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All Journal Bulletin of Electrical Engineering and Informatics Format : Jurnal Imiah Teknik Informatika JOIV : International Journal on Informatics Visualization Tech-E Jurnal Ilmiah FIFO Jurnal CoreIT BAREKENG: Jurnal Ilmu Matematika dan Terapan JITK (Jurnal Ilmu Pengetahuan dan Komputer) Technomedia Journal Riau Journal of Empowerment The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) KOMPUTIKA - Jurnal Sistem Komputer Jurnal Manajemen Informatika Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Tekno Kompak Building of Informatics, Technology and Science Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer IJAIT (International Journal of Applied Information Technology) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Sisfotek Global Journal of Computer System and Informatics (JoSYC) Community Development Journal: Jurnal Pengabdian Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) JiTEKH (Jurnal Ilmiah Teknologi Harapan) Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Ilmiah Infrastruktur Teknologi Informasi Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer EXPLORER J-Intech (Journal of Information and Technology) BEES: Bulletin of Electrical and Electronics Engineering Jurnal Sisfotek Global Jurnal Telematics and Information Technology (TELEFORTECH) Bulletin of Data Science Jurnal Ilmiah Sistem Informasi Akuntansi (JIMASIA) Paradigma Journal of Engineering and Information Technology for Community Service Journal of Computing and Informatics Research JEECS (Journal of Electrical Engineering and Computer Sciences) Jurnal Ilmiah Informatika dan Ilmu Komputer Journal of Informatics, Electrical and Electronics Engineering Jurnal INFOTEL Bulletin of Informatics and Data Science Jurnal Ilmiah Computer Science CHAIN: Journal of Computer Technology, Computer Engineering and Informatics Journal of Data Science and Information System Journal of Artificial Intelligence and Technology Information Journal of Information Technology, Software Engineering and Computer Science Jurnal Media Jawadwipa Bulletin of Artificial Intelligence International Journal of Informatics and Data Science Journal of Decision Support System Research Journal of Information Technology
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Kombinasi Pembobotan PIPRECIA-S dan Metode SAW dalam Pemilihan Ketua Organisasi Sekolah Setiawansyah Setiawansyah; Very Hendra Saputra
Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM) Vol. 2 No. 1 (2023): Volume 2 Number 1 March 2023
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jima-ilkom.v2i1.16

Abstract

This study aims to select the head of the school organization using the SAW method and PIPRECIA-S weighting, so that the assessment results in the weighting of criteria are more objective based on calculations from the PIPRECIA-S weighting method. The results of the election of the head of the school organization using the SAW method and the weighting of PIPRECIA-S recommended Jamaludin as a candidate for the head of the school organization because the final results of the ranking got Rank 1 with a total score of 1,821. Rank 2 was obtained by Bustomi with a final score of 1,763, rank 3 was obtained by Budiman with a final value of 1,698. The test results based on filling out questionnaires from each category 73% strongly agree, 25% agree, 2% are sufficient, and 0% disagree, so that they can be used in determining candidates for organizational chairman.
UMKM Class Determination Support System Using Profile Matching Setiawansyah Setiawansyah; Adhie Thyo Priandika; Bustanul Ulum; Ade Dwi Putra; Dyah Ayu Megawaty
Bulletin of Informatics and Data Science Vol 1, No 2 (2022): November 2022
Publisher : PDSI

