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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
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Implementasi Metode ANP Terhadap Sistem Pendukung Keputusan Memilih Toko Daring Terbaik Romindo Romindo; Jamaludin Jamaludin
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 4 (2019): Oktober 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v3i4.1373

Abstract

Today, online shops are in great demand by the people of Indonesia. Lazada, Shopee, Buka Lapak are a number of online stores that are quite popular in Indonesia. Students of the Ganesha Polytechnic are a small part of Indonesian people who are interested in buying at online stores. There is an increase and discussion among the Polytechnic students of Ganesha, in this case the difference is comparing which shops are the best. This debate is the purpose of this study. SuperDecisions is a decision support system which is an important requirement in the process of selecting the best online store. In the process of selecting a store, researchers also dare to use the Analytical Network Process (ANP) method as a problem modeling for complex results. The results of applying the ANP method to Shopee's decision process are the best online stores according to 3.80 Ganesha Polytechnic students, followed by Buka Lapak weighing 3.73 and Lazada with a weight of 2.47
Pencitraan Hiperspekral untuk Membedakan Asal Tanah Tumbuh Dari Tandan Buah Segar Kelapa Sawit Dina Veranita; Minarni Shiddiq; Feri Candra; Saktioto Saktioto; Mohammad Fisal Rabin
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 3 (2020): Juli 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i3.2219

Abstract

Hyperspectral imaging is a non destructive method that has been used to evaluate internal characteristics of fruits and vegetables. Plant genetics, soil characteristics, and plant management are some of key factors to define the quality of oil palm fresh fruit bunches (FFB) produced. This research was aimed to discriminate the Tenera oil palm FFBs produced by oil palm trees grown from mineral soil and peat soil using a hyperspectral imaging system which utilized a Specim V10 spektrograf. The discrimination was based on their ripeness level, mesocarp firmness, and classification using K-mean clustering. The samples consisted of 61 mineral soil FFBs and 60 peat soil FFBs with three ripeness levels as unripe, ripe, and overripe. Hyperspectral images were recorded and processed using Matlab programs. The spectral reflectance intensities showed the discrimination between both origin soils at wavelength ranges of 700 nm  900 nm. The results also showed higher reflectance intensities of peat soil FFBs than mineral soil FFBs. Correspondingly, Fruit firmness of peat soil FFBs are higher than mineral soil FFBs. Classification using K- mean clustering between reflectance intensities and fruit firmness showed significant clusters for three ripeness levels. These results will be useful for an oil palm FFB sorting machine based on spectral imaging method
Sistem Pendukung Keputusan Seleksi Bantuan Siswa Miskin Menerapkan Kombinasi Metode SAW dan ROC Andri Yunaldi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 4 (2019): Oktober 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v3i4.1511

Abstract

Decision support system (DSS) is a system that helps decision makers in this case the principal, so that the decisions produced are considered effective and appropriate to solve the problems faced. Specifically in determining the provision of assistance to poor students, the determination of the criteria is aimed at making the recipient of the assistance in accordance with the purpose of the assistance itself. In this study, the authors applied a combination of SAW and ROC methods in selecting beneficiaries. ROC (Rank Order Centroid) is a method that can produce weight values, while Simple Additive Weighting (SAW) is a method used to rank poor prospective student assistance recipients as an alternative. The results of the study are expected to contribute to the development of science, especially the principal in the selection decision for recipients of poor student assistance
Klasifikasi Argument Pada Teks dengan Menggunakan Metode Multinomial Logistic Regression Terhadap Kasus Pemindahan Ibu Kota Indonesia di Twitter Mochammad Naufal Rizaldi; Adiwijaya Adiwijaya; Said Al Faraby
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2348

Abstract

Information on moving the Indonesian capital from Jakarta to East Kalimantan certainly raises the pros and cons conveyed by the Indonesian people through the Twitter social network. However, the pros and cons comments are of course varied, accompanied or not accompanied by arguments or even completely unrelated to the topic under discussion. User limitations in filtering out that information will certainly make it difficult for the public or even the government to analyze the information contained in the tweet. Therefore, a system was built that could classify tweets automatically into three classes, namely non-arbitration, argument and unknown. The method used in this research is Multinomial Logistic Regression (MLR). MLR is a generalization method of Logistic Regression and is used to classify 3 or more classes. Before the classification process is carried out, the tweet must be preprocessed in order to make the tweet clear of all existing noise. Feature extractions used in this study include unigram, bigram and trigram. In this study, there are 12 test scenarios and comparison methods, namely Artificial Neural Network (ANN). Of all the test scenarios the best results for the MLR method are SRU with an accuracy of 41,30%, while for the ANN method namely the RU scenario with an accuracy of 45,10%.
Rancang Bangun Aplikasi Modul Pembelajaran Satwa Untuk Anak Berbasis Mobile Augmented Reality Kholid Fathoni; Yuliana Setiowati; Rozy Muhammad
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 1 (2020): Januari 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i1.1797

