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All Journal Jurnal Ekonomi SOROT: Jurnal Ilmu-ilmu Sosial Jurnal Online Mahasiswa (JOM) Bidang Ilmu Ekonomi Jurnal Tepak Manajemen Bisnis Dinamika Ilmu IJEBA (International Journal of Economic, Business & Applications) Jurnal Penelitian Hukum Legalitas JOURNAL OF APPLIED BUSINESS ADMINISTRATION Building of Informatics, Technology and Science Jurnal Disrupsi Bisnis Journal of Applied Sciences, Management and Engineering Technology (JASMET) Jurnal Bisnis Mahasiswa Bulletin of Information Technology (BIT) Healthy Tadulako Journal (Jurnal Kesehatan Tadulako) Indonesian Journal of EFL and Linguistics Journal of Computer Science and Information Systems (JCoInS) Journal of Student Development Information System (JoSDIS) Jurnal Economica: Media Komunikasi ISEI Riau Jurnal Bisnis Kompetitif Literasi: Jurnal Pengabdian Masyarakat dan Inovasi West Science Interdisciplinary Studies JAAMTER : Jurnal Audit Akuntansi Manajemen Terintegrasi Jurnal Manajemen Pendidikan Islam InJEBA : International Journal of Economics, Business and Accounting TAFASIR CSRID Jurnal Manajemen Dayasaing Jurnal Bisantara Informatika
Samsir Samsir, Samsir
Fakultas Ekonomi Universitas Riau
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : Building of Informatics, Technology and Science

 1 
Implementation of the Simple Additive Weighting Method in Determining Recipients of Subsidized Food Materials for Poor Families Kusmanto, Kusmanto; Budi, Eko Setia; Samsir, Samsir; Hariska, Elvia; Ginting, Guidio Leonarde
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 (433.804 KB) | DOI: 10.47065/bits.v3i3.1097

Abstract

In accordance with the rules that have been set from the Village Office so that the community gets subsidized food, it must comply with the specified criteria. The Village Office will determine who is selected to receive subsidized food and distribute it to poor families. As a tool that can be used to determine someone who is eligible to receive subsidized food, a decision support system is needed. In the decision support system there are several methods, one of which can be used is the SAW (Simple Additive Weighting) method. In this research
Implementation Naïve Bayes Classification for Sentiment Analysis on Internet Movie Database Samsir, Samsir; Kusmanto, Kusmanto; Dalimunthe, Abdul Hakim; Aditiya, Rahmad; Watrianthos, Ronal
Building of Informatics, Technology and Science (BITS) Vol 4 No 1 (2022): June 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (376.705 KB) | DOI: 10.47065/bits.v4i1.1468

Abstract

A film review is a subjective opinion of someone who has different feelings about each film. As a result, film enthusiasts will struggle to assess whether the film meets their requirements. Based on these issues, sentiment analysis is the best way to fix them. Sentiment analysis, also known as opinion mining, is the study of assigning views or emotional labels to texts in order to determine if the text contains positive or negative thoughts. The Nave Bayes method was chosen because it can classify data based on the computation of each class's probability against objects in a given data sample. The best model was created utilizing data without lemmatization, 500 vector sizes, and Nave Bayes classification, with an accuracy of 78.96 percent and a f1-score of 78.81 percent. Changes in vector size affect the system's capacity to foresee positive and negative sentiments. The difference in accuracy and recall values shows that when vector size 300 is utilized, the precision and recall outcomes are lower than when vector size 500 is used.
Applying Data Mining Techniques to Investigate the Impact of Smoking Prevalence on Life Expectancy in Indonesia: Insights from Random Forest Models Dalimunthe, Abdul Hakim; Samsir, Samsir; Subagio, Selamat; Siagian, Taufiqqurrahman Nur; Watrianthos, Ronal
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5201

