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Sihombing, Volvo
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Analysis Of Public Interest In Smartfren SIM Cards Using The K-Nearest Neighbors Method Tawanta Natalia Sembiring, Sri; Sihombing, Volvo; Irmayani, Deci
International Journal of Science, Technology & Management Vol. 5 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i5.1177

Abstract

The use of Smartfren SIM cards is increasing along with the public's need for fast and stable internet services. However, a deep understanding of public interest in the SIM card is necessary to optimize marketing strategies and increase sales. Proper analysis can help companies identify potential target markets and develop effective marketing strategies. We chose the K-Nearest Neighbors method to analyze public interest in using Smartfren SIM cards. This study aims to develop and evaluate the K-Nearest Neighbors model in predicting public interest in using Smartfren SIM cards. This study uses a dataset containing information about Smartfren SIM card users. We divide the data into two sets: a training set for model building and a test set for evaluating model performance. We apply the K-Nearest Neighbors method to classify the data into two categories: interested and not interested. We evaluate the model performance using accuracy, precision, recall, and F1-score metrics. We present the evaluation results as a confusion matrix. The developed K-Nearest Neighbors model showed excellent performance with an accuracy of 94.29%, a precision of 94.20%, a recall of 100%, and an F1-score of 97.01%. These results indicate that the K-Nearest Neighbors model is effective in predicting people's interest in Smartfren SIM cards. The high recall value indicates that the model is able to identify all interested individuals without missing any, while the high precision value indicates that the model rarely makes false positive prediction errors. This study concludes that the K-Nearest Neighbors method is very effective for use in analyzing people's interest in using Smartfren SIM cards. We can rely on the developed model's strong performance for real-world applications in marketing strategies.
Implementation of K-Nearest Neighbors Algorithm in Analyzing Public Interest in Shoping at Supermarkets Siti Kholijah, Siti Kholijah; Sihombing, Volvo; Irmayani , Deci
International Journal of Science, Technology & Management Vol. 5 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i5.1183

Abstract

People's shopping patterns and behaviors continue to develop along with technological advances and lifestyle changes, thus requiring retail business actors, especially supermarkets, to better understand their customers' interests and preferences. In this context, accurate analysis of customer shopping interests is very important to improve customer satisfaction and optimize marketing strategies. One solution that can be implemented to analyze people's shopping interests is the application of the K-Nearest Neighbors algorithm, a simple yet effective nearest neighbor-based classification method for recognizing patterns from existing data. This study aims to apply the K-Nearest Neighbors algorithm to classify people's interest in shopping at supermarkets. This study also evaluates the effectiveness and performance of the algorithm in the context of business decision-making in the retail sector. The research methodology includes collecting data on people's shopping interests, data pre-processing, implementing the K-Nearest Neighbors algorithm, and evaluating model performance using evaluation metrics such as accuracy, precision, recall, and F1-score. The results of this study indicate that the K-Nearest Neighbors algorithm is able to achieve an accuracy of 88%, with precision, recall, and F1-score all reaching 92.86%. These results indicate that the K-Nearest Neighbors model is very effective in classifying people's shopping interests, with a low error rate. The resulting confusion matrix also shows the model's ability to identify customers who are interested in shopping with little prediction error. This study concludes that we can rely on the K-Nearest Neighbors algorithm to analyze people's shopping interests in supermarkets. This model not only shows good performance in classification but also has great potential to be implemented in recommendation systems and customer segmentation in the real world. This study contributes to the development of consumer behavior analysis methods in the retail sector, as well as providing a basis for further research to explore other algorithms or combinations of techniques to improve the accuracy and effectiveness of classification models.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN FITNESS CENTRE TERBAIK MENGGUNAKAN METODE COMPLEX PROPORTIONAL ASSESSMENT Aurianda, Rieke; Sihombing, Volvo; Juledi, Angga Putra
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1547

Abstract

This study aims to design and implement a Decision Support System (DSS) to help the people of Bagan Batu Regency in choosing the best fitness center. The increasing awareness of a healthy lifestyle has triggered the development of the fitness industry, but the many choices often make it difficult for people to determine the right choice. The Complex Proportional Assessment (COPRAS) method is used in this study because of its ability to evaluate various alternatives based on benefit and cost criteria. Five criteria are considered, namely sports facilities, instructor quality, operating hours, membership fees, and location. Data were collected from several fitness centers in Bagan Batu and processed through a normalization and weighting process. Based on the results of data processing using this method, recommendations for the best fitness centers were obtained, namely FC_04, FC_08, and FC_07. The results of this study indicate that the COPRAS method can simplify and accelerate the provision of recommendations for selecting the best fitness location in Bagan Batu Regency.
SISTEM PENDUKUNG KEPUTUSAN PRIORITAS PESERTA PERTUKARAN MAHASISWA MENGGUNAKAN METODE WASPAS Alam, Dewi Pathimah; Sihombing, Volvo; Juledi, Angga Putra
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1540

