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Penerapan Algoritma Support Vector Machine Untuk Model Prediksi Kelulusan Mahasiswa Tepat Waktu Emy Haryatmi; Sheila Pramita Hervianti
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 2 (2021): April 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i2.3007

Abstract

A University can have many student data in their database because many students did not graduate on time. Data mining technique can be used to process student data to predict student graduation on time. Support Vector Machine (SVM) algorithm is one of data mining techniques. Objectives of this research was implementation of SVM algorithm to model the prediction of student graduation on time in private university in Indonesia. This research was conducted using CRISP-DM (Cross Industry Standard Process for Data Mining) method. There are five steps in that method such as understanding business to predict student graduation in time which is not available, data understanding by choosing the right attribute for the next step, data preparation includes cleaning the null data and transforming data into category which has been specified, modeling was used by implementing data training and data testing on SVM algorithm and evaluation to validate and measure the accuracy of the model. The result of this research shown that accuracy value of data testing was 94,4% using 90% data training and 10% data testing. This concluded SVM algorithm can be used to model the prediction of student graduation on time.
Adaptive power link adaptation on DVB-T system based on picture quality feedback Tubagus Maulana Kusuma; Randy Rahmanto; Emy Haryatmi
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (804.114 KB) | DOI: 10.11591/ijece.v9i4.pp3121-3129

Abstract

In digital television systems such as DVB-T, service provider has difficulties to observe the quality of picture reception in the viewers’ television. This is due to the unavailability of quality feedback sent from viewers’ devices to the service provider. Therefore, this research proposes link adaptation method in DVB-T system based on image quality measurement at recipient side, so that service provider may adjust the transmission power in real-time to improve the image quality. Quality metric used in this research is human perception- based no-reference image quality metric, which does not need the presence of the reference frame. The quality assessment is focused on the severeness of blocking artifact, which is the dominant artifacts in MPEG video. The numerical results have shown that power adaptation could maintain good picture quality as well as transmission power efficiency at the same time on the digital television transmission system. The proposed scheme is also suitable for other DVB system as well as various digital television system standards.
Penerapan Convolutional Neural Network Deep Learning dalam Pendeteksian Citra Biji Jagung Kering Arum TiaraSari; Emy Haryatmi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 2 (2021): April 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i2.3040

Abstract

Corn kernels detection can be implemented in industry area. This can be implemented in the selection and packaging the corn kernels before it is distributed. This technique can be implemented in the selection and packaging machine to detect corn kernels accurately. Corn kernel images was used before it is implemented in real-time. The objective of this research was corn kernel detection using Convolutional Neural Network (CNN) deep learning. This technique consists of 3 main stages, the first preprocessing or normalizing the input of corn kernels image data by wrapping and cropping, both modeling and training the system, and testing. The experiment used CNN method to classify images of dry corn kernels and to determine the accuracy value. This research used 20 dry corn kernels images as testing from 80 dry corn kernels images which used in training dataset. The accuracy of detection was dependent from the size of image and position when the image was taken. The accuracy is around 80% - 100% by using 7 convolutional layers and the average of accuracy for testing data was 0,90296. The convolutional layer which implemented in CNN has the strength to detect features in the input image.
Penerapan Algoritma Support Vector Machine Untuk Model Prediksi Kelulusan Mahasiswa Tepat Waktu Emy Haryatmi; Sheila Pramita Hervianti
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 2 (2021): April 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i2.3007

Abstract

A University can have many student data in their database because many students did not graduate on time. Data mining technique can be used to process student data to predict student graduation on time. Support Vector Machine (SVM) algorithm is one of data mining techniques. Objectives of this research was implementation of SVM algorithm to model the prediction of student graduation on time in private university in Indonesia. This research was conducted using CRISP-DM (Cross Industry Standard Process for Data Mining) method. There are five steps in that method such as understanding business to predict student graduation in time which is not available, data understanding by choosing the right attribute for the next step, data preparation includes cleaning the null data and transforming data into category which has been specified, modeling was used by implementing data training and data testing on SVM algorithm and evaluation to validate and measure the accuracy of the model. The result of this research shown that accuracy value of data testing was 94,4% using 90% data training and 10% data testing. This concluded SVM algorithm can be used to model the prediction of student graduation on time.
Implementasi Metode Moving Average Sebagai Prediksi Penjualan Perlengkapan Pertanian Pada CV. Aneka Tani Fatmi Aulia Hanum; Emy Haryatmi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.380

Abstract

CV. Aneka Tani is a shop that sells various agricultural equipment. The problems in CV. Aneka Tani are the process of recording transactions that are still done manually with a sales book and there is no sales prediction system. It causes waste of paper, human error in transactions, and bad stock management. The purpose of this research is to predict sales of agricultural equipment, applying the Moving Average algorithm to CV. Aneka Tani’s data to generate sales prediction models, and analyze predictive models. The research method used is the CRISP-DM (Cross Industry Standard Process for Data Mining) which consists of business understanding, data understanding, data preparation, modeling, evaluation, and implementation. The process of collecting data is done by conducting interviews with business owners. There were 6 products used in Moving Average method. The stable product is Dafat with MAD value is 0,9 and MSE value is 1,2. The non stabel product is Phonska with MAD value is 13,6 and MSE value is 245,7.
Implementasi Raised Cosine Filter Pada Sistem Penyiaran Televisi Digital Satelit 2 (DVB-S2) Rio Setiawan; Emy Haryatmi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 6 (2021): Desember 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i6.3442