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

Abstract

UMKM are businesses run by individuals, households, or small business entities. The classification of MSMEs is usually carried out with limits on turnover per year, the amount of wealth or assets, and the number of employees. Determining the UMKM class using the profile matching method which can make effective decisions on existing problems. With the decision support system to determine the class of UMKM in determining the class of UMKM by looking at the highest value of the ranking results based on several aspects of the assessment including turnover, assets, human resources, marketing, and permits. The results of the calculation for the assessment of the Micro UMKM class for PT Hasta Karya Nugraha are 1.5275 for the Micro UMKM Class Appropriate because it passes the minimum standard value for Micro MSMEs, the Small MSME Class for PT Hasta Karya Nugraha is 2.2975 Appropriate because it passes the minimum standard value for Small UMKM, and The Small UMKM class for PT Hasta Karya Nugraha is 2.3 Not suitable because it does not pass the minimum standard value for Medium UMKM. As for the results of the calculation of the assessment of the Micro UMKM class for CV Permata Jaya, namely 0.54 the Micro MSME Class is Appropriate because it passes the minimum standard value for Micro MSMEs, the Small UMKM Class for CV Permata Jaya is Appropriate because it passes the Small MSME minimum standard value, and the Small UMKM Class for CV Permata Jaya. CV Permata Jaya which is 1.62 Appropriate because it passes the minimum standard value of Medium UMKM. The conclusion of the assessment results of the application of the profile matching method to determine UMKM to move up the class for PT Hasta Karya Nugraha is in the Micro class, and CV Permata Jaya is in the Middle class.
Implementation of Operational Competitiveness Rating Analysis (OCRA) and Rank Order Centroid (ROC) to Determination of Minimarket Location Ida Mayanju Pandiangan; Mesran Mesran; Rohmat Indra Borman; Agus Perdana Windarto; Setiawansyah Setiawansyah
Bulletin of Informatics and Data Science Vol 2, No 1 (2023): May 2023
Publisher : PDSI

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Abstract

Minimarket location placement is one of the main capital for the business to progress and develop. In determining the location of the minimarket, various considerations must be taken so that nothing is fatal to the sustainability of the business. The problem that occurs in the company in choosing the placement of minmarket locations, namely the various locations that are chosen, each location has its advantages and disadvantages, each of which can affect the analysis of results and takes a long time to make a decision. So that requires a system that can provide a solution to this problem. In this case the resulting system is a system that is useful for determining location placement for minimarkets using the ROC method as its weighting and the OCRA method as a decision generator. This system can provide a solution in determining the location of minimarkets, from various existing locations. The results of each alternative are more objective and definitive in determining the location of minimarkets in a computerized way. For this reason, it is necessary to have supporting criteria for using a decision support system. Determination of importance weight values on conflicting criteria is generated through a weighting method, namely ROC or Rank Order centroid. The OCRA method or Operational Competitiveness Rating Analysis is a method that can calculate and produce rankings efficiently so that the resulting decisions are accurate. The results obtained from the utilization of this system determine the location of minimarkets using the OCRA method and ROC weighting as well as various conflicting criteria determined by the company and development management in Lubuk Pakam resulting in the highest preference value of 0.673 as a location that is suitable for use as a minimarket
Sistem Pendukung Keputusan Dalam Memilih Bibit Kedelai Menggunakan Kombinasi Metode TOPSIS dan ROC Heni Sulistiani; Untoro Adji; Sufiatul Maryana; Setiawansyah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1339

Abstract

To increase agricultural yields, seed selection is very important, one of which is in soybean plants, the problem that arises is the absence of a decision support system model in determining good soybean seeds for soybean farmers. So, farmers only choose existing soybean seeds based on the recommendations of fellow soybean farmers. This study aims to conduct a combination of ROC and TOPSIS can help in managing the complexity of determining agricultural seeds more efficiently. This is because ROC helps in sequencing variables, whereas TOPSIS helps in choosing the optimal alternative. This combination allows stakeholders to make more informed and rational decisions. The ROC method is a multivariate analysis technique used to analyze data that involves sorting or ranking variables measured in a group or population. ROC can be an effective analytical tool in helping stakeholders optimize their strategies or policies in a variety of situations and industries that require a deep understanding of data sequencing or ranking. The Technique for Order Preference by Similarity to Ideal Solution method or often known as the TOPSIS method is a decision-making analysis approach used to assist stakeholders in evaluating alternatives based on a number of predetermined criteria. The combination of ROC and TOPSIS can provide a deeper understanding of the structure of relationships between variables and their impact on alternative rankings. Based on the results of the ranking of agricultural seeds that get 1st Rank, namely Grobongan with a value of 0.54047, 2nd Rank, namely Anjasmoro with a value of 0.5, 3rd Rank, namely Detap 1 with a value of 0.43828, 4th Rank, Dena 1 with a value of 0.43457, and 5th Rank, namely Dering 1 with a value of 0.40553.
Multiple Attribute Decision Making Menggunakan Metode TOPSIS Dalam Penentuan Staff Marketing Terbaik Setiawansyah Setiawansyah; Very Hendra Saputra; Sanriomi Sintaro; Ahmad Ari Aldino
Bulletin of Artificial Intelligence Vol 2 No 2 (2023): October 2023
Publisher : Graha Mitra Edukasi

