Article Per Year (5 Year)
p-Index From 2020 - 2025
8.741
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi JOURNAL OF APPLIED INFORMATICS AND COMPUTING IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan MEANS (Media Informasi Analisa dan Sistem) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer Bulletin of Information Technology (BIT) BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer BEES: Bulletin of Electrical and Electronics Engineering Journal of Artificial Intelligence and Engineering Applications (JAIEA) JOMLAI: Journal of Machine Learning and Artificial Intelligence Jurnal Teknik Mesin, Industri, Elektro dan Informatika Journal of Informatics, Electrical and Electronics Engineering Infolitika Journal of Data Science Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Irfan Sudahri Damanik
STIKOM Tunas Bangsa
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

Published : 73 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 73 Documents
Search

 4   5   6   7   8 
Penerapan Jaringan Saraf Tiruan Backprogation Dalam Memprediksi Jumlah Pasien Rumah Sakit Dea Dwi Rizki Tampubolon; Irfan Sudahri Damanik; Harly Okprana
Journal of Informatics, Electrical and Electronics Engineering Vol. 1 No. 2 (2021): Desember 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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

Abstract

Artificial Neural Network is one of the artificial representations of the human brain that always tries to simulate the learning process in the human brain. Artificial Neural Network (ANN) is defined as an information processing system that has characteristics similar to human neural networks. ANN is an information processing system that has similar characteristics to a biological neural network. The hospital is an integral part of a social and health organization with the function of providing services, healing disease and preventing disease to the community. Backpropagation network is one of the algorithms that are often used in solving problems. complicated problem. This algorithm is also used in regulatory applications because the training process is based on a simple relationship. The problems that occur at the Djasemen Saragih Pematangsiantar Hospital are the lack of doctors working at the hospital so that there is a density of patients that occur every year, and the absence of patient rooms that are placed at home. ill when there was an increase that was not recognized by the hospital. With the data available every year, it is expected that the use of artificial neural networks using the backprogation method is very useful for the hospital in determining the prediction of the number of hospital patients for the next year can be used as the basic material for changes or additional patient rooms when there is an excess of predicted patients.
Decision Support System for Giving PDAM Tirtauli Pematangsiantar Employee Bonuses Using the Weighted Product (WP) Method Mira Ariffiani; Irfan Sudahri Damanik; Zulia Almaida Siregar
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.346

Abstract

Employee Bonuses at PDAM Tirtauli Pematangsiantar are given to employees who are selected as employees of the workforce who perform their work in accordance with the profession through the selection process. The process of judgment and decision-making in selection is usually subjective when there are some recipients of employee bonuses who have not much different abilities. Applications created in this research in the form of Decision Support System Employee Bonus Employee PDAM Tirtauli Pematangsiantar Using Weighted Product Method. This application is used to assist the selection in conducting assessments of the competency of the recipients of employee bonus giving and recommendation in decision making. The assessment criteria used include other Attendance, Number of Children, Length of Work, Responsibility, and Loyalty. Weighted Product method is a method of completion by using multiplication to associate attribute values, where the value must be raised first with the attribute weights in question. The system is built using WEB and MySQL programming language for data processing. The result of the research is the application of the recipient of the employee bonus giving to facilitate the process of selecting the recipients of the employee bonus giving according to the need.
Community Temporary Direct Assistance (BLSM) Decision Support System with the Profile Matching Method Mita Ariffiani; Irfan Sudahri Damanik; Ika Okta Kirana; Primatua Sitompul
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1033

Abstract

Community Temporary Direct Assistance (BLSM) is a Government Program. The process of assessing and making decisions in BLSM is usually subjective, especially if there are prospective BLSM recipients who have criteria that are not much different. The application made in this study is a Decision Support System for Community Temporary Direct Assistance (BLSM) in the Panguluh Nagori Gunung Bayu Office with the Profile Matching method. This application is used to assist in assessing the competence of prospective BLSM recipients and providing recommendations in decision making. The assessment criteria used include aspects of the condition of the house and economic aspects. This Profile Matching method will compare participant profiles with the ideal profile of prospective BLSM recipients. The smaller the gap, the greater the chance to pass the assessment. This system was built using the WEB programming language and MySQL as the database. It is hoped that the decision support system for receiving community temporary direct assistance (BLSM) at the Panguluh Nagori Gunung Bayu Office can assist the Village Head in determining potential beneficiaries who are entitled to be recommended for BLSM with a process of multi-criteria weighting and assessment that is faster, more accurate and more effective.
Analisis Kepuasan Konsumen Terhadap Pelayanan Bengkel Menggunakan Metode Algoritma C4.5 Ridho Hayati Alawiah; S Saifullah; Irfan Sudahri Damanik
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 1 (2021): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i1.55

