically, but requires reliable initial assumptions and is susceptible to prior probabilities. On the other hand, Case Anthologies use information obtained from previous situations, but may be limited by the availability of relevant data and may experience difficulties in dealing with unique or unusual situations. This study helps us understand the benefits and limitations of each technique in diagnosing Myasthenia Gravis. A more accurate and effective diagnosis can be made by combining the two methods. These studies can serve as a foundation for creating more sophisticated diagnostic techniques integrated into clinical practice. The following is a summary of the percentages obtained using the Bayes Theorem and Case Anthology methods: For the diagnosis of Myasthenia Gravis, the Bayes Theorem technique produces a percentage value of 55% while the Case Anthology method only produces a percentage value of 26%. Therefore, the Bayes Theorem technique is better and more reliable in diagnosing Myasthenia Gravis.
Perancangan Keamanan Pengguna Cardless dari Ancaman Cyber Crime Menggunakan Kriptografi Curva Elliptic Nevy Bella Samantha; Senie Destya; Wahid Miftahul Ashari
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6827

Abstract

In this era, technology has discovered new innovations by creating practical ways of making transactions. Cash withdrawal transactions are now much easier because a new way has been discovered, where people can make transactions without using a card. This is certainly very useful for people whose wallets are often left behind. This ease of carrying out transactions is called Cardless. Cardless itself is a cardless cash withdrawal service that offers a fast and time-saving transaction process. Apart from that, cardless cards also have several advantages, including ATM cards being safer from the risk of being swallowed or left behind by the ATM, and avoiding the risk of fraud. Like technology in general created by humans, cardless certainly also has disadvantages. This transaction has the potential for identity theft, uncontrolled spending, system compromise, and not everyone uses cardless cash withdrawal transactions due to lack of socialization of the use of cardless transactions. In this research, the researcher wants to recommend designing additional security in the m-banking application. Different from previous research, this time the researcher used the Elliptic Curve method. The subjects of this research are cardless users. The goal to be achieved in this research is that the security of the m-banking application when using cardless transactions becomes safer because the calculation of the algorithm has been added to randomize or encrypt the PIN. The function of encrypting the PIN itself is aimed at making it more difficult for criminals to successfully carry out crimes. . If the level of security is not added as recommended by the author, the bank will have to think of other ways to increase security when carrying out cardless transactions because then more customers or users will become victims. From the encryption results in this research, the PIN was previously 312143, after the encryption process was carried out, the PIN changed to DUDSDTDSDVDU. Of course, in the future technology will continue to develop and perhaps even bigger flaws will be created, but up to now Elliptic Curve cryptography is still cryptography that is difficult to solve. With so little chance that cybercrime perpetrators can break in.
Penerapan Metode CRISP-DM untuk Optimalisasi Strategi Pemasaran STP (Segmenting, Targeting, Positioning) Layanan Akomodasi Hotel, Homestay, dan Resort Yerik Afrianto Singgalen
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6896

Abstract

The challenge in maintaining the business continuity of hotel, homestay, and resort accommodation services is the use of technology and marketing methods that are effective and efficient. This study aims to apply the Cross Industry Standard Process for Data Mining (CRISP-DM) method to optimize hotel, homestay, and resort marketing strategies. This research uses case studies on hotel, homestay, and resort accommodation services based on the context of the service provider's business operational area in North Toraja Regency, South Sulawesi Province. The results of this study show that TF-IDF results and sentiment extracts can be utilized for segmenting and targeting processes. Based on the results of TF-IDF, it is known that the main emphasis of hotel, homestay, or resort guests (Toraja Herigate, Toraja Misiliana, Rosaliana Homestay, Hotel Pison, and Luta Resort Toraja) with business operational areas in Rantepao sub-district, North Toraja Regency, South Sulawesi Province, is as follows: staff (97), Rantepao (98), clean (108), breakfast (139), nice (147), rooms (165), toraja (177), good (189),  room (268), hotel (331). In addition, modeling results using the SVM algorithm with SMOTE operators can be used in positioning strategies to improve the competitiveness of accommodation services based on business operational areas. Specifically, the performance of the SVM algorithm using SMOTE operators resulted in an accuracy value of 97.64%, a precision value of 100%, a recall value of 95.37%, an f-measure value of 97.56%, an AUC value of 100%). Compared to the DT algorithm, the performance of SVM algorithms using SMOTE operators has better performance in the classification of review data. Thus, the CRISP-DM method is able to optimize the marketing strategy of hotels, homestays, and resorts.
Penerapan Metode TOPSIS Sebagai Pendukung Keputusan Pemilihan Layanan Akomodasi di Destinasi Wisata Pulau Yerik Afrianto Singgalen
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6530