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Abstract

Multiple Attribute Decision Making (MADM) is an approach used in decision making to select the best alternative from a number of given criteria or attributes. This research aims to apply the TOPSIS method in selecting the best marketing staff so that it can become a reference and benchmark for companies in selecting the best marketing staff using a decision support system model. The results of the ranking of the selection of the best marketing staff who got rank 1 with a value of 0.644, namely Ahmad, rank 2 with a value of 0.539, namely Hermawan, rank 3 with a value of 0.529, namely Santoso, rank 4 with a value of 0.443, namely Jayanti, rank 5 with a value of 0.399, namely Heru.
Student Ranking Based on Learning Assessment Using the Simplified PIPRECIA Method and CoCoSo Method Sitna Hajar Hadad; Dedi Darwis; Arie Qurania; Ahmad Ari Aldino; Abhishek R Mehta; Yuri Rahmanto; Setiawansyah Setiawansyah
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4544

Abstract

The problems that occur in determining the best students based on the learning process of the assessment process are still based on the academic scores of students and have not considered the learning process carried out by students. This study aims to apply the Combined Compromise Solution (CoCoSo) method in ranking students based on learning assessment using criteria of academic progress, problem-solving ability, mastery of skills, independence, motivation and positive attitude, adaptability, and for weighting the criteria used to apply the Simplified PIPRECIA (Pivot Pairwise Relative Criteria Importance Assessment) weighting method. The Simplified PIPRECIA method is particularly useful in situations where there are diverse criteria to be considered and complex decisions must be made taking into account the preferences and interests of various stakeholders. The Combined Compromise Solution Method is useful when there are conflicts in various criteria that need to be considered in the decision-making process. With this approach, each criterion is weighted and carefully calculated, so that the resulting decisions reflect comprehensive considerations that can meet various requirements and constraints. Based on the results of student rankings based on assessments in learning in the table above, rank 1 was obtained by students with Student ID 1211313 with a final grade of 6.487, rank 2 was obtained by students with Student ID 1211316 with a final grade of 6.402, and rank 3 was obtained by students with Student ID 1211314 with a final grade of 5.814.
Combination of CRITIC Weighting Method and Multi-Atributive Ideal-Real Comparative Analysis in Staff Admissions Waqas Arshad, Muhammad; Mesran; Setiawansyah, Setiawansyah; Suryono, Ryan Randy; Rahmanto, Yuri
Explorer Vol 4 No 2 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v4i2.1428

Abstract

Staff recruitment is a critical process in human resource management where organizations select and place individuals who fit the needs and goals of the company. This process involves identifying position needs, job postings, screening applicants, interviewing, skills evaluation, and making a final decision to determine the most suitable employee. The integration of CRITIC and MAIRCA allows the staff selection process to be more objective and systematic. CRITIC helps in assessing the importance of each criterion by considering its relevance, thus ensuring that the evaluation is not based on just one dimension. On the other hand, MAIRCA provides a comprehensive framework by comparing each candidate against the desired ideal standards and their actual achievements in relevant attributes. The combination of these two methods not only strengthens accuracy in staff selection, but also ensures that decisions are made in accordance with the organization's strategic goals to achieve optimal performance and effectiveness. The ranking results obtained the results of rank 1 with a value of 0.0824 obtained by Alternative G, rank 2 with a value of 0.0798 obtained by Alternative B, and rank 3 with a value of 0.0778 obtained by Alternative C.
Implementation of EDAS Method in the Selection of the Best Students with ROC Weighting Darwis, Dedi; Sulistiani, Heni; Megawaty, Dyah Ayu; Setiawansyah, Setiawansyah; Agustina, Intan
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 20, No 2 (2023): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v20i2.7904

