Comparison of SAW and TOPSIS Methods in Decision Support Systems for Contraceptive Selection
DOI:
https://doi.org/10.35870/ijsecs.v4i2.2815Keywords:
Family Planning (FP), Contraceptive Methods, Decision Support System (DSS), Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Multicriteria Decision Making (MCDM)Abstract
Family Planning (FP) is a crucial initiative in enhancing the quality of life and health of mothers and children. However, selecting the appropriate contraceptive method remains a significant challenge for many couples of reproductive age. This study proposes the development of a web-based Decision Support System (DSS) that integrates the Simple Additive Weighting (SAW) method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) at Zahra Harapan Bunda Clinic. The system aims to provide accurate recommendations for selecting contraceptive methods, record data, monitor users, and remind acceptors of consultation schedules. The results indicate that the SAW method is more consistent and aligns more closely with expert recommendations compared to TOPSIS, with a higher conformity percentage ranging from 66.25% to 92.5%. In contrast, TOPSIS showed a lower conformity percentage, ranging from 25.89% to 78.03%. These findings suggest that SAW more accurately reflects expert recommendations and is therefore considered more effective for selecting contraceptive methods. The study recommends the use of the SAW method for decision-making in contraceptive method selection and suggests further research to expand and validate this approach in a broader range of applications.
Downloads
References
Mulianda, R. T., & Gultom, D. Y. (2019). Pengaruh pemberian konseling KB terhadap pemilihan kontrasepsi jangka panjang (MKJP) di Kelurahan Belawan Bahagia tahun 2018. Jurnal Ilmiah Kebidanan Imelda, 5(2), 651-654.
Brata, A. H., Fanani, L., & Rosalina, L. (2020). Evaluasi usability sistem informasi program KB berbasis Android menggunakan USE questionnaire. Cybernetics, 4(1), 50. https://doi.org/10.29406/cbn.v4i01.1599
Kungkung, A., & Kiswanto, R. H. (2018). Analisa perbandingan metode SAW, WP dan TOPSIS menggunakan Hamming Distance. KNSI 2018. Retrieved from http://jurnal.atmaluhur.ac.id
Syarief, F. M. F., & Suwandana, S. (2017). Analisis dan perancangan decision support system menentukan angkat kredit dengan metode SAW (Simple Additive Weighting) pada Leasing Oto Finance Batam. Sekolah Tinggi Manajemen Informatika dan Komputer (STMIK) GICI Batam.
Jaenudin, T. S. M. T. A. (2017). Penerapan metode SAW (Simple Additive Weighting) dalam sistem pendukung keputusan untuk menentukan penerima beasiswa. Prosiding Saintiks FTIK Unikom, 2.
Prasetyanti, D. N., & Listyaningrum, R. (2017). Kaji banding metode TOPSIS, SAW dan AHP-TOPSIS guna menentukan UKT mahasiswa baru di Politeknik Negeri Cilacap. Jurnal Infotekmesin, 8(1).
Irwan, D., et al. (2018). Pemilihan lokasi pembangunan pabrik dengan metode SAW dan TOPSIS. Jurnal Teknik Industri, 10(2), 45-56.
Putra, A., & Handayani, S. (2019). Evaluasi kinerja karyawan menggunakan metode SAW dan TOPSIS. Jurnal Manajemen, 15(1), 67-78.
Yuliana, R., et al. (2020). Pemilihan supplier terbaik menggunakan metode SAW dan TOPSIS. Jurnal Logistik dan Rantai Pasok, 12(3), 123-135.
Moengin, P., Syachrany, A., Kemalasari, D., & Puspitasari, F. (2021). Sistem informasi untuk perbaikan kinerja dalam manajemen keselamatan transportasi kereta api (Studi kasus di PT. Kereta Api Indonesia). Jurnal Teknik Industri, 11(2), 173-185.
Sinaga, T. S., & Hidayat, R. (2020). Pengaruh motivasi dan kompensasi terhadap kinerja karyawan pada PT. Kereta Api Indonesia. Jurnal Ilman Jurnal Ilmu Manajemen, 8(1), 15-22.
Marbun, R., & Gunawan, I. (2019). Sistem pendukung keputusan perangkingan data konsumen penumpang kereta api dengan menggunakan metode Simple Additive Weighting di PT. KAI. Juripol (Jurnal Institusi Politeknik Ganesha Medan), 2(1), 15-25.
Sinurat, S. M. (2019). Sistem pendukung keputusan masinis terbaik di PT. Kereta Api Indonesia (Persero) Medan Sumatera Utara dengan menggunakan metode AHP (Analytic Hierarchy Process). Pelita Informatika: Informasi dan Informatika, 7(4), 466-472.
Akhiroh, M., & Nugrahanti, F. (2019). Perancangan sistem pendukung keputusan pemberian dana pinjaman menggunakan metode Simple Additive Weighting (SAW). Jurnal Sistem Informasi, 1(1), 42-44.
Mutmainah, I., & Yunita. (2021). Penerapan metode TOPSIS dalam pemilihan jasa ekspedisi. Jurnal SISFOKOM (Sistem Informasi dan Komputer), 10(1), 86-92.
Ginting, R., Purba, R. J., & Simatupang, T. (2020). Application of Simple Additive Weighting method for contraceptive method selection. Journal of Health Informatics in Developing Countries, 14(1), 45-56.
Nurcahyo, R., Alamsyah, Y., & Ridwan, M. (2019). Multi-criteria decision making for contraceptive methods using SAW. International Journal of Healthcare Management, 12(3), 211-218.
Kurniawan, A., Sutrisno, T., & Nugroho, H. (2021). Evaluating contraceptive methods using TOPSIS approach. Healthcare Technology Letters, 8(2), 102-108.
Prasetyo, E., Handayani, P. W., & Pinem, A. A. (2022). Optimizing contraceptive choices through TOPSIS. Journal of Medical Systems, 46(3), 158-165.
Wibowo, A., Santoso, L. W., & Fauzi, A. (2021). Combining SAW and TOPSIS for enhanced decision making in contraceptive method selection. International Journal of Decision Support System Technology, 13(4), 23-39.
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2024 Joko Susilo, Elyza Gustri Wahyuni
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree to the following terms:
1. Copyright Retention and Open Access License
Authors retain copyright of their work and grant the journal non-exclusive right of first publication under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
This license allows unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
2. Rights Granted Under CC BY 4.0
Under this license, readers are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, including commercial use
- No additional restrictions — the licensor cannot revoke these freedoms as long as license terms are followed
3. Attribution Requirements
All uses must include:
- Proper citation of the original work
- Link to the Creative Commons license
- Indication if changes were made to the original work
- No suggestion that the licensor endorses the user or their use
4. Additional Distribution Rights
Authors may:
- Deposit the published version in institutional repositories
- Share through academic social networks
- Include in books, monographs, or other publications
- Post on personal or institutional websites
Requirement: All additional distributions must maintain the CC BY 4.0 license and proper attribution.
5. Self-Archiving and Pre-Print Sharing
Authors are encouraged to:
- Share pre-prints and post-prints online
- Deposit in subject-specific repositories (e.g., arXiv, bioRxiv)
- Engage in scholarly communication throughout the publication process
6. Open Access Commitment
This journal provides immediate open access to all content, supporting the global exchange of knowledge without financial, legal, or technical barriers.
