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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Mantik Jurnal Tekinkom (Teknik Informasi dan Komputer) Jurnal EK dan BI Jurnal Sistem Komputer dan Informatika (JSON) Journal of Computer Networks, Architecture and High Performance Computing Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) JURNAL RUMPUN MANAJEMEN DAN EKONOMI
Sinaga, Novendra Adisaputra
Universitas Murni Teguh
Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Social Sciences

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Komparasi Metode Decision Tree, KNN, dan SVM Untuk Menentukan Jurusan Di SMK Novendra Adisaputra Sinaga; Ramadani Ramadani; Khoirunsyah Dalimunthe; Muhamad Sayid Amir Ali Lubis; Rika Rosnelly
Jurnal Sistem Komputer dan Informatika (JSON) Vol 3, No 2 (2021): Desember 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v3i2.3598

Abstract

The selection of majors for prospective vocational students is the first step in determining the next career. The determination of the major aims so that students can be directed in receiving lessons based on the ability and talent of students and of course when they have graduated have the skills to get a job if they do not continue their studies. Siti Banun Sigambal Private Vocational School is located in Labuhanbatu Rantau Prapat. In realizing one of the missions of SMK, namely Realizing quality learning in Vocational High School, SMK Siti Banun in determining the Department by conducting tests. In classifying data mining techniques can be used, among others Decision Tree, K-Nearest Neighbors (KNN) and Support Vector Machine (SVM). This research was conducted to compare the performance of Decision Tree, KNN and SVM algorithms in determining majors. Of the 245-test data used obtained SVM has an accuracy value of 89%, precision 87% while KNN has an accuracy value of 84%, precision 81% and Decision Tree has an accuracy value of 78% and precision of 75%.
Decision Support System for Purchase of Used Cars using Electre Method Novendra Adisaputra Sinaga; Arifin Tua Purba
Journal of Computer Networks, Architecture and High Performance Computing Vol. 1 No. 2 (2019): Computer Networks, Architecture and High Performance Computing
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v1i2.240

Abstract

- This study aims to build a decision support system that can help facilitate the selection of the right used car for potential buyers. To be able to buy a used car that suits the needs and funds owned by consumers, buyers must consider the many criteria and factors of each used car which consists of various brands that exist today. This study uses the ELECTRE (Elimination and Choice Translation Reality) method. The criteria in the comparison used in this decision support system are documents, cylinder volume, year of production and car price. The ELECTRE method is used in conditions where alternatives that do not meet the criteria are eliminated, and suitable alternatives can be generated. Of the 8 samples of used cars studied, the best recommendation was Ayla (A4) with a total aggregate of 4 and an alternative that was not recommended was Agya (A3) with a total aggregate of 0.
Indonesian Business Polytechnic New Student Admissions Test Using a Computer Based Test (CBT) Novendra Adisaputra Sinaga; Firinta Togatorop
Jurnal Mantik Vol. 4 No. 3 (2020): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2020.1110.pp2237-2244

Abstract

New Student Admission Is One Process in Higher Education which aims to filter out prospective students who are selected according to the criteria determined by the Higher Education to become their students. In general, the process of admitting new students is carried out through the stages of registration, selection tests, and student admissions. Every year, Politeknik Bisnis Indonesia conducts the Entrance Examination for ± 300 people, which is done manually so it takes longer time to print the questions, check the results of the exam and report the results of the exam. Computer Based Test (CBT) by utilizing the Moodle CMS is one of the evaluation strategies used to determine the capacity and competence of prospective new students more quickly and more efficiently. Utilizing this application simplifies the work of the Exam Committee so that it is more productive and professional in managing Administration. This application also requires prospective students to be accustomed to using the application and must be more mature in carrying out the examination because it does not allow working with others because the questions and answer choices appear randomly.
PERBANDINGAN AKURASI ALGORITMA NAÏVE BAYES, K-NN DAN SVM DALAM MEMPREDIKSI PENERIMAAN PEGAWAI Novendra Adisaputra Sinaga; B Herawan Hayadi; Zakarias Situmorang
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.446