Abstract

Education in children is a very important part of life to achieve success in the future. Early on, children must be taught knowledge, especially related to the daily environment, including: introduction of animals. Among the characteristics of children's learning is interesting. So far, conventional learning in the form of books makes children bored, so it takes creativity or interactive learning methods, one of which is multimedia-based learning. One of the multimedia technology developed at this time is augmented reality. Mobile augmented reality based applications can be used as learning media for animal recognition for children. This interactive learning media based on Mobile Augmented Reality, called ARnimal, combines picture books and augmented reality applications. The markers contained in the picture book will be captured by the camera from the mobile device and then processed and appear animated 3D animals on the screen in realtime. By combining the real and virtual world, ARnimal can stimulate the imagination of children so that children are more enthusiastic in learning. The results of this ARnimal trial on several types of smartphones show that all ARnimal functions are running well. ARnimal was also tested on some children who were accompanied by their parents and the results of the questionnaire showed that the application was easy to use, helped with education, had similarities with real animals and had an attractive appearance.
Perancangan Alat Monitoring Pendeteksi Suara di Ruangan Bayi RS Vita Insani Berbasis Arduino Menggunakan Buzzer Handri Al Fani; Sumarno Sumarno; Jalaluddin Jalaluddin; Dedy Hartama; Indra Gunawan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 1 (2020): Januari 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i1.1750

Abstract

Mining age and technology have led to the emergence of an innovation that can help facilitate human activities, especially for parents in controlling and looking after babies. By implementing a sound monitoring system in the baby room based on the Arduino Atmega 328 microcontroller which functions to detect noise. Data from the voice sensor is processed by Arduino via a pin. So Arduino will give instructions to Buzzer to send alarm notifications
Implementasi Teorema Bayes Dalam Diagnosa Penyakit Ayam Broiler Nasyuha, Asyahri Hadi; Hafizah, Hafizah
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2366

Abstract

Broiler chickens are a type of chicken produced from the cultivation of animal husbandry technology which has a characteristic of fast growth, as a meat producer with low feed conversion and is ready to slaughter at the age of 28-45 days. Chicken health affects the benefits that will be obtained by the farmer, therefore the Expert System for diagnosing chicken disease using the Bayes Theorem method was developed to help users, especially broiler chicken breeders, in diagnosing diseases along with suggestions or recommended countermeasures. The application of the Bayes Theorem method in diagnosing disease in broilers is by entering the calculation algorithm of the Bayes Theorem method into the system, so that the expert system can perform calculations using the Bayes Theorem method and provide diagnostic results and correct solutions to the specified disease.
PENERAPAN TEOREMA BAYES DALAM MEMPREDIKSI BAYI TERLAHIR CACAT Desi Ratnasari; Nelly Astuti Hasibuan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 1, No 3 (2017): September 2017
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v1i3.523

Abstract

The development of computer-based medical systems has increased considerably today. One of the health problems that often interfere with pregnant women is that the risk of a baby born with a disability is often overlooked because most people do not understand that a baby can be born with a disability and assume that all babies have a disability after being born not before birth, but actually born babies are quite dangerous and can result in death. This study aims to build an expert-based application that can be used to make early predictions of birth defects. This expert-based application, which mimics the workings of an expert or physician in analyzing the symptoms. Type Inference engine (machine reasoning) used in the research Bayes Theorem is a theory to generate parameter estimation by combining information from samples and other information that has been available previously.
Analisis Perancangan Jaringan Fiber to The Home Area Universitas Nasional Blok IV dengan Optisystem Efan Nuari; Iskandar Fitri; Nurhayati Nurhayati
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 2 (2020): April 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i2.1984

Abstract

Researchers will be designing the access network Fiber To The Home (FTTH) on the technology of Gigabit Passive Optical Network (GPON). The location that became the case study was the National University of Block IV, where the network speed at the site was slightly reduced speed. The purpose is to get the design of an access service network that is expected to be implemented for triple play services. Starting with data collection of data. The Fiber To The Home (FTTH) network design determining device specification, layout and number of devices used and simulated using Optisystem application. Then in the analysis based on predefined parameters in the form of BER (Bit Error Rate), Link Power Budget, and Rise Time Budget that meet the optical network with the standard of PT. Telkom. The results of the BER value has fulfilled the minimum BER value specified for fiber optic is 10-9 and for parameter Q – Factor obtained value 9,32288 so that has been meets the standard because it shows values above 6
Bagian 2: Model Arsitektur Neural Network Dengan Kombinasi K-Medoids dan Backpropagation pada kasus Pandemi Covid-19 di Indonesia Windarto, Agus Perdana; Na`am, Jufriadif; Yuhandri, Yuhandri; Wanto, Anjar; Mesran, Mesran
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2505

Abstract

The aim of the research is to create a prediction model on the best neural network architecture by combining the k-medoids and backpropagation methods in the case of the COVID-19 pandemic in Indonesia. Data obtained from the Ministry of Health is sampled and processed from covid19.go.id and bnpb.go.id. The case raised was the number of the spread of the COVID-19 pandemic in Indonesia as of July 7, 2020, with 34 records. The variables used in this study are the number of positive cases (x1), the number of cases cured (x2), and the number of deaths (x3) by province. The process of data analysis uses the help of RapidMiner software. The solution provided is to combine the k-medoids and backpropagation methods. Where the k-medoids method is mapping the specified cluster. The cluster labels used are high cluster (C1 = red zone), alert cluster (C2 = yellow zone), low cluster (C3 = green zone). The results of cluster mapping are continued to the backpropagation method to predict the accuracy of the existing cluster results. By using the best architectural model 3-2-1, the accuracy value is 94.17% with learning_rate = 0.696. Cluster mapping results obtained nine provinces are in the high cluster (C1 = red zone), three provinces are in the alert cluster (C2 = yellow zone), and 22 provinces are in the low cluster (C3 = green zone). It is expected that the results of the research can provide information to the government in the form of cluster mapping of regions in Indonesia.

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