Abstract

This study aims to provide recommendations for the best students to be selected using the EDAS method and ROC weighting, so as to help schools in decision making. The EDAS method requires a lot of input, and preference must be precise in the determination of the weight of the criteria. To fix the problem of weighting criteria in the EDAS method, the Centroid Rank Order (ROC) method is used. ROC is a simple method used to assign weight values to each criterion used. The results of this study provide recommendations for the best students to be selected using the EDAS method and ROC weighting, so as to help schools in decision making. The application of the EDAS method in the selection of exemplary student candidates resulted in exemplary prospective students obtained on behalf of Hadi Santoso with a final score of 0.70885 and obtained 1st rank. The results of these recommendations can help the school determine the selection of the best students by applying the EDAS method and ROC weighting.
Application of Support Vector Machine (SVM) Algorithm in Classification of Low-Cape Communities in Lampung Timur Aldino, Ahmad Ari; Saputra, Alvin; Nurkholis, Andi; Setiawansyah, Setiawansyah
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (358.539 KB) | DOI: 10.47065/bits.v3i3.1041

Abstract

Classification is a technique for grouping and categorizing specific standards as material for compiling information, making conclusions, or making decisions. This paper discusses data classification for underprivileged communities in Tanjung Inten, Purbolinggo, East Lampung using the Support Vector Machine (SVM) algorithm, then grouped into two label classes, namely the less fortunate and capable label classes. From the data that has been collected, 1154 data. The data goes through processing, scoring, labeling, and testing, producing two classes of results, namely less fortunate and capable. From the test data using the Support Vector Machine (SVM) method, the accuracy score is 97%, the precision score is 97%, the Recall score is 100%, and the F1-Score is 98%. This test resulted in a proportion of classification with the capable label is 87% and less fortunate label is 13%
Decision Support System for Determining the Best Internship Students Using the Combined Compromise Solution Method Pasaribu, A. Ferico Octaviansyah; Aldino, Ahmad Ari; Surahman, Ade; Setiawansyah, Setiawansyah
Building of Informatics, Technology and Science (BITS) Vol 5 No 3 (2023): December 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i3.4231

