Perhitungan deskriptor energi HOMO dan LUMO Perhitungan deskriptor momen dipole Perhitungan deskriptor Molar refractivity Rekapitulasi Data Deskriptor Training dan Test sets pada Microsoft excel Membangun persamaan HKSA Hasil Validasi HKSA pada SPSS

UIN Syarif Hidayatullah Jakarta 2.4 Pembuatan struktur pada Hyperchem Struktur yang telah dibuat kemudian ditambahkan atom hidrogen dengan cara: build add H model buildklik kiri

2.5 Optimasi struktur pada Hyperchem

optimasi dengan cara pilih setup semiempiricalklik kirikemudian pilih AM1Ok

2.6 Perhitungan deskriptor energi HOMO dan LUMO

Pilih compute Geometry Optimizationklik kiriPilih pada semiempirical optimization “Polak Ribere” Ok UIN Syarif Hidayatullah Jakarta Setelah optimasi selesai pilih compute Orbitalsklik kiripilih energi HOMO dan LUMO

2.7 Perhitungan deskriptor momen dipole

Pilih compute single pointproperties akan didapat tampilan diataspilih momen dipole ok

2.8 Perhitungan deskriptor Molar refractivity

Pilih compute QSAR propertiesPilih RefractivityComputeAkan didapat nilai Molar refractivity UIN Syarif Hidayatullah Jakarta

2.9 Rekapitulasi Data Deskriptor Training dan Test sets pada Microsoft excel

2.10 Membangun persamaan HKSA

Setelah semua data training set telah di input ke dalam program SPSS, kemudian pilih analyze RegressionLinierakan muncul tampilan pada gambar disamping. Masukkan data dependent variabel: Log1MIC dan Independent variabel:7 data deskriptorganti method: BackwardOk UIN Syarif Hidayatullah Jakarta

2.11 Hasil Validasi HKSA pada SPSS

Variables EnteredRemoved b Model Variables Entered Variables Removed Method 1 Molar_Refractivit y, MomenDipole, LogD, E_LUMO, E_HOMO, Harary_Index, Randix_Index a . Enter 2 . MomenDipole Backward criterion: Probability of F-to-remove = .100. 3 . Harary_Index Backward criterion: Probability of F-to-remove = .100. a. Tolerance = .000 limits reached. b. Dependent Variable: Log1MIC Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .994 a .988 .908 .083051 2 .992 b .985 .938 .067998 3 .988 c .976 .937 .068409 a. Predictors: Constant, Molar_Refractivity, MomenDipole, LogD, E_LUMO, E_HOMO, Harary_Index, Randix_Index b. Predictors: Constant, Molar_Refractivity, LogD, E_LUMO, E_HOMO, Harary_Index, Randix_Index c. Predictors: Constant, Molar_Refractivity, LogD, E_LUMO, E_HOMO, Randix_Index UIN Syarif Hidayatullah Jakarta ANOVA d Model Sum of Squares df Mean Square Fhitung Sig. 1 Regression .590 7 .084 12.218 .217 a Residual .007 1 .007 Total .597 8 2 Regression .588 6 .098 21.179 .046 b Residual .009 2 .005 Total .597 8 3 Regression .583 5 .117 24.906 .012 c Residual .014 3 .005 Total .597 8 a. Predictors: Constant, Molar_Refractivity, MomenDipole, LogD, E_LUMO, E_HOMO, Harary_Index, Randix_Index b. Predictors: Constant, Molar_Refractivity, LogD, E_LUMO, E_HOMO, Harary_Index, Randix_Index c. Predictors: Constant, Molar_Refractivity, LogD, E_LUMO, E_HOMO, Randix_Index d. Dependent Variable: Log1MIC Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 Constant -14.130 8.466 -1.669 .344 LogD .251 .094 1.278 2.677 .228 E_HOMO -.693 .955 -.535 -.726 .600 E_LUMO -3.027 .793 -.871 -3.817 .163 MomenDipole -.068 .116 -.320 -.584 .664 Harary_Index .044 .044 2.104 .992 .503 Randix_Index -1.364 .569 -18.640 -2.398 .252 Molar_Refractivity .294 .122 17.387 2.400 .251 UIN Syarif Hidayatullah Jakarta 2 Constant -18.700 2.637 -7.092 .019 LogD .298 .039 1.518 7.655 .017 E_HOMO -1.220 .253 -.943 -4.832 .040 E_LUMO -2.812 .575 -.809 -4.890 .039 Harary_Index .034 .034 1.637 1.018 .416 Randix_Index -1.106 .292 -15.108 -3.781 .063 Molar_Refractivity .243 .070 14.353 3.475 .074 3 Constant -19.106 2.622 -7.286 .005 LogD .302 .039 1.543 7.789 .004 E_HOMO -1.226 .254 -.947 -4.824 .017 E_LUMO -2.828 .578 -.814 -4.889 .016 Randix_Index -1.083 .293 -14.804 -3.693 .034 Molar_Refractivity 0.265 .067 15.681 3.978 .028

2.12 Nilai F