Article Per Year (5 Year)
p-Index From 2021 - 2026
6.755
P-Index
This Author published in this journals
All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA Jurnal Ilmiah Media Sisfo IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science Jurnal Mantik JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) JUKI : Jurnal Komputer dan Informatika Jurnal Scientia Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JPM: JURNAL PENGABDIAN MASYARAKAT Journal of Social Responsibility Projects by Higher Education Forum Bulletin of Information Technology (BIT) Prosiding Snastikom Jurnal ABDIMAS Budi Darma Bulletin of Data Science Jurnal Nasional Teknologi Komputer Journal of Informatics, Electrical and Electronics Engineering Journal Global Technology Computer Jurnal Sains dan Teknologi Informasi Bulletin of Artificial Intelligence ORAHUA : Jurnal Pengabdian Kepada Masyarakat Journal of Decision Support System Research Jurnal Mitra Pengabdian Farmasi Jurnal Komtika (Komputasi dan Informatika)
Dito Putro Utomo
Politeknik Negeri Medan, Medan
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation Other

Published : 71 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 71 Documents
Search

 4   5   6   7   8 
Decision Support System for admission of new employees by applying a combination of ANP-TOPSIS Methods Purba, Roulina Agape; Hasibuan, Nelly Astuty; Utomo, Dito Putro
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 4 (2022): Article Research: Volume 6 Number 4, October 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i4.11724

Abstract

Acceptance of new employees is one of the routine activities carried out to find reliable employees in their fields and become a benchmark to reflect the face of the company to the entire community. Currently, the problem that occurs is that the management process for new employee recruitment is centralized based on internal selection calculations by only one party, so that the results of assessment and decision making tend to be less objective and efficient at this time. So that the decisions taken can trigger the tendency of subjectivity in one of the prospective registrants which results in brokering at the selection stage.. To answer the challenge, ANP and the Technique were used to create a Decision Support System (DSS). Sort Preferences based on their similarity to the ideal solution. (TOPSIS) approach for hiring and retaining new employees by determining the optimum solution based on that strategy. The ANP was employed in this study to assign a weight to each criteria. The TOPSIS ranking technique is used to compute the weight.
Implementasi Metode EDAS Dalam Penilaian Kinerja Dosen Pada Masa Pandemi Covid-19 dengan Pembobotan Entropy Indini, Dwina Pri; Siregar, Tesa Aurelia; Utomo, Dito Putro
Journal of Informatics, Electrical and Electronics Engineering Vol. 3 No. 2 (2023): Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v3i2.1613

Abstract

Along with the development of technology that makes online learning run well, but the enthusiasm for student learning is not like when face to face and there are still many students who do not take various courses so that students' knowledge abilities are greatly decreased. When online learning takes place, it is very necessary for a lecturer's performance to arouse students' enthusiasm in participating in online learning. Because during this pandemic the role of lecturers is very necessary to develop an innovation and be able to make students not bored in participating in online learning. And also in terms of the performance appraisal process, several problems often occur, namely the speed in the performance appraisal process and also the accuracy of the performance appraisal. In assessing the performance of lecturers during online learning, there are several criteria including Discipline, Delivery of Materials, Interaction, Discussion Questions and Answers and Punctuality. Based on these problems, a decision support system is needed as a problem solving technique and is assisted by a method that can produce an accurate final value. The method is the Evaluation Based On Distance From Average Solution (EDAS) and Entropy method which is very helpful in generating weight values ??from alternative data and criteria so as to get the final results obtained in Alternative L9 with a value of 0.31025 on behalf of Surya Darma Nst, M. Kom.
Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Menggunakan Metode WASPAS Br Ginting, Raheliya; Yohana Br Ginting, Dewi; Putro Utomo, Dito
Bulletin of Information Technology (BIT) Vol 5 No 2 (2024): Juni 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i2.1399

