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All Journal International Journal of Artificial Intelligence Research Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Nasional Komputasi dan Teknologi Informasi J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Mantik Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Sains dan Teknologi TRIDARMA: Pengabdian Kepada Masyarakat (PkM) INFOKUM Login : Jurnal Teknologi Komputer Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurnal Pengabdian kepada Masyarakat Nusantara (JPkMN) Jurnal Sistem Informasi dan Teknologi Jaringan (SISFOTEKJAR) Jurnal Media Informatika J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Info Sains : Informatika dan Sains DISTANCE: Journal of Data Science, Technology, and Computer Science Jurnal Mandiri IT Jurnal Teknik Informatika Unika Santo Thomas (JTIUST)
Jonson Manurung
Program Studi Rekayasa Perangkat Lunak, STMIK Pelita Nusantara
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Social Sciences

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Best Cluster Optimization with Combination of K-Means Algorithm And Elbow Method Towards Rice Production Status Determination Paska Marto Hasugian; Bosker Sinaga; Jonson Manurung; Safa Ayoub Al Hashim
International Journal of Artificial Intelligence Research Vol 5, No 1 (2021): June 2021
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (71.292 KB) | DOI: 10.29099/ijair.v6i1.232

Abstract

Indonesia is the third-largest country in the world with rice production reaching 83,037,000 and became the highest production in southeast Asia spread in several provinces in Indonesia The problem found that such product has not been able to cover the needs of Indonesian people with a very high population so that in the research conducted information excavation to generate potential to the pile of data that has been described and analyzed by BPS with clustering topics. Clustering will help related parties, especially the ministry of agriculture, in determining land development priorities and can minimize the shortage of rice production nationally. Grouping process by involving the K-means algorithm to group rice production with a combination of the elbow method as part of determining the number of clusters that will be recommended with attributes supporting the area of harvest, productivity, and production. Method of researching with data cleaning activities, data integration, data transformation, and application of K-means with a combination of elbow and pattern evaluation. The results achieved based on the work description with a combination of K-Means and elbow provide cluster recommendations that are the best choice or the most optimal is iteration 2 which is the lowest rice production group with a total of 22 provinces, rice production with a medium category of 9 and production with the highest category with 3 regions
Analisis Algoritma C4.5 Dan Fuzzy Sugeno Untuk Optimasi Rule Base Fuzzy Jonson Manurung Jonson Manurung; Bosker Sinaga Bosker Sinaga; Paska Marto Hasugian Paska Marto Hasugian; Logaraj Logaraj; Sethu Ramen Sethu Ramen
Jurnal Sistem Informasi dan Ilmu Komputer Prima(JUSIKOM PRIMA) Vol. 5 No. 2 (2022): Jurnal Sistem Informasi dan Ilmu Komputer Prima (JUSIKOM Prima)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2488

Abstract

Logika fuzzy dapat mengatasi ketidakmampuan matematika konvensional untuk model sistem nonlinear. Fuzzy sugeno merupakan salah satu metode yang sering digunakan dalam logika fuzzy. Penggunaan metode sugeno dapat mengatasi masalah sistem non linear. Kelemahan dari logika fuzzy adalah meningkatnya beban komputasi yang bertambah secara eksponensial seiring dengan bertambahnya jumlah variabel dan jumlah aturan dalam logika fuzzy. Beberapa cara telah dilakukan oleh para peneliti sebelumnya untuk mengurangi beban komputasi, diantaranya dengan mengurangi sejumlah aturan dalam logika fuzzy. Mengurangi sejumlah aturan akan berdampak pada tingkat akurasi fuzzy yang berkurang. Pada penelitian ini, menggunakan algoritma C4.5 sebagai optimasi rule fuzzy. Hasil perbandingan metode fuzzy sugeno yang diintegrasikan dengan algoritma C4.5 mendapatkan hasil akurasi sebesar 88,57 %. Jumlah luaran yang awalnya 288 rule menjadi hanya 57 rule, hal tersebut menyebabkan beban komputsi berkurang. Disamping beban komputasi yang berkurang, hal tersebut berdampak pada berkurangnnya tingkat akurasi.
Pengembangan Penyandian Dalam Aplikasi Pada Kriptografi Dengan Menggunakan Metode RC6 Berbasis Web Rinaldy Chaniago; Jonson Manurung
Jurnal Sistem Informasi dan Teknologi Jaringan (SISFOTEKJAR) Vol 2 No 2 (2021): September : 2021
Publisher : Pustaka Timur Publisher

