Try this:
t = linspace(0, 10, 150); % Create Data
y = sin(2*pi*t*3) .* cos(2*pi*t*2) + 0.01*randn(size(t)); % Create Data
L = numel(t);
Ts = mean(diff(t)); % Sampling Interval
Fs = 1/Ts; % Sampling Frequency
Fn = Fs/2; % Nyquist Frequency
FTy = fft(y)/L; % Fourier Transform
Fv = linspace(0, 1, fix(L/2)+1)*Fn; % Frequency Vector
Iv = 1:numel(Fv); % Index Vector
areaFrac = 0.8; % Desired Fraction Of Total Area
areaTot = trapz(Fv, abs(FTy(Iv))); % Total Area
areaCum = cumtrapz(Fv, abs(FTy(Iv))); % Cumulative Integral
Fv80 = interp1(areaCum, Fv, areaTot*areaFrac, 'spline') % Frequency Corresponding To 80% Total Area
FTy80 = interp1(Fv, abs(FTy(Iv))*2, Fv80, 'spline') % Value of Fourier Transform At ‘Fv80’
figure
plot(Fv, abs(FTy(Iv))*2, '-b')
hold on
plot(Fv, areaCum, '-k')
plot([0 max(Fv)], [1 1]*areaTot, '--k')
plot([0 max(Fv)], [1 1]*areaFrac*areaTot, ':k')
plot([1 1]*Fv80, [0 FTy80], '-r')
plot(Fv80, areaTot*areaFrac, 'r+')
hold off
legend('Fourier Transform', 'Cumulative Area', 'Maximum Area', '80% Maximum Area', 'Fourier Transform at 80% Maximum Area')
Experiment to get the result you want.
