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All Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sinkron : Jurnal dan Penelitian Teknik Informatika KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Building of Informatics, Technology and Science Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) JOMLAI: Journal of Machine Learning and Artificial Intelligence Digital Transformation Technology (Digitech)

Heru Satria Tambunan, Heru Satria

AMIK Tunas Bangsa

Author-ID : 607322

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PENGENALAN POLA HIV DAN AIDS MENGGUNAKAN ALGORITMA KOHONEN PADA JARINGAN SYARAF TIRUAN BACKPROPAGATION Tambunan, Heru Satria
InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan) Vol 1, No 1 (2016): InfoTekJar
Publisher : InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (565.491 KB)

Perkembangan tekhnologi saat ini sangat berkembang pesat, sehingga sangat memudahkan untuk mengatasi berbagai masalah. Di dalam penelitian ini penulis menggunakan algoritma Kohonen pada Jaringan Syaraf Tiruan Backpropagation dalam pengenalan pola penyakit HIV dan AIDS dalamÂ mengenali pola penyakit HIV dan AIDS. Algoritma Backpropagation merupakan salah satu algoritma pembelajaranÂ yang membutuhkan pengawasan dalam proses pembelajarannya. Pada algoritma backpropagation terdapat pasangan data input dan output serta hidden layer untuk melakukan pemrosesan data Jaringan Syaraf Tiruan hingga diperoleh bobot penimbang (weight) yang diinginkan. Dalam penelitian ini, dalam pengenalan pola penyakit HIV dan AIDS. Penulis menggunakan 15 variabel datauntuk dilatih menggunakan algoritma backpropagation dimana pembobotannya secara random dan data yang kedua dilatih menggunakan algoritma backpropagation. Didalam penelitian ini mengunakan aplikasi matlab untuk melakukan pemrosesan.

SISTEM PENDUKUNG KEPUTUSAN DALAM SELEKSI PENYIAR RADIO BOSS FM 102.8 PEMATANG SIANTAR MENGGUNAKAN METODE ELECTRE Damanik, Habibah Jayanti; Parlina, Iin; Tambunan, Heru Satria; Irawan, Eka
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 1, No 1 (2017): Intelligence of Cognitive Think and Ability in Virtual Reality
Publisher : STMIK Budi Darma

Radio merupakan salah satu media dengar yang masih populer dimasyarakat sampai saat ini. Ketika persaingan semakin tinggi dalam perkembangan industri penyiaran radio dimasa sekarang ini, umumnya stasiun radio siaran akan memprioritaskan calon penyiarnya yang memiliki dedikasi dan komitmen yang tinggi terhadap dunia penyiaran radio. Penyiar radio adalah orang yang bertugas membawakan atau memandu acara di radio sekaligus menjadi ujung tombak sebuah stasiun radio dalam berkomunikasi dengan pendengar. Maka dari itu pemilihan calon penyiar sangat berpengaruh terhadap kualitas radio tersebut. Seleksi penyiar radio yang dilakukan pada Radio Boss Fm 102.8 Pematangsiantar masih bersifat konvensional dan subjektifÂ yang berdampak pada penyiar yang terpilih nantinya bukan berdasarkan dari kemampuan yang dimiliki sehingga penilaiannya menjadi kurang efektif . Untuk mengatasi masalah tersebut maka digunakan Sistem Pendukung Keputusan (SPK) dengan menggunakan metode ELECTRE. Sistem ini dibuat sebagai rekomendasi dan diharapkan dapat memudahkan Pihak radio dalam menentukan pemenang sesuai dengan kriteria yang telah mereka tentukan.

Sistem Informasi Penyaluran Beras Miskin (Raskin) Kelurahan Desa Silau Malela Kabupaten Simalungun Tambunan, Heru Satria; Sumarno, Sumarno; Gunawan, Indra
Jurnal Sistem Komputer dan Informatika (JSON) Vol 1, No 1 (2019): September 2019
Publisher : STMIK Budi Darma

Village Office Village Glare Malela Simalungun in the distribution mechanism distributing rice for the poor there are many processes of data collection using either a computer technology that uses Microsoft Exel, and conventionally sometimes encounter problems in the process of distribution transaction poor rice resulting in frequent occurrence of data redundancy and data collection which takes quite a long time. Therefore, the author wants to make the application of Information Systems Distribution of Rice Poor (Raskin) In the Village Office Village Glare Malela Simalungun using Adobe Dreamweaver CS6 application and database MySQL. System development method used is by the Waterfall method. Given this information system inputting, searching and reporting can be performed quickly and accurately because the data is stored securely and structured

Implementasi Data Mining Dalam Mengelompokkan Jumlah Produktivitas Ubi Kayu Menurut Provinsi Menggunakan Algoritma K-Means Wulandari, Sri; damanik, irfan sudahri; Irawan, Eka; Tambunan, Heru Satria; irawan, irawan
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 4, No 1 (2020): The Liberty of Thinking and Innovation
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v4i1.2727

