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Penerapan Datamining Klasifikasi Pada Faktor Pemilihan Cafe Bagi Anak Millineal Tanjung, Fatimah Dwi Puspa; Windarto, Agus Perdana; Irawan, Eka
Bulletin of Data Science Vol 1 No 3 (2022): June 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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

The purpose of this study is to apply the cafe selection factor for millennial children at the Sutomo Square cafe Pematangsiantar City by using the C4.5 Algorithm. Sources of data in the study used were observations, literature studies and distributing questionnaires to millennial children at the Sutomo Square cafe, Pematangsiantar City. The results of this study are expected to determine the factors in the selection of cafes for millennial children so that cafe owners can improve their creativity and cafe quality

Sistem Penyiram Otomatis Berbasis IOT Smart Home Pada Tanaman Rumah Menggunakan Arduino Atmega 328P Nainggolan, Joshua Fines; Poningsih, Poningsih; Irawan, Irawan; Irawan, Eka; Amalya, Nanda
BEES: Bulletin of Electrical and Electronics Engineering Vol 4 No 2 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bees.v4i2.4637

A greenhouse is a building with a frame or shaped like bubbles, covered with clear or translucent material that can transmit light optimally for production and protect plants from climatic conditions that are detrimental to plant growth. Research on an Arduino-based plant watering system in a plant house aims to design, create, and test a system to be able to carry out watering. The method used in research on an IOT smartphone-based plant watering system uses an ATMEGA 328P Arduino. There are several stages that need to be paid attention to, namely the design stage, the construction/manufacturing stage, and the installation stage. Next is the testing of products that have been made using Arduino and ESP8266. Watering can be scheduled so that it is done on time. The system can do watering; watering is done automatically with a working voltage of 208–214 VAC and 15 VDC and a constant Arduino pin voltage of 4.8 VDC. By carrying out tests on watering plants, based on the test results, the Arduino-based automatic plant watering system in the plant house can work well according to design.

The Conjugate Gradient Backpropagation Algorithm in Predicting Inmate Rates in Pematangsiantar City Based on Gender Darma, Surya; Robiansyah, Wendi; Firzada, Fahmi; Irawan, Eka; Saputra, Widodo
IJISTECH (International Journal of Information System and Technology) Vol 8, No 2 (2024): The August edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i2.353

The increase in the number of inmates in Indonesia, particularly in Pematangsiantar City, is a significant social issue. In this context, it is important to predict inmate levels based on demographic factors, including gender. One promising approach is the use of Artificial Neural Networks (ANN) with the Backpropagation Conjugate Gradient (BPCG) algorithm. ANN is a computational model that mimics the way the human brain processes information and has been used in various applications, including crime prediction. The BPCG algorithm is a variant of the backpropagation algorithm that efficiently accelerates the convergence of ANN training. This study aims to implement ANN with the BPCG algorithm to predict inmate levels in Pematangsiantar City based on gender and to evaluate the performance of this model in the context of available crime data. MATLAB (version 7.13 R2011b) was used as a tool, employing five model architectures (7-3-1, 7-5-1, 7-11-1, 7-12-1, and 7-15-1) to test data for estimation/prediction. The best model, 7-12-1, achieved 100% accuracy with 16 iterations in less than 1 second and an MSE of 0.1477446359. With 100% accuracy, this model will be used to predict the number of inmates in Pematangsiantar City by gender in 2023. This study can make a significant contribution to the fields of criminology and data analysis and serve as a reference for future research on the use of artificial intelligence in legal and criminal contexts.