Abstract

Interns are individuals who are undergoing a period of practical learning in an organization or company as part of their educational curriculum. During the internship, students have the opportunity to apply the knowledge they learn in class to real-world situations, as well as gain valuable work experience. The selection of the best intern can involve several problems or challenges. One of them is the difficulty in evaluating students' practical skills based solely on their academic performance. The Decision Support System (DSS) to determine the best internship students using the Combined Compromise Solution Method provides a holistic approach in the selection process. This method combines elements of the Compromise Solution Method that consider compromise solutions between alternatives. With this comprehensive approach, DSS can assist institutions or companies in selecting internship students that best suit their needs and expectations, as well as ensure the success of internships that are beneficial to both parties. The results of the ranking of the best internship student alternatives showed that rank 1st with a value of 5.7847 was obtained by Jonathan, rank 2nd with a value of 5.2625 was obtained by Handoko R, and rank 3rd with a value of 4.6117 was obtained by M. Ali Fikri. The results of this ranking help companies determine the best internship students by applying the combine compromise solution method
Co-Authors Abhishek R Mehta Ade Dwi Putra Ade Surahman Adhie Thyo Priandika Adi Sucipto, Adi Aditia Yudhistira Agus Perdana Windarto Agus Wantoro Agustina, Intan Ahdan, Syaiful Ahmad Ari Aldino Ahmad Ari Aldino Ahmad Ari Aldino Ahmad Ari Aldino Ahmadfauzy Alfry Aristo Jansen Sinlae Alita, Debby Amalia, Zahrina Andi Nurkholis Andika, Rio Aniyanti Tafonao An’ars, M. Ghufroni Arfinia Rahma Ari Sulistiyawati Ari Sulistiyawati Ari Sulistiyawati Ariany, Fenty Arie Qur’ania Arief Budiman Arshad, Muhammad Waqas Arsi Hajizah Asistyasari, Ayuni Ayu Megawaty, Dyah Bustanul Ulum Chandra, Iryanto Damayanti Damayanti Damayanti, Damayanti Daniarti, Yeni Daniel Prasetyo Tarigan Deas Andrian Dwijaya Debby Alita Dedi Darwis Dedi Triyanto Desyanti Dinda Titian Lestari Dodi Siregar Dodi Siregar Dwi Satria, M. Najib Dyah Aminatun Dyah Ayu Megawaty Eko Bagus Fahrizqi Erlin Windia Ambarsari Fadila Shely Amalia Fajar Irvansyah Faruk Ulum Febrianus Gea Ferico Octaviansyah Pasaribu, Ahmad Fernando, Yusra Fikri Hamidy Gibtha Fitri Laxmi Hamdan Sobirin, Muhammad Heni Sulistiani Heni Sulistiani Ida Mayanju Pandiangan Imam Ahmad Imam Ahmad Isnain, Auliya Rahman Jumaryadi, Yuwan Junhai Wang Junhai Wang Junhai Wang Kiki Septiani Kurniawan, Arsy Laurent Nababan Mahendra, Ferdian Jerry Mahesa Raihan Rifqi Mandasari, Berlinda Marzuki, Dwiki Hafizh Megawaty, Dyah Ayu Merlin Puspita Sari Mesran Mesran Mesran, Mesran Mohammad Taufan Asri Zaen Muhaqiqin muhaqiqin Ni Komang Ratih Kumala Nirwana Hendrastuty Nuari, Reflan Nuralia Nuralia Nurman Fadhlullah nurnaningsih, Desi Nuzuliarini Nuris Octaviansyah, A. Ferico Oprasto, Raditya Rimbawan Palupiningsih, Pritasari Parjito Parjito Pasaribu, A. Ferico Octaviansyah Pasha, Donaya Permata, Permata Pramuditya, Andri Prastowo, Kukuh Adi Purbha Irwansyah, Irsyad Pustika, Reza Putra, Ade Dwi Putra, Rulyansyah Permata Putri Sukma Dewi Putri Sukma Dewi Qadhli Jafar Adrian R Metha, Abhishek Rahmadianti, Fitrah Amalia Rahman, Miftahur Rasli, Roznim Mohamad Reflan Revife Purba Rilo Nur Devija Rini Nuraini Riska Aryanti Riska Aryanti Rohmat Indra Borman Romadhoni, Randi Roswita Daeli Ruziana binti Mohamad Rasli Ryan Randy Suryono S. Samsugi Safi, Mudar Sanriomi Sintaro Saputra, Alvin Setiawan, Dandi Setyani, Tria Sinta, Ratna Sari Roma Siti Mahmuda Sitna Hajar Hadad Sofiansyah Fadli Sri Agustiani Br Siburian Subhan Subhan Sufiatul Maryana Sufiatul Maryana Sumanto, Sumanto Surahman, Ade Susanto, Erliyan Redy Syaiful Ahdan Trisnawati, Fika Ulum, Faruk Untoro Adji Very Hendra Saputra Very Hendra Saputra Wahyudi, Agung Deni Wang, Junhai Waqas Arshad, Muhammad Wibawa, Yohanes Eka Widiyanti, Adella yasin, ikbal Yuliani, Asri Yuri Rahmanto