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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

Author-ID : 607325

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

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Penerapan Metode Smart Dalam Menentukan Mata Kuliah Terfavorit Pada Kampus Merdeka Di STIKOM Tunas Bangsa Muhammad Fachrur Rozy; Irfan Sudahri Damanik; Ilham Syahputra Saragih
Bulletin of Information Technology (BIT) Vol 2 No 3: November 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Saat ini kreativitas dan inovasi menjadi kata kunci penting untuk memastikan pembangunan Indonesia yang berkelanjutan. Para mahasiswa yang saat ini belajar di Perguruan Tinggi, harus disiapkan menjadi pembelajar sejati yang terampil, lentur dan ulet. Kebijakan Merdeka Belajar – Kampus Merdeka yang diluncurkan oleh Menteri Pendidikan dan Kebudayaan merupakan kerangka untuk menyiapkan mahasiswa menjadi sarjana yang tangguh, relevan dengan kebutuhan zaman, dan siap menjadi pemimpin dengan semangat kebangsaan yang tinggi. Proses pengambilan data diperoleh dengan cara membagikan kuisioner dan observasi secara langsung.Dengan variable jumlah SKS, peluang pekerjaan, dan alasan mahasiswa dalam mengambil mata kuliah pada kampus merdeka. Hasil penelitian ini berupa mata kuliah yang akan diambil berdasarkan mata kuliah yang ada pada Kampus Merdeka di STIKOM Tunas Bangsa.

Pemilihan Model Arsitektur Terbaik Dengan Mengoptimasi Learning Rate Pada Neural Network Backpropagation Cici Astria; Agus Perdana Windarto; Irfan Sudahri Damanik
JURIKOM (Jurnal Riset Komputer) Vol 9, No 1 (2022): Februari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i1.3834

Backpropagation is one of the methods contained in a neural network that is able to train dynamic networks using mathematical knowledge based on architectural models that have been developed in detail and systematically. Backpropagation itself is able to accommodate a lot of information that serves as a useful experience. However, the Backpropagation Algorithm tends to be slow to achieve convergence in obtaining optimum accuracy and requires large training data and the optimization used is less efficient. The purpose of this research is to optimize the learning rate on backpropagation neural networks. Source of data obtained from CV. Bona Tani Hatonduhan. There are 3 network architecture models used in this study, namely 2-51, 2-6-1, and 2-7-1 with learning rates of 0.1, 0.2, and 0.3. the results of trials carried out with MATLAB software produced the best architectural model, namely the 2-7-1 model with a learning rate of 0.3 with an accuracy of 83%. Based on this background, it is hoped that the results of the research can help in the process by optimizing the learning rate of the backpropagation Neural Network on the selection of the best architecture.

Analisis Jaringan Saraf Tiruan dengan Backpropagation pada korelasi Matakuliah Pratikum Terhadap Tugas Akhir Hanifah Urbach Sari; Agus Perdana Windarto; Irfan Sudahri Damanik
JURIKOM (Jurnal Riset Komputer) Vol 9, No 1 (2022): Februari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i1.3835

Backpropagation is one of the methods contained in a neural network that is able to train dynamic networks using mathematical knowledge based on architectural models that have been developed in detail and systematically. Backpropagation itself is able to accommodate a lot of information that serves as a useful experience. The purpose of this research is to make it easier for AMIK Tunas Bangsa Pematangsiantar students to determine the topic of their final project with practical value so that they can do their final project quickly. So the authors conducted research using correlation in determining the topic of the final project. The data in this study were obtained directly from the AMIK Tunas Bangsa Education academics in Pematangsiantar City. The data used uses data on practical grades of AMIK Tunas Bangsa Stambuk students 2017 from semester 4 to semester 6. There are 5 network architecture models used in this study, namely 5-1-2, 5-6-2, 5-8 -2, 5-10-2, and 5-12-2. From the results of trials conducted with MATLAB software, the best architecture is the 5-1-2 model with an accuracy of 47%. Based on this background, it is hoped that the research results can help students in determining the topic of the final project

Memanfaatkan Algoritma K-Means Dalam Memetakan Potensi Hasil Produksi Kelapa Sawit PTPN IV Marihat Deny Franata Pasaribu; Irfan Sudahri Damanik; Eka Irawan; Suhada; Heru Satria Tambunan
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 2 No 1 (2021): March
Publisher : Puslitbang Sinergis Asa Professional

Based on data on the results of oil palm production in PTPN IV Marihat displays several locations with fruit yields that vary in number. For this reason, grouping of potential fruit-producing locations is needed to know which locations produce large or small numbers of palm fruit. The production sharing is usually done based on the location or block of harvesting oil palm fruit. Therefore, a method is needed to facilitate the grouping of fruit producing locations. With the K-Means clustering approach, the division of location groups can be done based on harvested area (Ha), production realization (kg) and harvest year. In this research, clustering of potential fruit-producing areas was carried out using the K-Means algorithm. By using K-Means aims to facilitate the grouping of a block with a lot of fruit production, and low. The result of this research is that C1 (highest) is 14 Harvest Block data, and C2 (lowest) is 11 Harvest Block data.

