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Journal : Building of Informatics, Technology and Science

Implementasi Metode MOORA Dengan Pembobotan Rank Order Centroid (ROC) dalam Seleksi Penerimaan Staff Gudang PT. Royal Abadi Sejahtera Zahri Hubby Ramadhani; Nelly Astuti Hasibuan; Dito Putro Utomo
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2073

Abstract

Warehouse staff is a job related to the storage of goods for production or production. Therefore, the person who occupies the position is required to have certain criteria. However, during this time, the warehouse head of PT. Royal Abadi Sejahtera has experienced difficulties in the process of accepting warehouse staff, because there are many applicants who come to apply and do not meet the expected criteria. The problem faced in this research is that the company is still doing the selection by looking at prospective staff willing to work, the work does not only require a level of willingness to work, but has skills, education, work experience, attitude in work and good communication. Decision Support System is a system that is used to assist in the decision-making process in an organization. In the process the Decision Support System uses several methods used in the decision-making process and one of them is the MOORA (Multi Objective Optimization on the Basis of Ratio Analysis) method and the ROC (Rank Order Centroid) method for the weighting process. The benefits that the author wants to achieve in this study are to assist the company in facilitating the process of accepting warehouse staff as input for companies in making decisions using a decision support system to provide a more objective assessment resulting from the Decision Support System.
Penerapan Metode Profile Matching (PM) Dalam Menentukan Pemilihan Duta Generasi Berencana (GenRe) Atira Nabila; Nelly Astuti Hasibuan; Dito Putro Utomo
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2074

Abstract

This study examines the selection of Generation Planning Ambassadors (GenRe) subjectively assessed so that there are several candidates who have the same weighting criteria values, making it difficult for the committee to determine which one is the best. Generation Planning (GenRe) in Pangakalan Koto Baru District by using a decision support system by applying the profile matching method. The final result of the research will be able to simplify the work of the selection process for the Generation Planned Ambassador (GenRe). This method compares the actual data value of a profile to be assessed with the expected profile value, so that the difference in competence (GAP), the smaller (GAP) ) is generated, the greater the value weight, which means it has a greater chance of being recommended for selection. There are 5 (five) criteria used for this calculation, namely Public Speaking, English, Insight, Attitude, and Initiative. The results of this study were carried out by assessing based on ranking using the Profile Matching method, from the 9 (nine) prospective ambassadors there were 2 (two) male ambassador candidates and 7 (Seven) female ambassador candidates. Of the male ambassador candidates, the highest score was Fadlan Ikhsan with a score of 4.48 and the lowest was Rafli Jasna Aziz with a score of 3.48. And for female ambassador candidates with the highest score is Syakina Aulia with a score of 5 and the lowest score is Gisti Rahmatika with a score of 3.5. The results of the ranking of the planned generation of ambassadors are seen from the highest score
Penerapan Metode Profile Matching Dalam Sistem Pendukung Keputusan Pemilihan Teknisi Terbaik Sawitri Sawitri; Nelly Astuti Hasibuan; Dito Putro Utomo
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2075

Abstract

PT. Mitra Tunggal Perkasa is a distributor company engaged in the marketing of goods sales, the goods sold or marketed are heavy equipment types such as the Shark Komprssor machine. Maintenance on the compressor machine is usually carried out by a technician, in which case PT. Mitra Tunggal Perkasa selects the best technicians and also rewards technicians who will be the best alternative. The selection of the best compressor technician is done to help improve the technician's work power so that it becomes even better than the previous one. To assist the determination or selection in determining someone who deserves to be the best compressor engine technician, a decision support system is needed, and there are lots of criteria that every technician must have as a condition to become the best compressor engine technician. In this study, a case will be raised, namely looking for the best alternative based on predetermined criteria by applying the Profile Matching method. This method compares the actual data value of a profile to be assessed with the expected profile value, so that the difference in competence (GAP) can be seen. selected alternative, so that it can be used by each party in supporting the progress of the organization or company in achieving its goals through making the best decisions. The result of the Decision Support System for the Selection of the Best Mechanical Technician at PT. Mitra Tunggal Perkasa is alternative A2 with a value of 4,755 in the name of "Satish Kumar".
Analisa Penerapan Metode MOOSRA dan MOORA dalam Keputusan Pemilihan Lokasi Usaha Sudarsono, Bernadus Gunawan; Zulkarnain, Iskandar; Buulolo, Efori; Utomo, Dito Putro
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2696

Abstract

In the world of work, competition certainly exists. Especially in the selection of the location of the business being run. The better the location of the place of business, of course, the more competition. In this study, we will discuss the selection of a strategic and appropriate business location. The location of the business greatly affects the development of the business being run, many businesses do not develop (loss) so they have to stop their business because the location of the business is far from residential areas, the location is narrow and so on. To avoid this, we need a system that can solve the problem which is called a decision support system. Decision support system is a structured system in making effective business location selection decisions using methods such as WASPAS, SPI, TOPSIS, WP, SAW, MOORA, MOOSRA, EDAS and many others. The selection of business locations used the MOOSRA and MOORA methods. Both methods are very simple and easy to understand with the assessment based on the criteria used, namely Number of Competitors, Crowd Center, Location Size, Place Rent Price and Location Cleanliness. The results obtained after applying the two methods in the selection of business locations, namely the highest alternative or the first rank is Alternative A1 with a reference value of 0.564
Landscape of AHP Integration in Decision Support Systems: A Bibliometric Analysis of Scopus Publications Saputra, Imam; Mesran, Mesran; Utomo, Dito Putro; Siregar, Annisa Fadillah
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7451