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

Abstract

Cryptography is the art of encoding to keep messages from being easy to read, or commonly called secret messages. There are two main concepts, namely encryption, and decryption. Encryption is the process by which the information sent is converted into a form that is not recognized as the initial information by using a certain algorithm. Decryption is the opposite of encryption which is changing back the disguised form into initial information. In data encoding, namely document encoding with the RC6 method, it is carried out to secure the document into a file that cannot be read by others so that the data can be said to be safe, the data will be changed in content and format so that only those who have the key can return the data into data. readable start. In the design in building the document data security encoding application, supporting applications are used, namely sublime text and the xampp database so that the application built is web-based.
Sistem Pakar Mendiagnosa Penyakit Gigi dan Mulut Menggunakan Metode Naive Bayes Erika Novianti; Jonson Manurung
Jurnal Sistem Informasi dan Teknologi Jaringan (SISFOTEKJAR) Vol 2 No 2 (2021): September : 2021
Publisher : Pustaka Timur Publisher

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

Abstract

Technological advances that are growing rapidly are very beneficial for humans in completing their work. The high cost of consulting and checking teeth or mouth makes residents reluctant to go to the doctor. Expert systems are also widely used by humans in the medical field, especially in this research. In order to facilitate the consultation, a system is needed that can predict the dental and oral diseases that he is suffering from without having to go to the doctor to consult the disease. An expert system is a system for human-to-computer knowledge, so that computers can solve problems such as those that are usually tried by experts. Experts defined here are people who have special abilities who can solve problems that ordinary people cannot solve. Research on dental and oral disease expert systems for the manufacture of this expert system used the Naive Bayes method. The decision to diagnose dental and oral disease is carried out through a consultation process between the system and the user, if the answers are entered according to applicable regulations, then the system will share the results of the diagnosis of dental and oral diseases that he suffers from. We recommend that the procedures for collecting data in conducting this research are: interviews and literature review. In making this expert system with the Naive Bayes method, it is hoped that it can help residents to identify diseases, or provide solutions to problems with their teeth and mouth without having to go to the doctor first.
Implementasi Algoritma C4.5 Untuk Menganalisis Tingkat Kepuasan Mahasiswa Terhadap Bagian Administrasi dan Keuangan. Jonson Manurung; Mina Kumari; Maya Theresia Br. Barus
Jurnal Media Informatika Vol. 2 No. 1 Desember (2020): Jurnal Media Informatika (JUMIN)
Publisher : Jurnal Media Informatika

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Abstract

Kredit tanpa agunan menjadi pilihan masayrakat untuk melakukan peminjaman terhadapa perbankan yang menyediakan layanan tersebut. PT. BPR Diori Ganda adalah perusahaan perbankan swasta daerah yang melayani simpan pinjam dan kredit tanpa agunan bagi masyarakat. Pengajuan kredit tanpa agunan harus melalui tim kreditur untuk proses analisa atribut-atribut yang mempengaruhi klasifikasi nasabah agar kredit dapat disetujui, yang kemudian hasil analisa di serahkan ke komisaris untuk persetujuan kredit. Namun bagaimana jika yang mengajukan kredit pada hari yang sama dalam jumlah yang banyak, tentu hal ini akan membuat proses analisa dan persetujuan kredit akan membutuhkan waktu yang lama. Jika diilihat dari banyaknya kebutuan masyarakat untuk mengajukan kredit tanpa agunan maka dibutuhkan aplikasi klasifikasi, guna untuk mempermudah pekerjaan tim assessor dalam proses analisa atribut-atribut yang mempengaruhi klasifikasi nasabah. Untuk mengetahui klasifikasi nasabah yang mengajukan kredit tanpa agunan menggunakan data mining dengan algoritma K-Nearest Neighbor. Hasil dari penelitan ini adalah klasifikasi nasabah bermasalah atau tidak bermasalah intuk pengajuan kredit tanpa agunan.
Sistem Pendukung Keputusan Penilaian Kinerja Pegawai RSUD Dr. Hadrianus Sinaga Dengan Menggunakan Metode Multi Factor Evaluation Process: Sistem Pendukung Keputusan Penilaian Kinerja Pegawai RSUD Dr. Hadrianus Sinaga dengan Menggunakan Metode Multi Factor Evaluation Process Kanur L. P. Situmorang; Jonson Manurung
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (279.495 KB) | DOI: 10.54367/jtiust.v6i2.1557