Abstract

The development of digital video broadcasting is still continue recently and was done by many parties. One of the project regarding this research was DVB project. There was three areas in digital video broadcasting. One of them was Digital Video Broadcasting Satellite Second Generation (DVB-S2). The development of this project is not focus only in video broadcasting but also focus in applications and mutlimedia services. The objective of this research was to implement raised cosine filter in DVB-S2 using matlab simulink in order to optimize SNR and BER value. Parameters used in this project was QPSK mode and LDPC with 50 iteration. Those parameters was chosen to maintain originality of data that sent in noisy channel. The result showed that by implementing raised cosine filter could optimized BER value of the system. The higher SNR value would give the lower BER value. In static video, the best SNR value when using a filter is 0.9 dB with a BER value of 0.000004810 while for dynamic video the SNR is 0.9 with a BER value of 0.00001030.
Implementasi Raised Cosine Filter Pada Sistem Penyiaran Televisi Digital Satelit 2 (DVB-S2) Rio Setiawan; Emy Haryatmi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 6 (2021): Desember 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i6.3442

Abstract

The development of digital video broadcasting is still continue recently and was done by many parties. One of the project regarding this research was DVB project. There was three areas in digital video broadcasting. One of them was Digital Video Broadcasting Satellite Second Generation (DVB-S2). The development of this project is not focus only in video broadcasting but also focus in applications and mutlimedia services. The objective of this research was to implement raised cosine filter in DVB-S2 using matlab simulink in order to optimize SNR and BER value. Parameters used in this project was QPSK mode and LDPC with 50 iteration. Those parameters was chosen to maintain originality of data that sent in noisy channel. The result showed that by implementing raised cosine filter could optimized BER value of the system. The higher SNR value would give the lower BER value. In static video, the best SNR value when using a filter is 0.9 dB with a BER value of 0.000004810 while for dynamic video the SNR is 0.9 with a BER value of 0.00001030.
Implementasi Teknologi Blockchain Proof of Work Pada Penelusuran Supply Chain Produk Komputer Annisya; Emy Haryatmi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i3.3068

Abstract

In recent times, the supply chain has developed into a large ecosystem. Various products moving from party to party require cooperation between stakeholders in managing the data generated. The problem is that every company has its own transaction records that can be inconsistent and their storage is centralized and not integrated between companies. This makes transaction records easy to falsify. Efficient data management is needed from the producer to the store so that consumers can trust the product. Therefore, the authors designed a product tracking system using blockchain by implementing proof of work (PoW) as the consensus algorithm, SHA-3 256 as data security, Mongo database as cloud-based data storage and QR Code as the output. As a result, transaction data from producers, distributors to retail stores are stored completely in MongoDB which is a cloud-based database, then the resulting QR Code can be used to view details of producers, distributors to retail stores that sell them. The simulation and trial results show the product tracing system design is successful as expected.
Analisis Kepuasan Pengguna Aplikasi Daily Apps Berbasis Web Di Internal Divisi Digital Marketing PT. Transcosmos Indonesia dengan Metode End-User Computing Satisfaction (EUCS) Arini Islahul Nimah; Emy Haryatmi
Journal of Information System and Informatics Vol 3 No 4 (2021): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v3i4.186

Abstract

Website saat ini dimanfaatkan untuk hal manajemen internal, maupun untuk promosi ke pihak eksternal perusahaan, baik untuk mengumpulkan ataupun membagikan informasi kepada pengguna. Daily Apps adalah suatu aplikasi yang digunakan oleh karyawan Divisi Digital Marketing PT. Transcosmos Indonesia dengan tujuan merekam Daily Data, Project List, hingga menampilkan Individual Rates maupun Team / Group Rates. Masalahnya Daily Apps yang digunakan di internal divisi Digital Marketing belum pernah diulas sama sekali sehingga belum dapat diketahui kepuasan penggunanya. Tujuan penelitian ini adalah Menganalisis kuisioner kepuasan pengguna aplikasi Daily Apps menggunakan metode End User Computing Satisfaction (EUCS). Penelitian ini menggunakan metode kuantitatif, sedangkan teknik pengumpulan data menggunakan kuesioner dengan mengaplikasikan model End User Computing Satisfaction (EUCS), yang dianalisis menggunakan analisis factor. Kemudian disebarkan kepada 71 responden yang merupakan karyawan Divisi Digital Marketing PT. Transcosmos Indonesia. Hasil dari penelitian menunjukkan bahwa kepuasan pengguna berdasarkan analisis faktor yaitu pada Indikator content mempunyai pengaruh terbesar terhadap kepuasan pengguna Daily Apps di Divisi Digital Marketing PT. TCID, dengan nilai sebesar 2,908 atau > 1 maka menjadi faktor pertama, sedangkan pada indikator accuracy, timeliness,format, dan ease of use, didapatkan nilai < 1 maka dianggap faktor yang tidak mempengaruhi kepuasan pengguna.
Pemanfaatan Aplikasi Telegram dan Internet of Things Pada Pemantauan Tempat Sampah Andhika Alif Arsadi; Emy Haryatmi
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 5, No 2 (2021): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v5i2.3639

Abstract

Government implemented Standard Operating Procedure (SOP) for sanitation as main program. Trash can one of the storage which is regularly accessed by people to throw the garbage in housing area or public place such as shopping centre, train station and others. People are encouraged not to touch the trash can when they want to throw the garbage. People are supposed to wash their hand as soon as they touch the trash can. The objective of this research is to maintain the height of garbage in the trash can dan control the lid of trash can using telegram application. Bot telegram connected to microcontroller, motor servo and ultrasonic sensor was able to maintain the height of garbage and control the lid of trash can. People can use this system to throw the garbage in the trash can. Janitor also can use this system to empty the trash can before it full.