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Implementasi Simple Additive Weighting dan Weighted Product pada Sistem Pendukung Keputusan untuk Rekomendasi Penerima Beras Sejahtera

Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 5 No. 4 (2018) · pp. 419–426

DOI
10.25126/jtiik.201854768
ISSN
2528-6579, 2355-7699
Published
2018-10-01
Publisher
Fakultas Ilmu Komputer, Universitas Brawijaya
Language
id

Abstract

Salah satu upaya pemerintah untuk mengatasi masalah kemiskinan di Indonesia yaitu membuat program beras sejahtera (RASTRA). RASTRA merupakan program dari pemerintah berupa bantuan beras bersubsidi untuk membantu masyarakat yang berpenghasilan rendah. Permasalahan yang terjadi yakni banyaknya kriteria penilaian yang digunakan dalam pedoman RASTRA dan penduduk miskin di suatu area/wilayah seringkali menyulitkan proses penentuan Keluarga Penerima Manfaat yang berhak menerima RASTRA pada Musyawarah desa/kecamatan. Tujuan penelitian ini adalah merancang dan mengembangkan sistem penunjang keputusan menggunakan model matematika Simple Additive Weighting (SAW) dan Weighted Product (WP) untuk memberikan rekomendasi penerima RASTRA. Terdapat empat tahapan penelitian yang digunakan untuk mencapai tujuan penelitian, yaitu analisis kebutuhan perangkat lunak, desain perangkat lunak, pengembangan, dan pengujian perangkat lunak. Berdasarkan hasil pengujian, hasil perhitungan nilai preferensi SAW memiliki performa yang lebih baik daripada WP karena SAW mampu meminimalisir nilai preferensi alternatif yang sama. Hal ini tampak dari perankingan alternatif berdasarkan hasil perhitungan SAW sejumlah 13 peringkat, dan WP sejumlah 10 peringkat. AbstractOne of the government's efforts to overcome the poverty problem in Indonesia is to make the program "Beras Sejahtera" (RASTRA). RASTRA is a government program of subsidised rice to help low-income communities. The problems which occur are the number of assessment criteria used in the RASTRA guidelines and the poor in an area/region often complicate the process of determining the Beneficiary Family who are eligible to receive RASTRA at the village/sub-district deliberation. The purpose of this research is to design and develop decision support system using Simple Additive Weighting (SAW) and Weighted Product (WP) mathematical model to give the recommendation of RASTRA recipient. There are four research stages to achieve the research objectives, namely software requirements analysis, software design, development, and software testing. Based on the test results, the calculation of SAW preference values has better performance than WP because SAW can minimise the value of the same alternative preferences. This can be seen from the alternative ranking based on the calculation of SAW of 13 ranks, and WP 10 rank number.

Keywords

Collaboration network of the authors

13 authors · 22 co-authorship links · 2 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Amikom Purwokerto
  • Southern Taiwan University of Science and Technology
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Wiga Maulana BaihaqiUniversitas Amikom Purwokerto2
Yuli PurwatiUniversitas Amikom Purwokerto2
Taqwa HarigunaUniversitas Amikom Purwokerto2
Rahmat PambudiUniversitas Amikom Purwokerto1
Giat KaryonoUniversitas Amikom Purwokerto1
Diah Ratna IsmawatiAffiliation unknown1
Pungkas SubarkahAffiliation unknown1
Selvi SagitaUniversitas Amikom Purwokerto1
Dadang Wahyu UtomoUniversitas Amikom Purwokerto1
Min Tsai LaiSouthern Taiwan University of Science and Technology1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jtiik.ub.ac.id/index.php/jtiik/en/oai, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="id">Implementasi Simple Additive Weighting dan Weighted Product pada Sistem Pendukung Keputusan untuk Rekomendasi Penerima Beras Sejahtera</dc:title>
	<dc:creator xml:lang="id">Berlilana, Berlilana</dc:creator>
	<dc:creator xml:lang="id">Prayoga, Fandhi Dhuga</dc:creator>
	<dc:creator xml:lang="id">Utomo, Fandy Setyo</dc:creator>
	<dc:subject xml:lang="id">Sistem Pendukung Keputusan</dc:subject>
	<dc:subject xml:lang="id">Simple Additive Weighting</dc:subject>
	<dc:subject xml:lang="id">Weighted Product</dc:subject>
	<dc:subject xml:lang="id">Multi-attribute Decision Making</dc:subject>
	<dc:description xml:lang="id">Salah satu upaya pemerintah untuk mengatasi masalah kemiskinan di Indonesia yaitu membuat program beras sejahtera (RASTRA). RASTRA merupakan program dari pemerintah berupa bantuan beras bersubsidi untuk membantu masyarakat yang berpenghasilan rendah. Permasalahan yang terjadi yakni banyaknya kriteria penilaian yang digunakan dalam pedoman RASTRA dan penduduk miskin di suatu area/wilayah seringkali menyulitkan proses penentuan Keluarga Penerima Manfaat yang berhak menerima RASTRA pada Musyawarah desa/kecamatan. Tujuan penelitian ini adalah merancang dan mengembangkan sistem penunjang keputusan menggunakan model matematika Simple Additive Weighting (SAW) dan Weighted Product (WP) untuk memberikan rekomendasi penerima RASTRA. Terdapat empat tahapan penelitian yang digunakan untuk mencapai tujuan penelitian, yaitu analisis kebutuhan perangkat lunak, desain perangkat lunak, pengembangan, dan pengujian perangkat lunak. Berdasarkan hasil pengujian, hasil perhitungan nilai preferensi SAW memiliki performa yang lebih baik daripada WP karena SAW mampu meminimalisir nilai preferensi alternatif yang sama. Hal ini tampak dari perankingan alternatif berdasarkan hasil perhitungan SAW sejumlah 13 peringkat, dan WP sejumlah 10 peringkat. AbstractOne of the government's efforts to overcome the poverty problem in Indonesia is to make the program "Beras Sejahtera" (RASTRA). RASTRA is a government program of subsidised rice to help low-income communities. The problems which occur are the number of assessment criteria used in the RASTRA guidelines and the poor in an area/region often complicate the process of determining the Beneficiary Family who are eligible to receive RASTRA at the village/sub-district deliberation. The purpose of this research is to design and develop decision support system using Simple Additive Weighting (SAW) and Weighted Product (WP) mathematical model to give the recommendation of RASTRA recipient. There are four research stages to achieve the research objectives, namely software requirements analysis, software design, development, and software testing. Based on the test results, the calculation of SAW preference values has better performance than WP because SAW can minimise the value of the same alternative preferences. This can be seen from the alternative ranking based on the calculation of SAW of 13 ranks, and WP 10 rank number.</dc:description>
	<dc:publisher xml:lang="en">Fakultas Ilmu Komputer, Universitas Brawijaya</dc:publisher>
	<dc:date>2018-10-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
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	<dc:identifier>https://jtiik.ub.ac.id/index.php/jtiik/article/view/768</dc:identifier>
	<dc:identifier>10.25126/jtiik.201854768</dc:identifier>
	<dc:source xml:lang="id">Jurnal Teknologi Informasi dan Ilmu Komputer; Vol 5 No 4: Agustus 2018; 419-426</dc:source>
	<dc:source xml:lang="en">Jurnal Teknologi Informasi dan Ilmu Komputer; Vol. 5 No. 4: Agustus 2018; 419-426</dc:source>
	<dc:source>2528-6579</dc:source>
	<dc:source>2355-7699</dc:source>
	<dc:source>10.25126/jtiik.201854</dc:source>
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