Abstract

Rumah Sakit Umum Daerah (RSUD) DR. Hadrianus Sinaga setiap tahunnya memberikan penghargaan kepada pegawai yang berprestasi. Dalam proses penilaian pegawai berprestasi masih secara manual dan sangat tidak efektif, sehingga dirasa kurang optimal dan memerlukan banyak waktu baik dalam menyusun laporan maupun proses memutuskan calon pegawai berprestasi. Untuk menyelesaikan persoalan tersebut, maka diperlukan suatu Sistem Pendukung Keputusan (SPK) untuk menbantu pihak rumah sakit dalam memilih pegawai yang berkualitas dan berpretasi. Dalam pengambilan keputusan, metode yang dipakai dalam SPK ini adalah Multi Factor Evalution Process (MFEP). Pada metode MFEP ini pengambilan keputusan dilakukan dengan memberikan pertimbangan subjektif dan intuitif terhadap faktor yang dianggap penting. Pertimbangan tersebut berupa pemberiaan bobot atas multifactor yang terlibat dan dianggap penting. Aplikasi yang digunakan dalam pembuatan sistem ini adalah bahasa pemprogramana PHP untuk pembuatan programnya dan MySql untuk pembuatan database. Dengan menggunakan sistem pendukung keputusan ini, pemilihan pegawai berprestasi pada RSUD DR. Hadrianus Sinaga menjadi lebih efektif dan efisien serta menutup kemungkinan terjadinya kecurangan. Dari hasil pengujian system dan hasil analisa data bahwa A8 (Sumihar Tamba) mendapat nilai tertinggi dengan Bobot Evaluasi 81 dan Paling rendah A4 (Lenni Simbolon) dengan Bobot Evaluasi 70,75
APPLICATION OF FIFO ALGORITHM (FIRST IN FIRST OUT) TO SIMULATION QUEUE Jonson Manurung
INFOKUM Vol. 7 No. 2, Juni (2019): Data Mining And Image Processing
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (834.191 KB)

Abstract

In everyday life, many activities are found. One of them is waiting in line. Queuing is a boring thing. Moreover, the arrangement of the queues is not organized and the officers do not pay attention to who is the first to queue. So it is not uncommon to cause complications and even angry. Therefore, to handle problems in the queue, the simulation is implemented using the first in first out algorithm. With this algorithm, it can help determine who will be served first. Simulation is a way that is done to apply a more realistic system estimate. In this case, the authors use the first in first out algorithm. First in first out algorithm, i.e. first in, first out. In this case who is the first to wait in line, he will be served first and finish first. In this way, it is hoped that this will help determine who will be served first.
LOYALTY ASSESSMENT OF COMPANY COSTUMER WITH CLASSIFICATION METHOD Fricles Ariwisanto Sianturi; Jonson Manurung; R.Fanry Siahaan
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (763.646 KB)