Abstract

To supporting academic and non-academic activities, the Polytechnic Business Indonesian (PBI) must be supported by employees with reliable Human Resources (HRD) who have good behavior, good abilities and can complete work professionally and responsibly. Conventional techniques for analyzing existing large amounts of data cannot be handled which is the background for the emergence of a new branch of science to overcome the problem of extracting important information from data sets, which is called Data Mining. Utilizing methods to classify data by utilizing methods including: Naïve Bayes method, K-Nearest Neighbor (K-NN) and Supervise Vector Machine (SVM). From this research, in Predicting Applicants Graduation at PBI, the SVM method is better than Naïve Bayes and K-NN. With 33 test data used, SVM has 84.9% accuracy, 85.1% precision while K-NN has 81.8% accuracy, 84.1% precision and Naïve Bayes has 78.8% accuracy and 80.1% precision.
PERANGKAT LUNAK JAJAK PENDAPAT (VOTING) BERBASIS SHORT MESSAGE SERVICE (SMS) GATEWAY DAN WEB Novendra Adisaputra Sinaga; Andi Setiadi Manalu; Benjamin Albert Simamora
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 3 No 1 (2020)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v3i1.128

Abstract

One of the characteristics of democracy is characterized by direct elections. Nowadays the role of technology greatly affects all aspects of life because it is more effective and accurate. Electronic voting or e-voting is the usual form of voting used for general elections and polls using electronic media. The shift in the conventional election process in today's technological era utilizes the media for polling, one of which is short message service (SMS). The use of Short Message Service (SMS) technology can now be utilized for voting because it is supported by many factors including availability, speed, security and accuracy of data generated. Voting Based on Short Message Service (SMS) and relatively cheap costs so as to make it easier for users, both voting participants and voting implementers, to be more optimal.
SISTEM INFORMASI PEMATANGSIANTAR DIRECTORY MENGGUNAKAN METODE BACKWARD CHAINING BERBASIS MOBILE Novendra Adisaputra Sinaga
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 1 No 1 (2018)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (940.568 KB) | DOI: 10.37600/tekinkom.v1i1.38

Abstract

This Research is designed for an information system in the form of expert system applications to present information on Pematangsiantar Directory. The purpose of this system is to help provide information about the city of Pematangsiantar as a whole to the residents of Pematangsiantar city in particular and the local and foreign tourists as well as prospective investors in general. The system presents information in the form of public service to the residents of Pematangsiantar city government and other newcomers as well as products and services are made and offered by the business and government. The analysis was done by determining the first goal, then do the searching to obtain the desired information. The design system uses backward chaining inference method to the implementation of the system using My-SQL database systems and programming languages of PHP and JQuery. The system is based on mobile, so it can be accessed using a mobile device
PENGEMBANGAN SISTEM INFORMASI LABORATORIUM KOMPUTER BERBASIS WEB (STUDI KASUS POLITEKIK BISNIS INDONESIA) Novendra Adisaputra Sinaga
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 1 No 2 (2018)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (946.9 KB) | DOI: 10.37600/tekinkom.v1i2.69

Abstract

Politeknik Bisnis Indonesia adalah sebuah lembaga pendidikan berupa perguruan tinggi dibawah naungan Yayasan Pendidikan Bina Usaha Indonesia. Pengelolaan sistem informasi laboratorium komputer pada Politeknik Bisnis Indonesia yang masih belum terkomputerisasi menjadikan sistem kinerja pada Politeknik Bisnis Indonesia mengalami kendala dalam penyampaian informasi dan pengelolaan data. Penerapan sistem laboratorium komputer masih belum dimaksimalkan menggunakan sistem yang terkomputerisasi hanya menggunakan media aplikasi sederhana dan media pencatatan manual. Oleh karena itu dibutuhkan sistem yang dapat memenuhi sistem informasi secara efektif dan efisien. Untuk itu penulis mengambil judul “Pengembangan Sistem Informasi Laboratorium Komputer Berbasis Web (Studi Kasus Politeknik Bisnis Indonesia)” yang diharapkan dapat menjadi penerapan pengembangan sistem informasi sebelumnya yang dapat mempermudah kinerja pada bagian Staff Laboratorium Komputer Politeknik Bisnis Indonesia untuk memperoleh data yang dibutuhkan dengan lebih efisien dan akurat. Tujuan penulisan Tugas Akhir ini untuk mempelajari, menganalisis, merancang dan mengimplementasikan Pengembangan Sistem Informasi Laboratorium Komputer Berbasis Web Pada Politeknik Bisnis Indonesia dengan menggunakan HTML, PHP dan MySql sebagai bahasa pemograman yang digunakan.
SISTEM INFORMASI ADMINISTRASI KEPENDUDUKAN (STUDI KASUS: DESA PARSAORAN AJIBATA KECAMATAN AJIBATA KABUPATEN TOBA SAMOSIR) Novendra Adisaputra Sinaga; Sarida Sirait
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 2 No 2 (2019)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (725.455 KB) | DOI: 10.37600/tekinkom.v2i2.101