The Conjugate Gradient Backpropagation Algorithm in Predicting Inmate Rates in Pematangsiantar City Based on Gender Darma, Surya; Robiansyah, Wendi; Firzada, Fahmi; Irawan, Eka; Saputra, Widodo
IJISTECH (International Journal of Information System and Technology) Vol 8, No 2 (2024): The August edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i2.353

The increase in the number of inmates in Indonesia, particularly in Pematangsiantar City, is a significant social issue. In this context, it is important to predict inmate levels based on demographic factors, including gender. One promising approach is the use of Artificial Neural Networks (ANN) with the Backpropagation Conjugate Gradient (BPCG) algorithm. ANN is a computational model that mimics the way the human brain processes information and has been used in various applications, including crime prediction. The BPCG algorithm is a variant of the backpropagation algorithm that efficiently accelerates the convergence of ANN training. This study aims to implement ANN with the BPCG algorithm to predict inmate levels in Pematangsiantar City based on gender and to evaluate the performance of this model in the context of available crime data. MATLAB (version 7.13 R2011b) was used as a tool, employing five model architectures (7-3-1, 7-5-1, 7-11-1, 7-12-1, and 7-15-1) to test data for estimation/prediction. The best model, 7-12-1, achieved 100% accuracy with 16 iterations in less than 1 second and an MSE of 0.1477446359. With 100% accuracy, this model will be used to predict the number of inmates in Pematangsiantar City by gender in 2023. This study can make a significant contribution to the fields of criminology and data analysis and serve as a reference for future research on the use of artificial intelligence in legal and criminal contexts.

Penerapan Metode Analitycal Hierarchy Process (AHP) Dalam Menentukan Siswa Berprestasi SMA MAN Simalungun Bonita, Tanti; Irawan, Eka; Rizki, Fitri
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.290

The purpose of this study was to make a ranking of high achieving students in the tenth grade at Simalungun MAN School. In this study, researchers used a Decision Support System, using the Analytical Hierarchy Process (AHP) Method. From the data of student grades, all tenth graders of MAN Simalungun obtained student scores that have not yet reached the minimum completeness criteria (KKM). To assess student achievement not only from semester exam scores, grades in other fields can also be considered by teachers in assessing students. In the assessment can be taken from everyday values and also student absences. It is hoped that the results of this research can provide input to the school, especially teachers to pay more attention to students who are weak in the learning process. So students are motivated and can improve achievement at school

Implementasi Metode K-Medoids Clustering Dalam Pengelompokan Data Penyakit Alergi Pada Anak Ningrum, Haryati; Irawan, Eka; Lubis, Muhammad Ridwan
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.277

Allergies are an abnormal response from the immune system. People who experience allergies have an immune system that reacts to a substance that is usually harmless in the environment. There are two limitations in this study, namely, seafood allergy and air allergy. In this study, the data used were sourced from the National Statistics Agency in 2011-2019. This study uses data mining techniques in data processing with the k-medoids clustering method. The k-medoids method is a clustering method that functions to split the dataset into several groups. The advantages of this method are able to overcome the weaknesses of the k-means method which is sensitive to outliers. Another advantage of this method is that the results of the clustering process do not depend on the order in which the dataset is entered. This method can be applied to data on the percentage of children affected by allergies by province, so that it can be seen the grouping of provinces based on this data. From this grouping data obtained 3 clusters namely low cluster (2 provinces), medium cluster (30 provinces) and high cluster (2 provinces) from the percentage of allergy immunization under five in each province. It is hoped that this research can provide information to the health department, especially the public health center regarding data grouping of Allergic Diseases in children in Indonesia which has an impact on equity in giving anti-allergic immunization to children in Indonesia

Implementasi Algoritma K-Medoids untuk Pengelompokkan Sebaran Mahasiswa Baru Irawan, Eka; Siregar, Sandy Putra; Damanik, Irfan Sudahri; Saragih, Ilham Syaputra
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 5, No 2 (2020): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v5i2.213

The existence of new students at a tertiary institution is a routine activity every year in a tertiary institution and can also see the sustainability of the tertiary institution. The variety of regional origin of new students makes the party from the university want to see the distribution of new students based on the origin of the school and its place of residence. STIKOM Tunas Bangsa is one of the tertiary institutions in Pematangsiantar. It aims to promote the university. K-Medoids is able to group data on the distribution of new students in STIKOM Tunas Bangsa Pematangsiantar. The clusters produced in this study are of three clusters. The validity used in this study is the validity of Silhoutte Coefficient. The validity value generated in the K-Medoids algorithm produces a validity value of -116.47 by assuming that if the non-medoids value produced S