Abstract

Human resources or employees in a company organization are very important to support the progress and quality of the company in achieving its goals. Having employees with good performance in a company does not just come from the employees themselves but there must also be a role from the company. Providing rewards to employees is one factor that can be used as a basis for providing motivation to employees. Performance appraisal is a process of measuring the results of work provided by employees, where this assessment will later provide results on who the best employees have the best performance to get rewards from the company. The problem that often occurs is that selecting the best employees or evaluating employee performance is based on subjective factors, which of course is detrimental to other employees and also has an impact on the company. Decision Support System (DSS) is a process that is part of the information system. Where the decision support system will assist in the process of completing semi-structured data processing. The Weight Aggregate Sum Product Assessment (WASPAS) method is a method that can be used in making decisions that have many attributes or criteria or is also known as MCDM (Multi Criteria Decision Making). The method used in this research is the WASPAS method which can provide the best alternative results, namely alternative A6 with the name "Tian" with a Qi value = 0.9815 which was selected as the best employee
Penerapan Data Mining Dalam Pengelompokan Data Reseller di Telkomsel Authorized Partner (TAP) Deli Tua Dengan Algoritma K-Means Indini, Dwina Pri; Mesran; Dito Putro Utomo
Jurnal Ilmiah Media Sisfo Vol 17 No 2 (2023): Jurnal Ilmiah Media Sisfo
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/mediasisfo.2023.17.2.1391

Abstract

Perkembangan dunia kerja membuat Telkomsel Authorized Partner (TAP) Deli Tua harus bersaing dalam mempertahankan reseller. Proses yang dapat dilakukan untuk mempertahankan reseller pada TAP Deli Tua yaitu dengan mengelompokan reseller menjadi 2 kelompok yaitu reseller prioritas dan reseller non-prioritas. Proses penentuan reseller prioritas dan non-prioritas dapat dilihat berdasarkan dengan data penjualan yang sudah tersimpan pada TAP Deli Tua. Namun, proses pengelompokan harus dilakukan dengan baik dan benar. Dalam melakukan pengelompokan data reseller TAP Deli Tua harus teliti, maka dalam pemrosesan pengolahan data reseller yang melakukan order produk dilakukan dengan data mining dengan teknik clustering. Penelitian ini menggunakan algoritma K-Means yang dapat membagi data menjadi beberapa cluster yang diperlukan. Dengan adanya penerapan data mining dengan algoritma K-Means dapat membantu dalam mengelompokan data reseller di TAP Deli Tua. Hasil penelitian ini memperlihatkan bahwa data mining dengan penerapan algoritma K-Means dapat membantu TAP Deli Tua dalam menghasilkan keputusan yang lebih efektif dalam pengelompokan data reseller sehingga dapat mengetahui reseller prioritas dan reseller non-prioritas. Dari 15 data sampel 12 reseller berada dalam cluster 0 dan 3 reseller berada dalam cluster 1.
Penerapan Metode Certainty Factor Dalam Mendiagnosa Penyakit Otitis Eksterna Manik, Lastri; Saragi, Naomi Labora; Utomo, Dito Putro
Bulletin of Artificial Intelligence Vol 3 No 1 (2024): April 2024
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v3i1.138

