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      Efektivitas dan Akurasi Rancangan SINAVA dalam Navigasi Investasi Saham Berbasis Standarisasi Rasio Keuangan Sektor Agribisnis

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      Date
      2026
      Jenis/Type
      Tugas Akhir
      Subtype
      Undergraduate Theses
      Author
      Maslihudin, Anwar
      Riswandi, Dadang Iwan
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      Abstract
      ANWAR MASLIHUDIN. Efektivitas dan Akurasi Rancangan SINAVA dalam Navigasi Investasi Saham Berbasis Standarisasi Rasio Keuangan Sektor Agribisnis. Dibimbing oleh D. IWAN RISWANDI. Keterbatasan alat analisis fundamental sering memicu information overload dan bias psikologis investor ritel. Mengatasi hal tersebut, penelitian ini merancang sistem standarisasi rasio keuangan 18 emiten agribisnis menggunakan metode Rapid Application Development (RAD). Sistem ini mengintegrasikan 15 parameter fundamental dan teknikal menggunakan algoritma Simple Additive Weighting (SAW) melalui Piecewise Normalization ke dalam tiga profil investasi: value, growth, dan dividend. Sistem lulus 100% uji black box dan mencapai skor User Acceptance Testing (UAT) 92,81%. Backtesting membuktikan seluruh portofolio melampaui Indeks Harga Saham Gabungan (IHSG), dengan return tertinggi pada profil dividend (+50,04%), disusul value (+40,29%), dan growth (+34,24%). Risiko penurunan maksimal seluruh profil (-10,99% s.d. -14,13%) terbukti lebih tangguh daripada pelemahan pasar (-17,88%). Validasi pakar mengonfirmasi sistem ini efektif sebagai navigasi investasi dengan risiko terkendali.
       
      ANWAR MASLIHUDIN. Effectiveness and Accuracy of the SINAVA Design in Navigating Stock Investments Based on Agribusiness Sector Financial Ratio Standardization. Supervised by D. IWAN RISWANDI. Limited fundamental analysis tools often trigger information overload and psychological biases for retail investors. To address this, the study designed a financial ratio standardization system for 18 agribusiness issuers using the Rapid Application Development (RAD) method. The system integrates 15 fundamental and technical parameters using the Simple Additive Weighting (SAW) algorithm via Piecewise Normalization into three investment profiles: value, growth, and dividend. The system passed 100% black box testing and achieved a 92.81% User Acceptance Testing (UAT) score. Backtesting proved all portfolios outperformed the Jakarta Composite Index (JCI), with the highest return in the dividend profile (+50.04%), followed by value (+40.29%) and growth (+34.24%). The Maximum Adverse Excursion (MAE) risk for all profiles (-10.99% to -14.13%) was proven safer than the market downturn (-17.88%). Expert validation confirmed the system is effective for risk-controlled investment navigation.
       
      URI
      http://repository.ipb.ac.id/handle/123456789/176532
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      • UF - Accounting [607]

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      Copyright © 2020 Library of IPB University
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      Contact Us | Send Feedback
      Indonesia DSpace Group 
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