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Penilaian cerun dijalankan bagi meramal kebarangkalian berlakunya kejadian tanah runtuh dan juga tahap kemusnahannya di sesuatu kawasan yang dinilai. Dalam kertas kerja ini, empat sistem penilaian cerun (SAS) sedia ada bagi meramal kejadian tanah runtuh pada skala mikro yang telah dibangunkan oleh Jabatan Kerja Raya (JKR) Malaysia iaitu Slope Maintenance System (SMS), Slope Priority Ranking System (SPRS), Slope Information Management System (SIMS) dan Slope Management and Risk Tracking System (SMART) telah dikaji. Daripada hasil kajian, adalah jelas tiada sebarang satu SAS sedia ada yang sesuai bagi meramal kejadian tanah runtuh di kawasan yang didasari batuan granit. Ini adalah kerana beberapa sebab yang jelas iaitu antaranya skor bahaya yang digunakan diadaptasi dari negara luar, pengkalan data yang terhad, dan juga pengkalan data yang digunakan adalah daripada formasi batuan yang berbeza. Dalam kajian ini, dua SAS baru telah dibangunkan iaitu Model A yang menggunakan persamaan sepuluh parameter yang dibentuk dari analisa discriminant, dan Model B yang menggunakan persamaan sembilan parameter yang dibentuk dari analisa linear regression. Kedua–dua model baru ini jelas menunjukkan ia lebih sesuai bagi meramal kejadian tanah runtuh di kawasan didasari batuan granit. Kata kunci: Analisa discriminant, formasi granit, tanah runtuh, sistem penilaian cerun  A slope assessment is carried out to predict the probability of occurrence and the degree of severity of landslides in a given area. This paper evaluates four existing slope assessment systems (SAS) for predicting landslides at micro level of assessment developed by the Public Works Department of Malaysia, namely the Slope Maintenance System (SMS), Slope Priority Ranking System (SPRS), Slope Information Management System (SIMS) and the Slope Management and Risk Tracking System (SMART). From the results of this study, it appears that none of the existing SAS is satisfactory for predicting landslide in granitic formation, due to various reasons such as the use of hazard score developed from another country, insufficient database, and the use of data base derived from different rock formations. Two new SAS were developed, i.e. Model A using ten–variables equation that is based on the stepwise discriminant analysis, and Model B using ninevariables equation that is based on the stepwise linear regression analysis. These two new models appear to be suitable for predicting landslides in granitic formations than the existing four SAS.  Key words: Discriminant analysis, granitic formation, landslide, slope assessment system

Evaluation And Development Of Cut–Slope Assessment Systems For Peninsular Malaysia In Predicting Landslides In Granitic Formation