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Sensitivity Analysis of Various AHP Process: A Case Study on Consumption Fish Farming Michael Siregar, Ivan; Budi Putri, Lydia Wulandari; Sugihartono, Tri
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2101

Abstract

The utilization of a decision support system has successfully helped many businesses in increasing their product sales. By conducting product evaluations, the sales potential of each product will be seen more accurately, thereby helping strategic decision-makers. As one of the algorithms in product selection, AHP  has been proven to solve complex problems involving multi-criteria, as many studies have successfully used it to rank products. However, in AHP implementation there are two different ways of calculating weights and consistency ratios. Due to the various AHP processes available, this paper performs testing with the most frequently used variations to determine product potential and compare the methods for multi-criteria decision-making. The criteria are harvest duration, selling price, feed production, weather conditions, and target market. The research results show that the weights of the two methods are different, but the resulting ranks are the same. The best choice type of fish to be farmed by fish farmers is catfish with the highest weight and the most difficult type of fish to farm is giant gourami. The result also show that the best way of the normalization process is squares of comparison matrices because its sensitivity does not easily change the ranking order.
Sensitivity Analysis of Various AHP Process: A Case Study on Consumption Fish Farming Michael Siregar, Ivan; Budi Putri, Lydia Wulandari; Sugihartono, Tri
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 13 No. 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2101

Abstract

The utilization of a decision support system has successfully helped many businesses in increasing their product sales. By conducting product evaluations, the sales potential of each product will be seen more accurately, thereby helping strategic decision-makers. As one of the algorithms in product selection, AHP  has been proven to solve complex problems involving multi-criteria, as many studies have successfully used it to rank products. However, in AHP implementation there are two different ways of calculating weights and consistency ratios. Due to the various AHP processes available, this paper performs testing with the most frequently used variations to determine product potential and compare the methods for multi-criteria decision-making. The criteria are harvest duration, selling price, feed production, weather conditions, and target market. The research results show that the weights of the two methods are different, but the resulting ranks are the same. The best choice type of fish to be farmed by fish farmers is catfish with the highest weight and the most difficult type of fish to farm is giant gourami. The result also show that the best way of the normalization process is squares of comparison matrices because its sensitivity does not easily change the ranking order.
Analisis Variasi Implementasi Algoritma Analytical Hierarchy Process (AHP) Dalam Menentukan Prioritas Produk Kalibrasi Michael Siregar, Ivan; Budi Putri, Lydia Wulandari
Jurnal Nasional Teknologi dan Sistem Informasi Vol 10 No 1 (2024): April 2024
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v10i1.2024.54-63

Abstract

Pemanfaatan teknologi informasi telah berhasil menolong banyak perusahaan dalam meningkatkan penjualan produknya. Dengan melakukan evaluasi terhadap kinerja penjualan maka akan terlihat dinamika perubahan angka penjualan setiap produk secara lebih akurat untuk membantu pengambil keputusan yang strategis. Oleh karena itu, untuk mengatasi permasalahan ranking dan prioritas produk pada penelitian ini diperlukan suatu algoritma khusus seperti AHP untuk menyelesaikan permasalahan kompleks yang memiliki banyak kriteria. Banyak penelitian yang berhasil menggunakan algoritma AHP untuk menentukan peringkat produk seperti produk yang laris di minimarket dan beberapa studi kasus lainnya. Namun dalam penerapan AHP terdapat beberapa cara berbeda dalam menghitung bobot dan rasio konsistensi. Menggunakan AHP, melakukan pengujian dengan variasi proses AHP yang sering digunakan untuk menentukan prioritas kalibrasi produk dan membandingkannya, kemudian mengimplementasikan metode terbaik ke dalam Python. Kriterianya adalah jumlah pelanggan, jumlah alat yang masuk, harga per alat, waktu penyelesaian, dan review pelanggan. Berdasarkan hasil penelitian, bobot masing-masing cara berbeda-beda, namun prioritas yang dihasilkan sama. Produk terlaris adalah plug gauge dengan bobot tertinggi dan terburuk adalah instrumen. Hasilnya juga menunjukkan bahwa cara terbaik dalam proses normalisasi adalah dengan membagi setiap nilai kolom dengan total kolom yang bersangkutan dan memiliki nilai konsistensi yang lebih akurat. Hasil pemeringkatan akan memudahkan pengambil keputusan menganalisis prioritas produk dan menggunakan cara yang efektif.