Abstract

Otitis externa is a common ear problem that often requires an accurate diagnosis for effective treatment. The Certainty Factor Method is an artificial intelligence approach used to support the diagnostic process. This research aims to apply the Certainty Factor Method in diagnosing otitis externa. Patient data, including symptoms, medical history, and examination results, are used to build a knowledge base that is then utilized in the diagnostic process. This method allows for improved accuracy in determining diagnoses by considering the confidence level associated with each symptom and examination result. Experimental results show that the application of the Certainty Factor Method can assist doctors in diagnosing otitis externa with higher accuracy compared to conventional methods. With this approach, diagnoses are made with higher confidence levels, which can aid in providing accurate and prompt treatment for patients suffering from otitis externa. The Certainty Factor Method has the potential for use in other medical contexts and can make a positive contribution to problem-solving in the healthcare field. This research underscores the importance of technology in supporting ear disease diagnosis and providing more reliable solutions for managing otitis externa. By leveraging the Certainty Factor approach, doctors can be more efficient and effective in responding to patients' conditions, thus reducing the risk of complications and enhancing healthcare quality. Therefore, this study offers a valuable contribution to the fields of medicine and computer science in improving the diagnosis of ear diseases, such as otitis externa, so that patients can receive better and faster care.
Penerapan Metode Multi-Objective Optimization On The Basis Of Ratio Analysis Dalam Sistem Pendukung Keputusan Penilaian Kinerja Pegawai Klinik Kecantikan Yohana br Ginting, Dewi; Rahmi Danur, Surizar; Putro Utomo, Dito; Feby Ronauli Lubis, Eka; Novida Sari, Sri; Rizqi Dwikunti Siregar, Dini
Bulletin of Information Technology (BIT) Vol 5 No 3: September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i3.1408

Abstract

The research conducted is to conduct an employee performance assessment process at a Beauty Clinic. The employee performance assessment process at a Beauty Clinic is carried out to provide awards to qualified employees at the Beauty Clinic. This study applies a Decision Support System (DSS) which is used as a system that can process employee performance assessments at the Beauty Clinic. In the employee performance assessment process at the Beauty Clinic, there are 6 criteria, namely Service Orientation, Integrity, Responsibility, Initiative, Discipline and Attendance. Thus, a system is needed that can make decisions, namely DSS by implementing the MOORA method to obtain preference values ​​from employee performance assessments at the Beauty Clinic, there is the best alternative in alternative A5 with a preference value of 0.37472
Peningkatan Branding UMKM Melalui Penggunaan Canva untuk Desain Kemasan Produk di Deli Serdang Saputra, Imam; Azlan, Azlan; Marbun, Nasib; Dito Putro Utomo
ORAHUA : Jurnal Pengabdian Kepada Masyarakat Vol. 2 No. 02 (2025): Januari
Publisher : Faatuatua Media Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70404/orahua.v2i02.135

Abstract

Program pengabdian masyarakat dengan tema "Peningkatan Branding UMKM Melalui Penggunaan Canva untuk Desain Kemasan Produk di Deli Serdang" bertujuan untuk meningkatkan keterampilan pelaku UMKM dalam menciptakan desain kemasan yang menarik dan profesional. Pelatihan ini dilaksanakan di Komplek Rumah Pondok Mansion, Desa Ujung Labuhan, Kecamatan Namorambe, Kabupaten Deli Serdang, dengan melibatkan 30 pelaku UMKM. Metode pelaksanaan meliputi presentasi teori tentang branding, demonstrasi penggunaan Canva, dan praktik langsung dengan pendampingan fasilitator. Hasil kegiatan menunjukkan bahwa 90% peserta mampu menggunakan Canva secara mandiri untuk membuat desain kemasan setelah pelatihan. Kemasan baru yang dihasilkan berhasil meningkatkan daya tarik produk dan memperkuat identitas merek. Beberapa peserta melaporkan peningkatan penjualan hingga 40% setelah menggunakan kemasan yang lebih profesional. Namun, keterbatasan perangkat dan koneksi internet menjadi tantangan yang diatasi dengan penyediaan fasilitas selama pelatihan. Program ini menunjukkan bahwa penggunaan Canva sebagai alat desain grafis memberikan solusi efektif dan terjangkau bagi UMKM untuk meningkatkan branding produk. Model pelatihan ini dapat direplikasi di wilayah lain untuk mendukung pertumbuhan ekonomi lokal melalui pemberdayaan UMKM.
Penerapan Data Mining Dalam Pengelompokan Data Penjualan Paket Internet di Telkomsel Authorized Partner (TAP) Deli Tua Dengan Algoritma K-Means Siregar, Tesa Aurelia; Mesran, M; Utomo, Dito Putro
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 8, No 2 (2023): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v8i2.618