Analisis Penilaian Kualitas Jenis Pelayanan Tebaik dengan Metode Analytic Network Process (ANP) di Kantor Dinas Kependudukan dan Pencatatan Sipil Kota Pematangsiantar Fajar Rudi Sartomo Samosir; Irfan Sudahri Damanik; Dedi Suhendro; Solikhun; Susiani
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 2 No 1 (2021): March
Publisher : Puslitbang Sinergis Asa Professional

This study aims to determine the best service quality at the Pematangsiantar City Population and Civil Registration Office, which includes services for making Identity Cards (KTP), Family Cards (KK), birth certificates, marriage certificates and receipt making. The method used in this research is the Analytic Network Process (ANP) method. The data collection technique used is a questionnaire technique that is distributed directly to the people who come to take care of the needs of personal and family data files. The parameters used consist of the facilities provided, employee behavior, services, and provisions. Determining community satisfaction with a service can be seen from the quality of the type of service. The results of this study were obtained in rank-1 with a normal value of 0.49126400, rank-2 family cards with a value of 0.18988000, rank-3 birth certificates with a value of 0.16073800, marriage certificates rank-4 with a value of 0.09707200 and Finally, rank-5 receipt services with a value of 0.06104600 With this research it is hoped that it can help the Pematangsiantar City Population and Civil Registration Service to evaluate the services provided to the community in order to meet community expectations in terms of managing the needs of personal and family data files and knowing the types of best services.

Jaringan Saraf Tiruan Backpropagation Untuk Memprediksi Jumlah Ekspor Buah-Buahan Menurut Negara Tujuan Nurhidayana Nurhidayana; Irfan Sudahri Damanik; Rafiqa Dewi
Journal of Information System Research (JOSH) Vol 2 No 2 (2021): Januari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (345.974 KB)

This research aims to predict the number of exports of fruits by country of destination in the coming year based on data in the previous year. The application of a prediction is very important in conducting research. The method used in conducting this prediction is the artificial neural network (JST) with its Backpropagation algorithm. The architecture used in this study is 4-2-1, 4-4-1, 4-6-1, 4-8-1, 4-4-2-1, and 4-3-6-1. Test results obtained prediction of export of fruits according to destination country with 91% accuracy rate with 4-4-1 architecture

Data Mining Menggunakan Metode Asosiasi Apriori untuk Merekomendasi Pola Obat Pada Puskesmas Dewinta Marthadinata Sinaga; Agus Perdana Windarto; Heru Satria Tambunan; Irfan Sudahri Damanik
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Drugs are one of the most important components in terms of health, both to cure and reduce pain due to illness suffered by everyone, besides that the use of drugs also gives us information about what diseases everyone suffers so that the information is very helpful for health workers. For this reason, drugs need to be managed properly, effectively and efficiently. This study aims to analyze the a priori algorithm on drug output data at the Parsoburan Health Center Pematangsiantar to find out what types of drugs are most needed by patients at the same time. The data used is in the form of drug output data in April 2021. Based on the a priori algorithm calculations, 70 association rules were formed with a number minimum of support 90% and a minimum confidence of 90%. It is hoped that the results of the research can help the Parsoburan Health Center Pematangsiantar optimize quality health services for planning future drug needs and produce useful information for decision making.

Analysis of Weight Product (WP) Algorithms in the best Go Car Driver Recommendations at PT. Maranatha Putri Bersaudara Roni Kurniawan; Agus Perdana Windarto; M Fauzan; Solikhun Solikhun; Irfan Sudahri Damanik
IJISTECH (International Journal of Information System and Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

This study aims to rank the best Go Car Driver. The problem arises because of the inaccuracy in giving value to the driver which results in the decision being given incorrectly so that the assessment tends to be subjective. This research was conducted at PT. Maranatha Putri Bersaudara. Sources of data obtained by observing, interviewing. The settlement method used is a decision support system with the Weight Producted method. The assessment criteria used are Performance (C1), Number of orders (C2), Rating (C3), Attitude (C4), Rating (C5) and Appearance (C6) where the alternatives used are 4 samples. The results obtained using the Weighted Product method are Alternative1 and Alternative4 which are recommended as the best go car driver with the assessment results of 0.0307 and 0.0272. It is expected that research results can be input to the relevant parties in recommending the best go car driver so as to minimize subjective judgment.

Application of Data Mining on Patterns of Sales of Goods in Minimarkets Using the Apriori Algorithm Siti Hadija; Eka Irawan; Irfan Sudahri Damanik; Jaya Tata Hardinata
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 4 (2022): December
Publisher : Yayasan Literasi Sains Indonesia

Minimarket is a shop that sells goods for daily needs. Each minimarket generates a lot of sales data every day. Sales transaction data can only be stored without further analysis. Based on this description, research was conducted to assist minimarket managers in making it easy to solve sales pattern problems at minimarkets using the Apriori algorithm. The Apriori algorithm is an algorithm that searches for item set frequencies using the association rule technique. The final result of using data mining using the Apriori association method is proven to be able to find out the results of the analysis that appear simultaneously based on sales data at the Mawar Simp.Tangsi Balimbingan Minimarket with a minimum amount of support of 30% and 80% confidence resulting in 8 association rules that are formed.

Determining Product Suitability using Rule-Based Model with C4.5 Algorithm Chintya Carolina Situmorang; Dedy Hartama; Irfan Sudahri Damanik; Jaya Tata Hardinata
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.v2i1.1923

A hotel warehouse must have orderly, good, safe, comfortable, and usable procurement of goods. The common issue that occurs in a warehouse is damaged and unusable goods. The fluctuating production demand for goods sometimes leads to neglecting the quality of the goods in the warehouse. To determine usable goods, appropriate recommendations are needed. The C4.5 algorithm with data mining techniques is an appropriate recommendation for analyzing a large amount of data for classification. The data used in this study is the inventory data of Hotel Sapadia Pematangsiantar's warehouse. Implementing the C4.5 algorithm that produces a Decision Tree can assist the warehouse in determining which goods are still usable for hotel activities. This study resulted in the best variable from the rule model used to determine the feasibility of goods being the physical condition of the goods. The accuracy of the rule model generated from the C4.5 Algorithm modeling is 99.02% against the feasibility of goods.

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

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