Abstract

The selection of accommodation services in a tourist destination can be adjusted to the preferences of tourists. This study aims to recommend the TOPSIS method as a decision support system in the selection of accommodation services in tourist destinations, based on case studies of Morotai Island tourist destinations. The application of the TOPSIS method as decision support for the selection of accommodation services in Morotai Island tourist destinations consists of four stages as follows: the stage of making a normalized matrix, weighted normalized matrix manufacturing stage; steps determine the matrix of positive and negative ideal solutions; The step determines the preference value for each alternative. The criteria set are as follows: room price as a cost with an importance weight of 5; distance of the hotel to the destination as a benefit with an importance weight of 3; room type/class as a benefit with an importance weight of 4; hotel amenities as a benefit with an importance weight of 4; Service rating as a benefit with importance weight 4. Specifically, the accommodation service providers focused on are Daloha Resort; Metita Beach and Dive Resort; Moro Ma Doto; Molokai by Sahid Hotel; and Ria Hotel. The results of this study showed that the alternative with the highest preference value was Metita Beach and Dive Resort, with a value of 0.764348724, then Molokai by Sahid Hotel, with a value of 0.626002478. In addition, Daloha Resort has a value of 0.616994938, and Ria Hotel has a value of 0.61630669. Also, Moro Ma Doto has a value of 0.363441753. This suggests that travelers prioritizing price as the dominant factor with weight critical (5) will choose Metita Beach and Dive Resort. If the importance weight of each criterion is changed according to the traveler's perspective, the system will recommend different accommodation services. Thus, tourists can use the TOPSIS method in choosing accommodation services and give importance weight according to individual preferences. Therefore, the TOPSIS method can be used in selecting accommodation services in various tourist destinations.
Expert System for Pineapple Fruit Diseases Using Bayes' Theorem Ade Pujianto; Raditya Wardhana; Acihmah Sidauruk; Ria Andriani
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6432

Abstract

Expert systems are a branch of artificial intelligence that utilizes specialized knowledge to solve problems at the level of an expert. In the field of agriculture, expert systems are used for diagnosing plant diseases. In this research, an expert system was designed and developed with the aim of assisting pineapple farmers in determining the diagnosis of diseases based on the main symptoms observed in the plants. To overcome knowledge uncertainty, the Bayesian probability method was employed in this expert system. The diagnostic process begins with a consultation session, where the system asks relevant questions to the farmers based on the observed symptoms in the pineapple plants. The ultimate outcome of this study is an expert system capable of diagnosing diseases in pineapple plants and providing effective solutions with an accuracy rate of 93.34%. Additionally, the system provides probability values for each diagnosed disease, indicating the system's confidence level in the identified diseases, and offers treatment recommendations or solutions to the pineapple farmers.
Penerapan dan Pemantauan Pakan Ikan Lele Otomatis Menggunakan Keypad Shield Berbasis IoT Muhamad Ariandi; Imam Karua
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6807

Abstract

Cultivating freshwater fish is a promising business in the long term. One type of freshwater fish that is widely cultivated by people is catfish. Catfish is a type of freshwater fish that does not require a lot of care, so it is very profitable and has high economic value. The problem that often occurs in catfish farming is that when feeding fish, farmers are often late in providing fish food, which causes catfish to die and experience cannibalism or eat other species. Based on the problems that occurred, research was carried out at Agrowisata Tekno 44 which aimed to implement an automatic catfish feeding device through the Internet of Things (IoT) based Blynk system which can be controlled using an LCD Keypad Shield which can provide a warning if the feed approaches a predetermined minimum limit. Addition of Mega+Wifi R3 Atmega 2560+ESP 8266 which functions as a link between the automatic fish feed and the Blynk application. The research method used in writing this article is a literature study by comparing the results of ultrasonic sensor measurements with a measuring tool in the form of a vernier caliper, and an interview method with cultivators to obtain information about feeding. Scheduled measurements at a specified time to obtain maximum results, an ultrasonic sensor was added to the fish feed container which functions to determine the contents of the volume of the RTC fish feed container which is used to store time information from the automatic fish feed tool, Push Button to measure the amount feed, the servo motor is used to open and close the fish food container that will exit into the fish pond. Testing the ultrasonic sensor with a vernier caliper to measure the distance that detects fish food in the fish food container produces a measurement ratio with a difference of 0.1 from the comparison between the measurements of the ultrasonic sensor and the vernier caliper. The results of testing carried out for 7 days with automatic fish feeding running according to a predetermined schedule, namely 06.00 and 18.00 with a success rate of 100% accuracy. And the success of the feed weight was 95.6% with an average accuracy of 96%, meaning that the fish did not lack food due to the lack of feed received.
Optimalisasi JST dalam Memprediksi Kunjungan Wisatawan Mancanegara Untuk Perencanaan dan Pengembangan Pariwisata yang Efektif Riki Winanjaya; Harly Okprana
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6739