Abstract

With the increasing sales of internet packages at TAP Deli Tua, it is crucial to be more meticulous in processing the sales data to avoid stock shortages that could result in losses for TAP Deli Tua. Determining the best-selling products among the internet package sales is essential, as incorrect grouping may lead to losses for TAP Deli Tua. This could further decrease the sales level at TAP Deli Tua, causing significant financial losses for the company. Therefore, TAP Deli Tua must be more attentive in data processing to prevent any detrimental outcomes.To achieve accurate decision-making, TAP Deli Tua needs to collect sales data from internet packages for analysis. One of the algorithms used for this purpose is the K-Means algorithm, which falls under Non-Hierarchical Clustering. It partitions the dataset into several clusters, optimizing the grouping criteria. The most commonly used criterion is the one that minimizes the clustering error for each point by calculating its squared distance from the corresponding cluster center. Additionally, the sum of distances for all points in a dataset is computed.Based on research findings, data mining with the implementation of the K-Means algorithm can assist Telkomsel Authorized Partner (TAP) in making more accurate and significant decisions. By applying the K-Means algorithm, the analysis revealed that out of 15 sales data points for internet packages, 8 best-selling products were in Cluster 0, while 7 non-best-selling products were in Cluster 1. With the increasing sales of internet packages at TAP Deli Tua, it is crucial to be more meticulous in processing the sales data to avoid stock shortages that could result in losses for TAP Deli Tua. Determining the best-selling products among the internet package sales is essential, as incorrect grouping may lead to losses for TAP Deli Tua. This could further decrease the sales level at TAP Deli Tua, causing significant financial losses for the company. Therefore, TAP Deli Tua must be more attentive in data processing to prevent any detrimental outcomes.To achieve accurate decision-making, TAP Deli Tua needs to collect sales data from internet packages for analysis. One of the algorithms used for this purpose is the K-Means algorithm, which falls under Non-Hierarchical Clustering. It partitions the dataset into several clusters, optimizing the grouping criteria. The most commonly used criterion is the one that minimizes the clustering error for each point by calculating its squared distance from the corresponding cluster center. Additionally, the sum of distances for all points in a dataset is computed.Based on research findings, data mining with the implementation of the K-Means algorithm can assist Telkomsel Authorized Partner (TAP) in making more accurate and significant decisions. By applying the K-Means algorithm, the analysis revealed that out of 15 sales data points for internet packages, 8 best-selling products were in Cluster 0, while 7 non-best-selling products were in Cluster 1.
Sistem Pendukung Keputusan Pemilihan Back Office Terbaik Dengan Menggunakan Metode MOOSRA Sihotang, Dahner Ismanda Bertenius; Utomo, Dito Putro
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 7, No 1 (2024): Transformasi Komputasi Kuantum Untuk Percepatan Teknologi Baru
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v7i1.8047

Abstract

Choosing the best back office is very important to support increased efficiency and effectiveness in bank operations. At PT. Bank Sumut selects the best employees in the Back Office every year. However, the selection process still has obstacles/problems. The problems faced are that the assessment and input of values is still done manually so it is less professional and quite time consuming due to the large number of back office staff who have to be assessed. Therefore, the final results obtained from the back office selection process are still less than objective. So a system is needed as a reference for the best back office selection process, namely a Decision Support System. A Decision Support System is a system that can provide problem solving capabilities and communication capabilities for problems with semi-structured conditions and unstructured situations. By using the MOOSRA method in the selection process because the MOOSRA method can calculate the weighting of the criteria and can obtain the highest criteria value so that it gets the highest weight to achieve a final ranking. The MOOSRA method is a method in a Decision Support System that can carry out a multi-criteria decision making process and can handle subjective evaluations from information collected from expert groups. The results of data processing carried out using the MOOSRA method can produce the highest final value compared to other alternatives, namely Alternative 1 (A1) with a final value of 0.3733 and is declared worthy of being the best back office.
Penerapan Metode MOOSRA Pada Sistem Pendukung Keputusan Pemilihan Leader Produksi Nainggolan, Dian Wichita; Utomo, Dito Putro
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 7, No 1 (2024): Transformasi Komputasi Kuantum Untuk Percepatan Teknologi Baru
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v7i1.8049