Abstract

Consumer satisfaction is one thing that is very important is assessing the level of service provided by the workshop to its consumers. The purpose of this study was to determine the quality of serviceto consumer satisfaction Zul Keluarga jaya workshop Pematangsiantar in terms of reliability, Responsiveness, Assurance, Emphaty, Tangibles to consumers Zul Keluarga Jaya workshop Pematangsiantar. In the Zul keluarga Jaya workshop Pematangsiantar the five aspects have not been measured with certainty, so the Zul Keluarga Jaya workshop Pematangsiantar found it difficult to determine which aspects should be improved. By using the C4.5 algorithm, the authors try to measure these five aspects so that a decision tree is formed. After doing a manual calculation, then the proof is done using Rapidminer software. Testing conducted with RapidMiner software using the apply model % performance. From the results of calculation using the C4.5 algorithm produced twelve (12) rule rules of the target to be achieved namely six (6) satisfied decisions and six (6) dissatisfied decisions, and the results of lesting with RapidMiner software resulted in an inspiration rate of 94,00%.
Penerapan Metode TOPSIS Dalam Penilaian Mutu Kinerja Pegawai (Application Of Topsis Method In Employee Equality Assessment) Sumantri Sihombing; Irfan Sudahri Damanik; Ilham Syahputra Saragih
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 1 (2021): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i1.57

Abstract

Quality human resources (HR) can increase profits and performance that achieve targets and goals. In an organization or company one of the most influential things is employee (HR). Therefore we need a way or oversight body to assess the quality of employees in the organization while reducing the subjective assessment of employee performance quality. Employee quality assessment certainly has many assessment criteria with different priorities - so we need a method that can take into account these criteria. One method for solving multi-criteria problems is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). TOPSIS is a way of making decisions by finding the best choice among alternatives - alternatives by calculating the proximity of alternatives with the value of an ideal solution. The study was conducted by calculating the criterion points of tupoksi and daily discipline so that it is easier to assess employee quality. The final results obtained in the form of an alternative proximity value sequence with the value of the ideal solution. from the test it can be concluded that there is an ease in making more objective decisions.
Sistem Pendukung Keputusan Menentukan Benih Padi Terbaik Menggunakan Metode TOPSIS Rahel Nita Trides Siahaan; Irfan Sudahri Damanik; M. Fauzan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 1 (2021): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i1.53

Abstract

Farmers are engaged in agriculture in a way to manage land to grow and maintain plants, farmers play an important role in Indonesia. The majority of the population is the majority of farmers and is very dependent on rice. But there are some communities that are very difficult to determine which rice seeds are good and quality to be replanted. The best rice seeds are factors that influence the business productivity of farmers. Most of the farmers have not fully understood the various types of rice seeds and are still looking for solutions to choose quality rice seeds, of course. To use these problems a Decision Support System is needed which is expected to solve these problems. The author chooses the TOPSIS method which will provide information while helping farmers in making decisions about the rice seeds they will use. By applying the TOPSIS Method can produce the right decision to choose the best rice seeds.
PEMETAAN HASIL PRODUKSI BUAH-BUAHAN DENGAN TEKNIK DATA MINING K-MEDOIDS Ira Audita; Irfan Sudahri Damanik; EKA IRAWAN
Jurnal Teknik Mesin, Industri, Elektro dan Informatika Vol. 1 No. 3 (2022): September : JURNAL TEKNIK MESIN, INDUSTRI, ELEKTRO DAN INFORMATIKA
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1102.947 KB) | DOI: 10.55606/jtmei.v1i3.535