Analisis Metode SMART Rekrutmen Guru Baru TK/Paud Lestari Di Kabupaten Simalungun Putri, Nadillah Dwi; Irawan, Eka
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.285

This research is based on the background of the observations and experiences of researchers, that the system of recruitment of new teachers who are currently running in TK / PAUD LESTARI is still not optimal because they are still doing manual and not computerized methods. As a result, it will slow down the work time of the school in making decisions, searching, inputting, updating, the previous recruitment data of the previous period will also be difficult and require a long time, and the security of data recruitment is also not guaranteed. This study uses a quantitative research approach with the subject of new teacher recruitment research for TK / PAUD LESTARI. Research is carried out in the System Development Life Cycle (SDLC) which is a life cycle or methodology in system development. The conclusion of the results of this study is through the cycle of the System Development Life Cycle (SDLC) which is a life cycle or methodology in developing the system to be even better. Based on the conclusions of the results of this study, it was recommended: the aim of the researchers to conduct this research was to design and create a "New Teacher Recruitment Decision Support System in TK / PAUD LESTARI in Simalungun Regency" in order to facilitate the school in inputting, updating, searching and securing recruitment data

Jaringan Syaraf Tiruan Untuk Memprediksi Nilai Siswa SMA Menggunakan Backpropagation Damanik, Evan Hikler; Irawan, Eka; Rizki, Fitri
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 4 No. 2 (2021): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v4i2.1500

Penguasaan seorang siswa/i terhadap sebuah mata pelajaran sangat mempengaruhi pemberian nilai yang dilakukan oleh pengajar yang bersangkutan. Perlunya pengajar atau guru memantau setiap nilai dari siswa/i yang diajarkan ilmu pengetahuan pada bidangnya masing-masing. Dengan perkembangan teknologi yang sangat cepat, sangat membantu pengajar dalam mengetahui atau memprediksi nilai yang akan didapatkan siswa/i terkait. Penelitian ini bertujuan untuk menerapkan kinerja jaringan syaraf tiruan algoritma backpropagation dalam memprediksi nilai siswa/i sekolah menengah atas dengan berbagai model dan meminimalkan error nya. Pada penelitian ini penulis menggunakan data nilai siswa/i sekolah menengah atas negeri 1 sidamanik. Dalam pengolahan data nilai, penulis menggunakan jaringan syaraf tiruan dengan algoritma backpropagation sebagai langkah-langkah logis untuk melakukan prediksi nilai ujian nasional siswa/i sekolah menengah atas. Pokok permasalahan pada penelitian ini adalah terjadinya penurunan nilai ujian nasional siswa/i dibeberapa mata pelajaran, yang kedepannya siswa/i akan mengalamin kesulitan dalam mencapai universitas atau sekolah tinggi yang diinginkan. Kata Kunci: Nilai Siswa/i, Sekolah, JST, Backpropagation

Menentukan Kepuasan Masyarakat dalam Membuat Surat Izin Mendirikan Bangunan pada Dinas Penanaman Modal dan Pelayanan Terpadu Satu Pintu menggunakan Algoritma K-Nearest Neighbor Hutasoit, Rahel Adelina; Suhada, Suhada; Irawan, Eka; Damanik, Irfan Sudahri; Susiani, Susiani
MEANS (Media Informasi Analisa dan Sistem) Volume 5 Nomor 2
Publisher : LPPM UNIKA Santo Thomas Medan

This research aims to classify the public satisfaction on the creation of building permits in the Office of Investment and integrated service of one door Pematangsiantar. Data is obtained from the results of a community questionnaire from 2019, with a sample of 80 data in society. The attributes used as many as 9, namely terms, procedures, service time, cost/tariff, service products, implementing competence, implementing conduct, infrastructure and handling complaints. The method used in this research is the K-Nearest Neighbor (KNN) algorithm and was processed using the RapidMiner Studio 8.1 software to determine the public satisfaction of the creation of building permits. The data used is divided into two, which are training data used 50 data and data testing used as much as 30 data. With this research is expected to help the Department of Investment and Integrated services one door Pematangsiantar to evaluate the service system provided to the public to meet the expectations of the community in the manufacture of building permits.

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