Abstract

The selection of production leaders at PT. Sagami Indonesia is determined based on the scores obtained from each criterion set by the company. However, choosing a leader is not easy due to the presence of many candidates meeting the criteria, and the results obtained are still less effective because there is no strong regulation in the process. To address this issue, there is a need for an assessment using a Decision Support System application to assist in decision-making for selecting production leaders. Subsequently, the analysis is conducted using the MOOSRA method to obtain rankings based on the final scores of alternatives. Based on the test results, it can be concluded that the Decision Support System application for leader selection, using the MOOSRA method, can help prevent fraud in the production leader selection process.
Co-Authors A M Hatuaon Sihite Abdul Karim Ade Ambarwati Br Ginting Aminuddin Aziz Annisa Apriliani Annisa Fadillah Siregar Annisah Annisah Asprina Br Surbakti, Asprina Br Atira Nabila Azlan, Azlan Bernadus Gunawan Sudarsono Bister Purba Boby Septia Pranata Br Ginting, Raheliya Butar Butar, Roi Martin Cici Alfiani Pradika Dita Dewi Maulida Sari Tanjung Dwi Asdini Efori Buulolo Eka Pratiwi Sumantri Faisal Amir Feby Ronauli Lubis, Eka Fince Tinus Waruwu Firman Telaumbanua Ginting, Winda Widia Br Guidio Leonarde Ginting Guidio Leonarde Ginting Hasibuan, Nelly Astuty Hendrikus Daely Ida Rizky Nasution Ihsan Ihsan Ilham Mubarik Ilham, Safarul Imam Saputra Imam Saputra Indini, Dwina Pri Irfan Nainggolan Iskandar Zulkarnain Johanes Mario Purba Keke Annisa Siregar Kurnia Ulfa M Mesran Manik, Lastri Meiliyani Br Ginting, Meiliyani Br Mesran, Mesran Miftahul Khairat Miko Putra Haposan Tinambunan Muhammad Syahrizal Murdani Murdani, Murdani Nainggolan, Dian Wichita Nainggolan, Laksono Nasib Marbun Nasib Sihombing Nastiti, Sindy Nelly Astuti Hasibuan Nona Oktari Noveriang Ndruru Novida Sari, Sri Nurjannah Oktari, Nona Pitriani Piliang Purba, Andrean Saputra Purba, Bister Purba, Roulina Agape Radius Kharisman Ndruru Raheliya Br Ginting, Raheliya Br Rahmi Danur, Surizar Rama Prameswara Ritonga Refika Ratna Dilla Rian Syahputra Rivalri Kristianto Hondro Rizqi Dwikunti Siregar, Dini Roni Yunis Russy Amelia Samueal Damanik Santri W Pasaribu Saragi, Naomi Labora Saragih, Soumi Rohmah Sarumaha, Lukas Sarwandi Wandi Sawitri Sawitri Selly Armasari Sihotang, Dahner Ismanda Bertenius Simatupang, Meylita Putri Sirait, Pahala Siregar, Tesa Aurelia Sitepu, Harun Rivaldo Soeb Aripin Suginam Suharti Suharti Sulistianingsih, Indri Surya Darma Nasution Susi Mardiana Giawa Sussolaikah, Kelik Tesa Aurelia Siregar Ulva Rizky Amanda Virdyra Tasril Yohana Br Ginting, Dewi Zahri Hubby Ramadhani