Abstractâˆ’Cassava is one of the main foodstuffs, not only in Indonesia but also in the world. In Indonesia, cassava is the third staple food after rice and corn. The spread of cassava plants extends to all provinces in Indonesia. Using data mining is one of the ideas of information to classify the amount of cassava productivity by province, by using the k-means clustering method the amount of cassava productivity will be collected based on the year (2011-2018) of 30 provinces. K-means is a method with unsupervised classification type where the data is grouped into one or more clusters. k-means modeling the dataset into clusters where one cluster has the same characteristics and has different characteristics from other clusters. This study aims to classify the amount of cassava productivity by province. Where the highest cluster results are obtained with a total ofÂ 2 provinces, medium cluster with 4Â provinces, and a low cluster with 24 provinces.Keywords: Data Mining, K-means, Clustering, Cassava, RapidMiner Studio

Implementasi Jaringan Syaraf Tiruan Backpropagation Untuk Memprediksi Jumlah Pemasangan Instalasi Air Pada PDAM Tirtauli Sianipar, Markus Parulian; Sumarno, Sumarno; Tambunan, Heru Satria
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

In a service company, there are customers who become company consumers. One level of customer satisfaction can be measured from the level of installation of water installations to the customer's house. Therefore, the Regional Drinking Water Company (PDAM) Tirtauli Pematangsiantar needs to solve the problem in overcoming the number of water installations. Artificial Neural Network with backpropagation algorithm is used to predict the number of new water installations. The test results obtained a prediction accuracy of 89% with a 2-10-1 architecture

SISTEM PENDUKUNG KEPUTUSAN DALAM PENENTUAN PENERIMA RASTRA (BERAS SEJAHTERA) MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (STUDI KASUS DESA KARANG BANGUN) Sinaga, Dicky Hartama; Tambunan, Heru Satria; Jalaluddin, Jalaluddin
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 3, No 1 (2019): Smart Device, Mobile Computing, and Big Data Analysis
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v3i1.1691

Decision Support System (SPK) is a computer-based system that combines models and data in an effort to solve unstructured problems with user involvement through an easy-to-use user interface. This system is used to help decision making in semitructured situations and unstructured situations, where no one knows for sure how decisions should be made. Simple Additive Weighting method is one of the settlement methods for Multi attribute decision making (MADM) problems. This method evaluates several alternatives to a set of attributes or criteria, where each attribute does not depend on each other. Hope from the results of the study, the use of Simple Additive Weighting as a model of the Eligible Decision Support System for Rastra Assistance using the weighted product method in Karang Bangun Village, Siantar Subdistrict, Simalungun Regency can help the village in calculating the feasibility of rice recipients and to determine the eligibility of recipients of rice faster and more accurate. because this application is easier than the old system and the data storage is more accurate.Keywords: Decision Support Systems, Simple Additive Weighting, Rastra, Poor

Penggunaan Jaringan Sistem IPTV (Internet Protocol Television) User-Client dengan Pemanfaatan Fasilitas BOX TV, Android dan Windows Gunawan, Indra; Sumarno, Sumarno; Tambunan, Heru Satria
Building of Informatics, Technology and Science (BITS) Vol 1 No 2 (2019): December 2019
Publisher : Forum Kerjasama Pendidikan Tinggi

IPTV (Internet Protocol Television) networks are some of the types of terrestrial networks using internet facilities through a packet provided through a packet switched network infrastructure such as broadband access. The use of the IPTV system can be done through account facilities provided and provided to users, where the facilities of the accounts obtained are terrestrial facilities that can pamper users by watching premium facilities or programs that can be enjoyed. With the development of the use of the internet and bandwidth speeds that can be obtained or used by users, the use of the IPTV network system can be used optimally. The use of the IPTV system through the account provided can be utilized by using the facilities found in some TV BOX and Android. Besides being able to be used at home if using BOX TV, Android and Windows, this IPTV system can also be used outside the home with facilities provided by devices embedded with the Android and Windows operating systems. So, all types of information needed by users must be quickly and responsibly accepted immediately, so there is no limited information needed.