Abstract

This study investigates the relationship between smoking prevalence and life expectancy in Indonesian provinces using data mining techniques, specifically focusing on the application of random forests. The primary objective is to quantify the potential impact of reducing smoking prevalence on population health outcomes. Data were sourced from the Indonesian Central Bureau of Statistics, which included life expectancy and smoking prevalence data from 2021 to 2023. The methodology involved aggregating life expectancy data from the district to the province level, followed by the application of a random forest model to predict life expectancy based on smoking prevalence and other socioeconomic indicators. Key findings indicate a weak to moderate negative correlation between smoking prevalence and life expectancy, with higher smoking rates associated with lower life expectancies. Predictive modeling suggests that a reduction in smoking prevalence could lead to significant improvements in life expectancy. For example, a 5% reduction in smoking rates could increase the average life expectancy by approximately 0.3 years, while a 15% reduction could result in an increase of about 0.9 years by 2025. These results underscore the detrimental impact of smoking on population health and highlight the importance of effective tobacco control measures. The predictive models developed in this study provide valuable information for policymakers, enabling targeted public health strategies and resource allocation. This research contributes to the field by demonstrating the utility of data mining techniques in public health and offering a comprehensive analysis of the relationship between smoking and life expectancy in Indonesia. The findings advocate for the urgent implementation of smoking cessation programs to enhance life expectancy and improve public health outcomes
Co-Authors A.A. Ketut Agung Cahyawan W Abd. Rasyid Syamsuri Ainun, Annisa Alamsyah - Alvi Furwanti Alwie Andi Syahputra Anggia, Paramitha Ansar Arifin, Ansar Arsyad Arsyad Arwinence, Arwinence Azhar, Wahyu Azmi, Fauzan Bambang Arianto Berampu, Lailan Tawila Botutihe, Fauziah Dalimunthe, Abdul Hakim Dewita Suryati Ningsih Dian, urnamasari Diana Eravia Eko Setia Budi Esti Handayani, Dwi Fadillah, Erwin Febriwanti, Febriwanti Gatot Wijayanto Guidio Leonarde Ginting Handayani, Tut Harahap, Fauji Hariska, Elvia Hasbullah Hasbullah Hasri, Mulya Helfiyana, Helfiyana I Ketut Gunarta Isyandi, B. Iwan Fitrianto Rahmad Iwan, Daulay N Iwan, Daulay Nauli Jayanti, Elda Kelvin Kelvin Khalif, Arif Khalilurrahman Khalilurrahman, Khalilurrahman Kusmanto Kusmanto Mardiana Mardiana Marpaung, Radinda Tamara Ayu Marpaung, Rio Jonnes Minarti, Melly Minci, Veronika Yurike MITRA LINDA, MITRA Muhammad Yusril Muslimah, Jannatul Nalapraya, Tresna Nasution, Sya’ral Norhidayati Rahmah, Mariyatul Nur Halimah Nurwati Nurwati Pakpahan, Donok M Panjaitan, Indra Syahputra Paramitha, Anggia Prima Andreas Siregar Primaroni, Oky Putri, Raisa Monica Rahma, Ismiwiya Rahmad Aditiya Rahmad Aditya Recky Riandika Sayandra, Recky Riandika Rezki, Ananda Rio g, Marpaung J.M. Rio, Marpaung Jones Rio, Marpaung Jonnes M Rizqon Jamil Farhas Ronal Watrianthos Rustami, Rustami Ryan, Simatupang Sury Febriansyah Salewe, M Idman Septherine, Putri Sharnuke Asrilsyak Shela, Hasm Riaufa Siagian, Taufiqqurrahman Siagian, Taufiqqurrahman Nur Siregar, Aldi Sajali Siregar, Alisa Yulima Siregar, Eka Maya Putri Sri Restuti Subagio, S. Subagio, Selamat Subagio, Selamet Sulasri, Sulasri Sumarti Sumarti Suntin, Suntin Suseno, Novri Irfan Nur Susi Hendriani Syawalmi, Laily Tahara, Tasrifin Tahir, Tarmizi Tang, Mahmud Tengku Firli Musfar Wahyu Azhar Ritonga Widayatsari, Any Yanuari, Said ZA, Kasman Arifin Zulfadil, Zulfadil Zulfadil, Zulfadil Zulfadil, Zulfadil Zulkarnain Zulkarnain