Najib Still Popular Court Cluster Label Insignificant Says Analyst

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Analyst Jeniri Amir said many people remember Najib Razak’s people-centric policies even though he has not been in power since the 2018 general election. (Bernama pic)PETALING JAYA: The “court cluster” label used against certain Umno leaders is inconsequential and will not affect Barisan Nasional (BN) in the coming Johor elections, says an analyst.
Jeniri Amir.National Council of Professors fellow Jeniri Amir says the coalition’s leaders are still popular, particularly former prime minister Najib Razak because his views on various issues resonate with the people.
He was commenting on the impact of the ‘court cluster’ label on BN’s chances in the Johor elections.
BN’s opponents have raised the spectre of the group of Umno leaders facing trial, and say they could ultimately return to power should the coalition win the Johor polls.
Jeniri said even though Najib had not been in power since the 2018 general election, many remember his people-centric policies, which included the Bantuan Rakyat 1Malaysia cash aid, as shown by the praises that Najib received on social media.
“Many people do not care about Najib’s cases, they know that no prime minister is perfect,” he told FMT.
Azmi Hassan.The Johor elections were BN’s to win because Malay voters, who form the majority, were likely to back Umno.
“PKR is a multiracial party, much of Bersatu’s support (in GE14) was drawn from Umno, Pejuang has weak grassroots and the PAS ideology may be too extreme,” he said.
He expects BN to “win handsomely” as in Melaka in November, when it trounced Pakatan Harapan (PH) and Perikatan Nasional (PN).
Akademi Nusantara senior fellow Azmi Hassan said ineffectiveness of the PH and PN administrations contributed to Najib’s popularity, as he spoke up against them.
“Those who are on the fence will go back to Umno even though they chose PH during the last general election,” said Azmi, citing the coalition’s poor performance in their 22 months in power. The same applied to PN. - FMT

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