Abstract

Foreign tourist predictions assist the government and stakeholders in planning long- and short-term tourism strategies. Accurate information on the estimated number of tourists enables appropriate infrastructure development, efficient budget allocation and setting of relevant policies. Foreign tourists discussed in this study are foreign tourists based in ASEAN countries. This research will utilize historical data on foreign tourist arrivals from the Ministry of Tourism, the Ministry of Law and Human Rights (Directorate General of Immigration) and Mobile Positioning Data. The data that has been obtained will be processed and filtered to obtain relevant and accurate data before being used as input in the creation of an Artificial Neural Network (ANN) model. The algorithm proposed in this study is the Cyclical Rule algorithm with the optimization of the Bayesian Regulation algorithm, which can be used to solve data prediction problems. This study was analyzed using 10 (ten) architectural models, including 4-4-1, 4-5-1, 4-8-1, 4-10-1, 4-12-1, 4-15-1, 4-16-1, 4-20-1, 4-24-1, and 4-25-1. Based on the analysis, the results obtained from the 4-10-1 model with the optimization of the Bayesian Regulation algorithm as the best model with the smallest testing MSE compared to the other models, equal to 0.00786961. Based on the prediction results, foreign tourist arrivals from ASEAN countries in 2023 are expected to decrease compared to 2022. Tourism actors can take advantage of the results of this prediction to improve the quality and quantity of services provided to tourists, as well as adjust the needs of tourists with the resources available at tourist destinations.
Perbandingan Metode ARIMA Box-Jenkins dengan Moving Avarage Untuk Peramalan Harga Emas Desmi Roma Putra Lubis; Ilka Zufria
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6897

Abstract

Gold is a type of investment that is starting to be popular with many people. Gold price forecasting has an important role for investors and business people in making smart investment decisions. The problem in this research is displaying the price of gold in the market which influences many factors, for example global supply and demand, fluctuating exchange rates, the global situation, and the US dollar exchange rate. And another problem that can be taken up is forecasting gold prices which change from time to time which results in potential losses for investor trading in terms of profit risk in the market. Therefore, it is necessary to create a system that can determine gold price forecasts for investors in the market. uses the Box-Jenkins ARIMA comparison method with precise Moving Average and careful analysis to forecast gold prices. The comparison method is used to determine the trend pattern of the series and provide accurate data, namely the ARIMA Box-Jenkins method, while the Moving Average method determines the movement of the average value to estimate the next value. By calculating the prediction results of the Moving Average and ARIMA, then comparing the accuracy values of ARIMA and Moving Average, we get the accuracy value of ARIMA, namely 98.74% and Moving Average, namely 97.73%. It is known that the difference is not too different, but ARIMA gets the highest accuracy. The role of the application was carried out by conducting research at the H. ST Gold Shop. Martua by collecting gold price data, after the collected data is calculated for coding then entered into an application that has been built using the Moving Average and ARIMA methods.
Performa Metode Convolutional Neural Network Pada Face Landmark Untuk Virtual Make Up Try On Dameethia Angeline; Erico Jochsen; Dyah Erny Herwindiati; Janson Hendryli
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6619

Abstract

Make up or facial makeup, is an activity to change the appearance from its original form with the help of make up materials and tools. Make-up tools are beauty tools that are commonly used by most women to beautify the appearance of their faces with many shade choices. The shade on the make-up tool is the color usually used in make-up. Examples of make-up tools that are most often used include eyeshadow, blush on, and lipstick. These make-up tools are sold widely online and offline in physical stores. However, usually a tester is also needed so that those who want to buy can try the shade that suits them. When buying online, they often find it difficult to choose the right shade, while testers in physical stores are sometimes considered less hygienic because they have been used by many people. The aim of this paper is to measure the performance of the Convolutional Neural Network (CNN) method using the ResNet-50 architecture on facial landmarks for creating virtual make up try ons which can be an alternative to this problem. The facial image data source used is from the Kaggle site called Facial Keypoints Detection. The testing process produces 78.99% accuracy while the training process produces 95.12% accuracy. The evaluation results of this model use Root Mean Squared Error (RMSE) of 2.2577 and Mean Absolute Error (MAE) of 1.5389.
Penerapan Case Base Reasoning Pada Sistem Pakar Aspek Perkembangan Berdasarkan Standar Tingkat Pencapaian Perkembangan Anak Nazwa Wanda Tazkiya; Wahyu Tisno Atmojo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6312

Abstract

Every child will develop in every aspect of development. But every child will experience different development in every aspect of their development. Many parents are less aware of the importance of early childhood development and pay less attention to child development in every aspect of development. The importance of aspects of child development at the age of 5-6 years where this age will be a provision for children in entering the next level such as elementary school. Efforts to overcome this problem with the development of expert systems become effective solutions. The expert system helps parents to make it easier to determine the more dominant aspects of development in children aged 5-6 years. In this expert system research, applying the Case Base Reasoning method is used to match new cases with previous cases that have been solved stored in the case base. Thus, it is expected that parents' awareness and attention to child development will increase so that parents can provide support and learning that is more optimal and in accordance with children's needs. Results obtained for more dominant aspects in the development of children aged 5-6 years based on indicators Standar Tingkat Pencapaian Perkembangan Anak (STPPA) RA which has been determined by the Decree of the Director General of Islamic Education No. 3331 of 2021 with 6 aspects of child development such as religious and moral values, physical motor, cognitive, language, social-emotional and art, test results were obtained using the case base reasoning method against expert analysis with 5 test data getting 4 accurate test data and 1 inaccurate test data so as to get an accuracy of 80%.

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