Abstract

Companies in general want the customers they have to be able to sustain forever. To make this happen is not something that is easy in the current climate of intense business competition, considering that there are rapid changes that can occur at any time, such as changes in customers, competitors and changes in broad conditions that are always dynamic. This requires policy makers to develop a strategy capable of achieving sales growth targets, increasing the company's market share. For this reason, an analysis of customer loyalty is needed. For this reason, an analysis is needed to understand and assess customer loyalty using a classification design method. With classification, information can be produced more quickly and the information presented is analytical in nature so that it is easy to use for decision making.
IMPLEMENTATION OF TF-IDF AND COSINE SIMILARITY ALGORITHMS FOR CLASSIFICATION OF DOCUMENTS BASED ON ABSTRACT SCIENTIFIC JOURNALS Paska Marto Hasugian; Jonson Manurung; Logaraz Logaraz; Uzitha Ram
INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (503.77 KB)

Abstract

Research on one of the higher education dharmas is carried out by each lecturer and is a challenge for lecturers who pay attention to produce new and useful findings. Research results will be published in journals both nationally and internationally and one of the websites published by Ristekbirn is Sinta which includes all research works in Indonesia. The problem in this research is the accumulation of data that is getting bigger and it needs to be analyzed by utilizing text mining by searching for the resources contained in the abstract document and presenting part of the information. The purpose of this study is to classify the suitability of another document so that knowledge is found. and placement in groups according to existing topics. The process of these problems is by classifying documents based on abstracts from the publication of scientific papers. Solving these problems involves two mutually supporting algorithms, namely TD-IDF with Cosine Similarity with different tasks. TF-IDF ensures the weight of each document that can be read and read with Cosine Similarity. This research uses text mining as part of the search for related patterns and documents that have been tested. For the process of calculating the test data, 1 document and 15 documents were used as training data. With the calculation of TD-IDF the weight of each document from Q, D2 to D15 is 10,946, 28,050,27,176, 39,043, 36,535, 30,696, 25,612, 12,581, 42,335, 29,661, 33,867, 31,706, 22,654, 15,450, 59,832, 42,127, The similarity of the data is tested by determining the value of k = 4 which results in similarity to the Expert System and Cryptography, while with the selection of K = 5 with the highest similarity to the expert system..
Deteksi Tepi Citra Dengan Metode Laplacian of Gaussian Dan Metode Canny Bosker Sinaga; Jonson Manurung; Monalisa Hotmauli Silalahi; Sethu Ramen
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.v5i2.401

Abstract

The research conducted is testing the accuracy of the level of similarity of the management of STMIK Pelita Nusantara. The facial images tested were 17 images and 136 tests in each method (Laplacian of Gaussian (LoG), Canny, and the combination of LoG + Canny). Tests were carried out using Matlab R2017b. From the test results, the researchers concluded that the accuracy of the highest level of similarity is the Laplacian of Gaussian method, namely images 12 and 17 with a percentage of 99.85%, then the Canny method, namely images 4 and 7 with a percentage of 99.53% and the lowest is the combination of the two methods. (LoG + Canny) namely images 6 and 13 with a percentage of 98.14%. And the highest average accuracy of the similarity window is the Laplacian of Gaussian method with a percentage of 49.91%, then the Canny method with a percentage of 38.19% and the lowest is the combination of the two methods (LoG + Canny) with a percentage of 37.81%.
Co-Authors Agus Firmansyah Agustina Simangunsong Ananda Friska Utami Bosker Sinaga Erika Novianti Evi Rianto Firdaus Situmorang Fricles Ariwisanto Sianturi Hardy Priyatno Ambarita Hengki Tamando Sihotang Hertati Ervinna Siahaan Johanes Perdamenta Sembiring John Foster Marpaung Kadin Darlianto Tinambunan Kanur L. P. Situmorang Logaraj Logaraj Logaraz Logaraz Maria Siahaan Maya Theresia Br. Barus Maya Theresia Br. Barus Mina Kumari Monalisa Hotmauli Silalahi Nera Mayana Br.Tarigan Paska Marto Hasugian Puspita Simamora R. Mahdalena Simanjorang Rinaldy Chaniago Ritha Zahara Tarigan Rizky Suhardianto Safa Ayoub Al Hashim Sethu Ramen Sethu Ramen Sethu Ramen Siahaan, R. Fanry Sri Kumala Sari Uzitha Ram Yosefo Halawa Yupiter Gulo