Abstract

Parsaoran Sibisa Village, Ajibata is the village with the highest population density with a fairly high population movement in Ajibata Subdistrict, Toba Samosir Regency. At present the administrative system and population data activities are used by the filing method. Filing method is done by recording population data in population archive books, this method is less effective and efficient when there is a complex process of finding population data and population data reports. From these data it can be concluded that the problem in Parsaoran Ajibata Village is the lack of orderly administration of population so that population services are less effective and efficient. Therefore, the writer tries to offer a solution to build Population Administration Information System as Supporting Population Administration Order in Parsaoran Sibisa Village, Ajibata District, Toba Samosir Regency. Through assistance and training to the Village Government it will increase the knowledge and understanding of the importance of using Information Systems in terms of efficiency and effectiveness so that the Population Database in the Pisaoran Sibisa Village, Ajibata District is complete, accurate, and up to date.
IMPLEMENTASI DATA MINING C4.5 PENERAPAN ALGORITMA C.45 UNTUK MEMPREDIKSI TINGKAT KEPUASAN MAHASISWA TERHADAP POLITEKNIK BISNIS INDONESIA Novendra Adisaputra Sinaga; Arifin Tua Purba
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 4 No 2 (2021)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v4i2.394

Abstract

Universities are not only required to provide services for students, but also must be able to compete to maintain service quality. This demand is absolutely necessary in order to create a loyalty for the community which will become valuable capital for an organization in the future. This study aims to recommend the satisfaction of Indonesian business polytechnic students by using the C4.5 data mining classification technique. Sources of data were obtained from questionnaires distributed via google form to final semester students (class of 2018) at the Indonesian Business Polytechnic. The attributes used to assess visitor satisfaction include: Tuition Fee Tariff, Campus Facilities, Administrative Services, Lecturer Services, Recommendation Level. The results of data processing using the C4.5 method through the RapidMiner tools obtained an accuracy value of 80.00%, precision 79.19%, and recall 79.19% with Satisfied criteria.
Analysis of EfficientNetV2 Model Usage in Predicting Gender on the Face of Mask Users Novendra Adisaputra Sinaga
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 9 No 3 (2022): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v9i3.2975

Abstract

A technique for identifying physical traits or human behavior that is utilized as input for pattern recognition is called biometrics. Each type of biometric identification undoubtedly employs a unique technology. In order to do research on how to promote or sell items in accordance with visitor gender, a gallery or exhibition, such as a movie theater, retail mall, or exposition, needs visitor information from the event. The EfficientNetV2 model, a New Family in the Covolution Neural Network (CNN) family, outperforms the previous model in terms of parameter efficiency and training speed. According to tests, the EfficientNetV2 model can learn up to 6.8.The results using the EfficientNetV2 model were carried out for 25 epochs and there were 2 classes, namely male and female, each of which consisted of 72,318 training data and 16,813 testing data. The accuracy value for training is 0.9455 (94.5%) and for data testing the accuracy value is 0.9475 (94.7%). The loss value for training is 0.1375 (13.75%) and for testing data the loss value is 0.1277 (12.7%).
Co-Authors Andi Setiadi Manalu Arifin Tua Purba B. Herawan Hayadi Benjamin Albert Simamora Berlien, Richard Calen, Calen Edi Siregar Eka Pratiwi Septania Parapat Erikson Damanik Firinta Togatorop Henry Dunan Pardede Khoirunsyah Dalimunthe Muhamad Sayid Amir Ali Lubis Nainggolan, Grace Agustina Arthauli Pardede, Doughlas Purba, Arifin Tua Ramadani Ramadani Rika Rosnelly Sarida Sirait Sugeng Riyadi Sumaizar Sumaizar Teddy Surya Gunawan Wanayumini William Liang Zakarias Situmorang