Abstract

Buah-buahan merupakan salah satu komoditas hortikultura yang memegang peranan penting bagi pembangunan pertanian di Indonesia. Secara garis besar, produksi buah-buahan di Provinsi Sumatera Utara selama periode 2018-2020 mengalami penurunan. Penurunan jumlah produksi buah-buahan dapat mengakibatkan harga buah menjadi mahal, dan stok buah-buahan menjadi langkah. Penelitian ini bertujuan untuk mengetahui hasil dari pengelompokkan tanaman buah-buahan menggunakan metode K-Medoids yang merupakan bagian dari Data Mining. Metode K-Medoids ini merupakan metode clustering yang dapat memecahkan dataset menjadi beberapa kelompok. Pada penelitian ini data yang digunakan bersumber dari Badan Pusat Statistik pada tahun 2017-2021. Hasil dari penelitian ini diperoleh sebanyak 21 komoditas yang tergolong cluster rendah dan 2 komoditas yang tergolong dalam cluster tinggi. Penelitian ini diharapkan dapat Membantu Pihak Dinas Pertanian Provinsi Sumatera Utara dalam mengupayakan meningkatkan hasil produksi tanaman buah-buahan yang ada di Provinsi Sumatera Utara.
Algoritma K-Means untuk Pengelompokkan Dokumen Akta Kelahiran pada Tiap Kecamatan di Kabupaten Simalungun Napitupulu, Flora Sabarina; Damanik, Irfan Sudahri; Saragih, Ilham Syahputra; Wanto, Anjar
Building of Informatics, Technology and Science (BITS) Vol 2 No 1 (2020): June 2020
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (403.352 KB) | DOI: 10.47065/bits.v2i1.323

Abstract

A birth certificate is a document that must be owned by a citizen. This document contains information about the birth of a person and is an official record of proof of state recognition of the person's existence. The purpose of this study is to group birth certificate documents in each district in Simalungun Regency. The research data was obtained from the Population and Civil Registry Office of Simalungun Regency. The grouping algorithm used is the K-means algorithm which is one of the Data Mining algorithms that is good for the case of grouping. By using this algorithm the data that has been obtained can be grouped into several clusters, where the application of the K-Means Clustering process uses the RapidMiner tool. Data is divided into 3 groups: high (C1), medium (C2) and low (C3). The results obtained from this study are in December entered into a high level cluster (C1), in August, September and October entered into a medium cluster (C2), and in January, February, March, April, May, June, July and November entered into the low cluster (C3).
Pengelompokan Algoritma K-Means dan K-Medoid Berdasarkan Lokasi Daerah Rawan Bencana di Indonesia dengan Optimasi Elbow, DBI, dan Silhouette Hartama, Dedy; Wanayumini, W; Damanik, Irfan Sudahri
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5851

Abstract

The study examines the use of K-Means and K-Medoids algorithms in the grouping of disaster area locations in Indonesia, with the aim of identifying patterns and optimizing disaster re-sponse strategies. The data used includes geographical and historical information of various disaster events in Indonesia, such as Aceh Besar, Asahan, Badung, Bangkalan, Bekasi, and others. In the clustering process, optimization techniques such as the Elbow Method, the Da-vies-Bouldin Index (DBI), and the Silhouette Score are used to determine the optimal number of clusters. Research results show that the K-Means algorithm tends to be more stable in deal-ing with outliers than K- Means, with the results of the DBI (Davis-Booldin Index) 0.3737248981 and the cluster 7, resulting in the silhouette score of 0.868728638 and cluster 2, resulting at the elbow 98106477130.371 and claster 2. The Silhouette Score and Elbow index-es also provide a strong indication that the clustering algorithm used is capable of forming significant and meaningful clusters. The study has made important contributions to the opti-mization of clustering with three methods used so that it can be the basis for authorities in planning and implementing more effective disaster mitigation policies.
An Implementation of Hybrid CNN-XGBoost Method for Leukemia Detection Problem Hidayat, Taufiq; Hadinata, Edrian; Damanik, Irfan Sudahri; Vikki, Zakial; Irvanizam, Irvanizam
Infolitika Journal of Data Science Vol. 1 No. 1 (2023): September 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v1i1.87