Effect Effect of Gradient Descent With Momentum Backpropagation Training Function in Detecting Alphabet Letters Alkhairi, Putrama; Batubara, Ela Roza; Rosnelly, Rika; Wanayaumini, W; Tambunan, Heru Satria
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.12183

The research uses the Momentum Backpropagation Neural Network method to recognize characters from a letter image. But before that, the letter image will be converted into a binary image. The binary image is then segmented to isolate the characters to be recognized. Finally, the dimension of the segmented image will be reduced using Haar Wavelet. One of the weaknesses of computer systems compared to humans is recognizing character patterns if not using supporting methods. Artificial Neural Network (ANN) is a method or concept that takes the human nervous system. In ANN, there are several methods used to train computers that are made, training is used to increase the accuracy or ability of computers to recognize patterns. One of the ANN algorithms used to train and detect an image is backpropagation. With the Artificial Neural Network (ANN) method, the algorithm can produce a system that can recognize the character pattern of handwritten letters well which can make it easier for humans to recognize patterns from letters that are difficult to read due to various error factors seen by humans. The results of the testing process using the Backpropagation algorithm reached 100% with a total of 90 trained data. The test results of the test data reached 100% of the 90 test data.

Prediction of Palm Oil Seed Stock Production Results with the Back-propagation Algorithm Damayanti, Tri Febri; Wanto, Anjar; Tambunan, Heru Satria
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 2 (2023): June
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i2.2391

Palm oil is the largest plantation export commodity in Indonesia because Indonesia has a soil structure that is suitable for planting oil palms. As is the case with the production of oil palm seed stock, of course, it does not always increase, and the production of oil palm seed stock will undoubtedly decrease. Therefore, an algorithm is needed to predict it so that the company can find out the future development of oil palm seed stock production using the Back-propagation algorithm. The Back-propagation Algorithm is used to predict the yield of oil palm seed stock production using data from the Marihat unit Oil Palm Research Center (PPKS) in 2019-2022. The Back-propagation Algorithm is an algorithm that reduces the error rate by adjusting the weights based on the desired output and target, as well as Testing the Back-propagation algorithm using Matlab. Based on the test results of the five architectural models used, one best architectural model was obtained, namely 2-14-1, using the Back-propagation method, which produced an MSE value of 0.0551030 with a Training time of 08:00 seconds with a test accuracy of 75%. Based on the research results obtained, it is expected to be input, suggestions, and efforts, especially for the Marihat Unit PPKS company, increase the stock of oil palm production seeds in each period to increase company profits more optimally.

Analisis Metode C4.5 Dalam Mengukur Akurasi Kepuasan Mahasiswa/i Terhadap Layanan Perpustakaan Damanik, Abdi Rahim; Gunawan, Indra; Sormin, Rizky Khairunnisa; Tambunan, Heru Satria; Sumarno, Sumarno; Darma, Surya
Digital Transformation Technology Vol. 4 No. 1 (2024): Periode Maret 2024
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v4i1.4498

Penelitian ini bertujuan untuk menganalisis akurasi model prediksi kepuasan mahasiswa/i terhadap layanan perpustakaan STIKOM Tunas Bangsa menggunakan metode C4.5. Layanan perpustakaan yang berkualitas merupakan faktor penting dalam menunjang keberhasilan akademik mahasiswa/i. Penelitian ini bertujuan untuk menganalisis tingkat kepuasan mahasiswa/i terhadap layanan perpustakaan menggunakan metode C4.5, sebuah algoritma pohon keputusan yang populer untuk klasifikasi. Dengan pendekatan ini, diharapkan dapat diukur tingkat akurasi kepuasan dan mengidentifikasi faktor-faktor utama yang memengaruhinya, sehingga perpustakaan dapat meningkatkan kualitas layanan sesuai dengan kebutuhan pengguna.i. Data yang digunakan dalam penelitian ini diambil dari survei kepuasan mahasiswa/i terhadap berbagai aspek layanan perpustakaan, seperti ketersediaan koleksi, fasilitas, pelayanan staf, dan kenyamanan ruang baca. Data tersebut kemudian diolah dan dianalisis menggunakan metode C4.5 untuk membangun model prediksi. Hasil analisis menunjukkan bahwa metode C4.5 mampu memberikan akurasi yang cukup tinggi dalam mengukur kepuasan mahasiswa/i, dengan tingkat akurasi yang dihasilkan mencapai persentase yang signifikan. Penelitian ini memberikan kontribusi penting dalam pengembangan model prediksi kepuasan mahasiswa/i yang dapat digunakan sebagai acuan dalam meningkatkan kualitas layanan perpustakaan di STIKOM Tunas Bangsa.

Co-Authors Achmad Noerkhaerin Putra Alkhairi, Putrama Batubara, Ela Roza Damanik, Abdi Rahim Damanik, Habibah Jayanti Damayanti, Tri Febri Dedi Handoko Eka Irawan Indra Gunawan Irawan Irawan Irfan Sudahri Damanik Jalaluddin Jalaluddin Jaya Tata Hardinata Kirana, Ika Okta MARIA BINTANG Parlina, Iin Rika Rosnelly, Rika Rizky Khairunnisa Sormin Sianipar, Markus Parulian Sinaga, Dicky Hartama Sri Wulandari Sumarno . Surya Darma Veithzal Rivai Zainal Wanayaumini, W Wanto, Anjar

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