Abstract

This study aims to develop a Decision Support System (DSS) based on the WASPAS (Weighted Aggregated Sum Product Assessment) method to assist Labuhan Batu University in selecting the best students to participate in the student exchange program. Manual selection which is often subjective and prone to bias is a problem that needs to be overcome. The WASPAS method was chosen because of its ability to combine weighted addition and weighted multiplication, resulting in a more comprehensive and objective evaluation. This study includes the stages of problem identification, student data collection, determination of selection criteria, and data processing using the WASPAS method. The criteria used include English language skills, leadership, knowledge, GPA, and achievement. The results of data processing using the method obtained an alternative with the Highest Value, namely A7 with a final result of 122.86582. The results of the study showed that the application of the WASPAS method resulted in a more transparent and objective evaluation compared to the manual selection method. By using this system, it is hoped that the selection process for student exchange program participants will be more efficient and on target.
PENGGUNAAN METODE MABAC PADA SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LOKASI MAGANG TERBAIK Safitri, Nina; Bangun, Budianto; Sihombing, Volvo
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1541

Abstract

This study aims to develop a Decision Support System (DSS) based on the Multiple Attribute Boundary Approximation Area Comparison (MABAC) method to assist Labuhan Batu University students in choosing the best internship location. The main problem faced is the difficulty in determining a strategic and quality internship location due to limited resources. This study uses a quantitative descriptive method involving five main criteria: Location Distance, Company Reputation, Facilities, Suitability of the Internship Program with the Curriculum, and Work Environment. Data were collected through literature, expert consultation, and primary and secondary data analysis. Based on the results of data processing using the MABAC method in this study, 3 best internship locations were obtained, namely locations A9, A4, and A3. The results of the analysis using the MABAC method show the system's ability to provide internship location recommendations based on objective multicriteria assessments. The resulting system can help make it easier for students to choose an internship location that suits their needs.
SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN PEGAWAI BIRO AKADEMIK MENGGUNAKAN MOOSRA Pertiwi, Nur Fajar Kurnia; Munthe, Ibnu Rasyid; Sihombing, Volvo
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1538

Abstract

This study aims to design and develop a decision support system (DSS) for the employee selection process at the academic bureau of Labuhan Batu University using the MOOSRA method. The main issue faced is the use of subjective and non-standardized traditional selection methods, which can reduce the accuracy and efficiency in selecting the right candidates. The method applied in this study is MOOSRA, which can process various selection criteria such as educational qualifications, work experience, information technology skills, communication skills, and discipline. The results of the calculation of values ​​and rankings indicated that alternative A4 was the best candidate, followed by A9 and A1. The results of the study indicate that the use of the MOOSRA method in the decision support system can provide more objective and efficient recommendations in the employee selection process at the academic bureau of Labuhan Batu University.
OPTIMASI PROSES SELEKSI PEGAWAI MENGGUNAKAN SISTEM PENDUKUNG KEPUTUSAN METODE COPRAS Andriyani, Wahyu Fitri; Sihombing, Volvo; Juledi, Angga Putra
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1545

Abstract

This study aims to develop a decision support system (DSS) based on the COPRAS method to help simplify the employee selection process at SPX Express, Rokan Hilir. The challenges faced in the selection process are subjectivity in assessment and non-integration of data, which results in less than optimal selection decisions. The COPRAS method is used to evaluate candidates based on predetermined criteria, such as Personality Tests, Health Tests, Knowledge Tests, Age, and Work Experience. This study involves the stages of determining the weight of the criteria, collecting data, and processing data using the COPRAS method to produce candidate rankings. The results showed that the candidates with the highest rankings were CP_02, CP_01, and CP_05. This DSS system can improve efficiency and objectivity in employee selection decision making.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LOKASI PEMASARAN LAPTOP BEKAS MENGGUNAKAN METODE ARAS Purba, Mila Hanim; Sihombing, Volvo; Irmayani, Deci
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1542

