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@ndrer

Veni in altitudinem dolorum, et demerserunt me. 10100100000.

London, England Katılım Eylül 2009
1.5K Takip Edilen1.7K Takipçiler
•⟂⊂Ω–•ᘰ | Ω ∟ ᘰ ᘰ:
@tunjungutomo it seems like (for me) there was a sudden jump from a relatively benign topic like stats/ML forecasting, into very technical, jargon-y medical science papers with all the scary diseases. I suspect they’re not the only ones doing this.
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@tunjungutomo Not gonna speculate on who influenced whom. But I do have a suspicion that, like predatory research paper mills, these people didn’t just stumble into conference-swindling. How do you even know which conference is gullible, and what kind of abstract will be likely accepted?
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cwa
cwa@nasykucing·
@keithlorracee @joutnal @muamarmusa @ndrer nah ini, pertanyaan aku sih sebenernya.. kalo modelnya emang bilang gitu (X lebih cost effective than Y) gimana? (despite dia asumsinya ngawur, atau hasilnya seems impossible) how can one frame the result w/o being misleading, kalo risetnya ga dilakukan bareng ahli bidang tsb?
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Why bother with painstaking research if you can use AI to generate slop paper and people be none the wiser. Cheating sucks because it destroys the incentives for people to work hard and work honestly. Making it a race to the bottom for who can make a fool out of the other.
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People be like “orangnya terlihat pintar tapi kok bikin pelanggaran akademik ya?” Sometimes people cheat not because they are stupid, or that they are inherently incapable to achieve their goal. They cheat because they want to achieve their goal ✨easily✨.
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@nasykucing @muamarmusa not sure. Perhaps you don’t need clearance from Board of Ethics unlike primary data collection. But at the very least it’s ethically suspect, since you’re interpreting result and providing recommendation you have no expertise in.
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cwa@nasykucing·
@muamarmusa @ndrer wait, riset kayak gini tuh "boleh" kah? simply bikin model terus yaudah, pake data sekunder aja, tanpa ngegandeng orang di bidang ahlinya?
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@muamarmusa Nope. This group really suggested that they conducted a focused cohort of 2,400 Alzheimer patients. That’s a stretch even for a large biolab. Also there is a categorical difference between predicting visitors and cancer/Alzheimer’s. The latter has implication to life and death.
•⟂⊂Ω–•ᘰ | Ω ∟ ᘰ ᘰ: tweet media•⟂⊂Ω–•ᘰ | Ω ∟ ᘰ ᘰ: tweet media
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musa ムサ 🍉
musa ムサ 🍉@muamarmusa·
@ndrer sebenernya bisa aja kalo bidang matematika terapan, tapi datanya semua mau ga mau data sekunder
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•⟂⊂Ω–•ᘰ | Ω ∟ ᘰ ᘰ:
But again, not many people can sniff out conference that can provide them means of travel + high probability of acceptance given minimum effort and credential. Takes a special kind of grift you know
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Junk papers and AI slops are always expected. You can’t always expect honesty from humans. Look at Replication Watch and Data Colada. The onus rests on the conference committee’s and the reviewers’ ability to filter them out 🤷‍♂️
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•⟂⊂Ω–•ᘰ | Ω ∟ ᘰ ᘰ:
Ini dana reses sudah dihitung belum ya? Bisa jadi > Filipina lho. Nggak terima saya kalau kita kalah dari mereka untuk urusan ngepet-ngepetan begini 😀
Ricky Ho@rickyho_1989

This chart is a brutal reflection of why public frustration toward political elites in many emerging markets continues intensifying because it shows that Indonesian lawmakers are compensated at levels that look extraordinarily disconnected from the underlying economic reality faced by the average citizen, with parliament salary reaching roughly 14.7x GDP per capita, among the highest ratios globally and second only to the Philippines in this dataset, despite Indonesia still remaining a country where purchasing power remains relatively weak, informal employment is massive, public service quality remains uneven, infrastructure bottlenecks persist, legal enforcement often feels inconsistent, and upward economic mobility for large parts of the population remains structurally difficult. And this is precisely why charts like this become politically toxic because citizens naturally begin asking a very simple question: what exactly are taxpayers receiving in return? In high-income countries, lawmakers may also earn very large nominal salaries, but those economies simultaneously generate far stronger productivity, higher institutional quality, better healthcare systems, stronger education outcomes, more efficient bureaucracy, higher legal predictability, and materially better public goods overall, meaning political compensation exists within a much larger and wealthier economic ecosystem. But in Indonesia, the optics become far more uncomfortable because the political class increasingly appears capable of extracting upper-middle-class or even developed-market lifestyles from an economy that still struggles to generate broad-based prosperity for much of the population itself. And perhaps the harshest part is that compensation alone is probably not even the real issue. The real issue is performance. Citizens are generally willing to tolerate highly compensated leaders if the country visibly becomes richer, more efficient, more meritocratic, less corrupt, and economically stronger over time. But when corruption scandals remain persistent, policymaking appears inconsistent, infrastructure projects repeatedly face rent-seeking concerns, and wealth creation remains concentrated among political insiders, conglomerates, and connected elites, high political compensation begins looking less like professionalization and more like institutionalized extraction. Importantly, this also helps explain why anti-elite sentiment, populism, and distrust toward institutions continue rising globally because once the gap between elite living standards and ordinary household realities becomes too visible, citizens increasingly stop believing the system operates primarily for collective national advancement and instead begin viewing politics as a mechanism for self-enrichment among those already close to power. Ultimately, this chart reflects something much deeper than salary levels alone because it exposes the uncomfortable reality that in many emerging markets, the political class often succeeds in upgrading its own prosperity far faster than the nation it supposedly represents, and over time that divergence itself becomes corrosive to institutional trust, social cohesion, and long-term political legitimacy.

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kalau nggak berani head-to-head sama AMRT dan DNET dan mesti dicebokin sama kamarentah mah berarti skill issue. Kalah sama warung madura
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•⟂⊂Ω–•ᘰ | Ω ∟ ᘰ ᘰ:
Just an observation apropos of nothing: AI works better if you define a narrow, specific problem space. If you ask it to “diagnose the problems and propose economic policies to fix Country X. Make no mistake” you’d find its arguments fall all over the place. Alias nggrambyang 😌
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@catuaries tapi semakin dibaca semakin nganu. Kayak “Tax-Cut Targeted Umkm [sic]”. Wong UMKM aja udah susah dipajaki karena economies-of-scale-nya terlalu kecil dibandingkan enforcement cost, malah tambah mau di-cut wkwk. Mix istilah ID-EN ini juga tipikal sekali hasil output dari nganu 😌
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