Abstract

This study employs bibliometric analysis to provide a comprehensive overview of the research landscape concerning the integration of the Analytic Hierarchy Process (AHP) and Decision Support Systems (DSS). Utilizing 1770 documents retrieved from the Scopus database (1985-2025) and employing Biblioshiny for analysis, this research examines publication trends, citation patterns, keyword co-occurrence, collaboration networks, and thematic evolution within the field. The findings reveal a significant growth in publications, particularly after 2015, highlighting the increasing scholarly interest. Citation analysis identifies influential works and key contributing countries. Keyword analysis underscores "decision support systems," "analytic hierarchy process," and "decision making" as central themes, with emerging interest in areas like "artificial intelligence." Collaboration network analysis illustrates significant co-authorship patterns and international collaborations. Thematic mapping further categorizes research themes, identifying well-established "Motor Themes" (e.g., "decision support system," "GIS") and fundamental "Basic Themes" (e.g., "decision making," "analytic hierarchy process"). This study provides valuable insights into the intellectual structure, evolutionary trends, and collaborative dynamics of the AHP-DSS integration research field, highlighting its robust nature and potential future directions.
Animal Caregiver Selection by Applying ARAS Method Decision Support System and Entropy Weighting Utomo, Dito Putro; Syahrizal, Muhammad; Hondro, Rivalri Kristianto; Saputra, Imam
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7048

Abstract

Animal care is a profession that is responsible for taking good care of animals or checking the condition of animals for the purpose of animal health. To get a qualified animal care worker according to the company's needs, it takes quite a long time, because animal care workers who apply for a job at a company must first go through several tests in order to meet the criteria required by the company. So that animal care workers are needed and required to care for animals, maintain their health and pay attention to the nutrition of the animals. So that there is no extinction of protected animals. The current animal care worker acceptance procedure in the wildlife park is that applicants submit identity files, if they pass the applicant's files, they take an interview test and the last test, the applicant must practice in the field directly to find out how well the applicant is able to adapt to animals. In calculating the value, problems often occur in this acceptance process. A decision support system (DSS) is an interactive information system that provides information, modeling, and data manipulation. In this case, the author uses the Entropy method and the ARAS (Additive Ratio Assessment) method to solve it. The Entropy method can be used to calculate weights based on data characteristics in the criteria, the higher the variation between data in the criteria, the higher or more important the weight of the criteria. While the ARAS (Additive Ratio Assessment) method is used for ranking. The use of the Entropy method as a weighting aims to ensure that the weighting process is carried out based on objective value assignment. In the application of the Entropy Method, a weighting of the criteria value is produced where the criteria with the highest to lowest values ​​are Certificate, Work Experience, Age, Interview and Education with the highest value being 0.768 and the lowest being 0.021. Then the process of applying the selection of animal nurses using the ARAS method obtained the result that alternative A1 was selected as an animal nurse with a value obtained of 0.0816.
SMOTE and BERT Approaches for Handling Class Imbalance in Sentiment Analysis of the CoreTax Application on Big Data Ginting, Meiliyani Br; Surbakti, Asprina Br; Ilham, Safarul; Utomo, Dito Putro; Ginting, Raheliya Br
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.8310

Abstract

Coretax is a tax information system developed by the Directorate General of Taxes (DJP) to support digital and integrated tax administration processes, covering everything from taxpayer registration to reporting and auditing. Although it was designed to improve efficiency, transparency, and accuracy in tax management, its implementation has sparked mixed reactions among the public due to various technical challenges and the complexity of the annual tax reporting process. This situation highlights the need for a sentiment analysis that can objectively capture public perceptions of the system’s performance. In this study, Natural Language Processing (NLP) and Machine Learning techniques were applied to analyze 3,000 tweets from Twitter (X) related to Coretax. One of the main issues identified in the dataset is class imbalance, where positive sentiments significantly outnumber negative and neutral ones, leading to biased classification results. To address this issue, the Synthetic Minority Over-sampling Technique (SMOTE) was used to balance the dataset by generating synthetic samples for the minority classes. The BERT model was then employed for sentiment classification because of its strong ability to understand contextual meaning through its transformer-based architecture. Experimental results show that before applying SMOTE, the BERT model achieved an accuracy of 77%, which increased to 80% after SMOTE was implemented, along with improvements in precision, recall, and F1-score, particularly for the minority classes. These findings demonstrate that the combination of SMOTE and BERT significantly enhances the performance of sentiment analysis in understanding public responses to Coretax. This approach can serve as a valuable reference for evaluating and improving tax digitalization policies, ensuring they are more effective, inclusive, and responsive to public needs.
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 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 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 Siswahyudianto 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