Abstract

This study aims to develop a decision support system (DSS) based on the Additive Ratio Assessment (ARAS) method to help used laptop entrepreneurs in Bagan Sinembah District in determining the optimal marketing location. The problems faced include the selection of business locations that are often done based on intuition without considering data and strategic factors, such as market demand, operational costs, infrastructure, market competition, and economic growth potential. The research method involves identifying the main criteria, collecting alternative location data, normalizing data using the ARAS method, and calculating the utility value for each alternative. The results of the study showed that the three best alternatives for marketing locations were A1 in the first position with a utility value of 0.86507, A4 in the second position with a value of 0.79749, and A6 in the third position with a value of 0.78166. Based on the results of the study, it shows that the ARAS method is effective in dealing with multi-criteria problems, providing recommendations for marketing locations with the highest utility value, which is considered the best choice.
SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KINERJA APARATUR DESA DENGAN METODE TOPSIS Tiara, Dewi; Munthe, Ibnu Rasyid; Sihombing, Volvo
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1543

Abstract

This study aims to develop a decision support system based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to evaluate the performance of village officials more objectively, quickly, and accurately at the Bagan Sari Village Office, South Labuhan Batu Regency. The main problem faced is that the assessment of the performance of officials is still carried out manually, which has the potential to produce subjective and inconsistent data. This study uses a quantitative approach with the following stages: determining criteria and weights, collecting data, and processing data using the TOPSIS method. The criteria used include discipline, attendance, cooperation, and loyalty. The results of the study indicate that the TOPSIS-based system can produce village official performance ratings with high accuracy, minimize bias, and accelerate the decision-making process. This system is expected to be able to provide strategic guidance for the Village Head in improving the quality of service and motivating officials to improve their performance. The implementation of this technology is also a strategic step in modernizing village governance.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN UMKM TERBAIK MENGGUNAKAN METODE PREFERENCE SELECTION INDEX Abdillah, Ihsan; Bangun, Budianto; Sihombing, Volvo
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1546

Abstract

This study aims to design and implement a Decision Support System (DSS) based on the Preference Selection Index (PSI) method to determine the best Micro, Small, and Medium Enterprises (MSMEs) products in Bagan Sari Village, Labuhan Batu Selatan Regency. The main problem addressed is the need for a fair and objective mechanism to assess MSME products based on five key criteria: price, quality, popularity, innovation, and contribution to the village economy. This system is designed to assist the village government in prioritizing support for MSMEs with superior products, thereby significantly impacting the local economy. Through data analysis stages, the system successfully identified the top three alternatives: UMKM_07, UMKM_04, and UMKM_08, which scored the highest in the assessment criteria. These results demonstrate that the PSI method can provide objective and transparent recommendations. By implementing this DSS, the village government can allocate resources more effectively, support MSMEs in enhancing competitiveness, and drive local economic growth. This research is expected to serve as a reference for other villages in managing and advancing MSMEs in a measurable and efficient manner.
Co-Authors Abdillah, Ihsan Abdillah, Syakira Adi, Puput Dani Prasetyo Aditya, Nanda Alam, Dewi Pathimah Alpiansyah, Fredy Andriyani, Wahyu Fitri Angreani Hulu, Linca Elma Popi Ariska, Fevi Aurianda, Rieke Bangun, Budianto Barasa, Kristina Dewi Utami, Yarma Agustya Dwiyanti, Dida Dwiyanti, Didan Efendi, Davina Rizky Fadilla Hasibuan, Intan Gultom, Gregorius Apri K Halawa, Prianus Harefa, Sinema Hasibuan, Dilla Puspita Hasibuan, Mila Nirmala Sari Hasibuan, Sabdi Albi Hendriyanti, Yurika Cici Hia, Faomaha Hutagalung, Charles Efendy Irmayani , Deci Irmayani Irmayani Irmayani, Deci Jannah , Ely Jati, Dewi Sekar Juledi, Angga Putra Juni Yanris, Gomal Lumban Gaol, Tid Verawati Maizura, Safrina Manurung, Romtika mawarni, Putri Sigit Mega, Mega Muhammad Halmi Dar Muliani, Sonia Sri Munthe , Ibnu Rasyid Munthe, Ibnu Rasyid Mustamu, Novilda Elizabeth Nasution, Fitri Aini Pakto, Dedi Pertiwi, Nur Fajar Kurnia Purba, Mila Hanim Purwati Purwati Ramadhani, Siska Rangkuti, M. Andri Gautama Rani Rahayu, Rani Rusmiana, Rusmiana Safitri, Nina Simamora, Rikardo Lasroha siregar, Victor M.M. Siti Kholijah, Siti Kholijah Sitio, Arjon Samuel Sitompul, Joni Awendri Sitorus, Anggiat Selamat Syafitri, Risma Syahputra, Rapian Tasyabila, Tasyabila Tawanta Natalia Sembiring, Sri Tiara, Dewi Tria Wulandari Yanris, Gomal Juni