Abstract

Leukemia is a blood cancer in which blood cells become malignant and uncontrolled. It can cause damage to the function of the body's organs. Several machine learning methods have been used to automatically detect biomedical images, including blood cell images. In this study, we utilized a hybrid machine learning method, called a hybrid Convolutional Neural Network-eXtreme Gradient Boosting (CNN-XGBoost) method to detect leukemia in blood cells. The hybrid method combines two machine learning methods. We use CNN as the basic classifier and XGBoost as the main classification method. The aim of this methodology was to assess whether incorporating the basic classification method would lead to an enhancement in the performance of the main classification model. The experimental findings demonstrated that the utilization of XGBoost as the main classifier led to a marginal increase in accuracy, elevating it from 85.32% to 85.43% compared to the basic CNN classification. This research highlights the potential of hybrid machine learning approaches in biomedical image analysis and their role in advancing the early diagnosis of leukemia and potentially other medical conditions.
Co-Authors Abdi Rahim Damanik Achmad Noerkhaerin Putra Agus Perdana Windarto Agustinus Liberty Pasaribu Anjelita, Mawaddah Azi Arisandi Azi Guntur Chairul Fadlan Chintya Carolina Situmorang Cici Astria Dea Dwi Rizki Tampubolon Dedi Suhendro Dedi Suhendro Dedi Suhendro Dedy Hartama Dedy Hartama Dedy Hartama Dedy Hartama Deny Franata Pasaribu Dermawan, Sabaruddin Dewi, Rafiqa Dewinta Marthadinata Sinaga Dinda Nabila Batubara Eka Irawan Eka Irawan Eka Irawan Eka Irawan Eka Irawan Eka Irawan Eka Irawan F Fauziah Fachry Abda El Rahman Fajar Rudi Sartomo Samosir Fikri Wicaksono Frskila Parhusip Guntur, Azi Hadinata, Edrian Hanifah Urbach Sari Hanne Lore Br Siagian Hartama, Dedy Hasudungan Siahaan Hendry Qurniawan Heru Satria Tambunan Heru Satria Tambunan Heru Satria Tambunan, Heru Satria Hutasoit, Rahel Adelina Ika Okta Kirana Ilham Syahputra Saragih Ilham Syaputra Saragih Indah Pratiwi M.S Indra Gunawan Ira Audita Irawan Irawan Irnanda, Khairunnissa Fanny Irvanizam, Irvanizam Jaya Tata Hardinata Laila Kumalasari M Fauzan M Fauzan M FAUZAN M Fauzan M. Fauzan Manurung, Hotben Marina Rajagukguk Masduki Nizam Fadli Masitha Masitha Masitha, Masitha Mawaddah Anjelita Mian Manimpan Siahaan Mira Ariffiani Mita Ariffiani Muhammad Aliyul Amri Muhammad Fachrur Rozy Muhammad Ifnu Suhada Muhammad Ifnu Suhada Napitupulu, Flora Sabarina Nasution, Rizki Alfadillah Ningsih, Sri Rahayu Nur Arief Nur Hasanah Lubis Nurhidayana Nurhidayana Okprana, Harly P, Dini Rizky Sitorus Paulus Hendrico Silalahi Primatua Sitompul Rahel Nita Trides Siahaan Ria Annisa Saragih Ridho Hayati Alawiah Roni Kurniawan S Saifullah Sabaruddin Dermawan Safii, M. Sahendra Fahreza Saifullah Saifullah Sandy Putra Siregar Saputra, Widodo Saragih, Ilham Syaputra Saragih, Ria Annisa Sari, Andini Fadila Sari, Hanifah Urbach Sari, Winda Permata Sepridho, Jaka Siahaan, Mian Manimpan Sinaga, Dolli Sari Sinaga, Waris Pardingatan Siregar, Sandy Putra Siti Hadija siti rodiah Solikhun Solikhun Solikhun Sri Rahayu SRI RAHAYU Sri Rahayu Ningsih Sri Wulandari Suhada Suhada Suhada Suhada Suhada, Suhada Suhada, Muhammad Ifnu Suhendro, Dedi Sumantri Sihombing Sundari Retno Andani Susiani Susiani Susiani, Susiani Theresia Siburian Vikki, Zakial Wanayumini Wanto, Anjar Widodo Saputra Winanjaya, Riki Yumni Syabrina Agustina Lubis Zulia Almaida Siregar