Breaking Boundaries: A World More Populated Online Than Offline

Breaking Boundaries: A World More Populated Online Than Offline

by Huda Sani

In a world that is increasingly becoming digitized, the lines between the virtual and real blur into a vibrant dance of data and connection. Imagine a place where the number of digital denizens surpasses the populations of entire countries – a realm where Facebook's friend count outshines the people strolling the streets of India. 

In the world of social media, big players like Facebook, YouTube, WhatsApp, and Instagram are like the cool kids on the block with the most friends. They're basically the rulers of the online hangout, where everyone gathers, sharing memes, videos, and messages. They're the A-listers making the internet buzz.

Around the world, everyone's hooked on social media. The top social media platforms have a global user base, with platforms like Facebook and YouTube exceeding 2 billion users. This highlights the widespread adoption of these platforms on a global scale. 

The user counts for platforms like WeChat, Douyin, Kuaishou, and Sina Weibo suggest popularity in specific regions, such as China. Understanding regional preferences and cultural factors can provide insights into the platform's success. It is like each place has its own social media stars. Exploring these trends helps us see what people love in different parts of the world. Social media isn't just global; it is a wild ride through cultural hotspots as well. 

The user counts for major social media platforms, especially Facebook, YouTube, and WhatsApp, are comparable to the populations of large countries like India and China. This suggests the immense scale and impact of social media on a global level.

Multiple accounts and overlapping users are common occurrences. 

It's like wearing different hats for different occasions, but all in the same online world!

Engagingly, the phenomenon of multiple accounts extends even within the same social media platform. Notably, when some platforms host user counts comparable to entire country populations, it hints at individuals juggling multiple accounts.  People often have more than one account on the same social media site, like having different profiles for different things. Think of it like having separate spaces for work and play. When a social media platform has loads of users, it's like a whole country is on there! So, having a few accounts might be because people want to use the platform in different ways – like chatting with friends or following trends. 

Besides, the observation that some social media platforms have user counts approaching or exceeding the populations of large countries may indicate that individuals have accounts on multiple platforms. This could be due to different platforms serving distinct purposes, user preferences, or regional popularity. In essence, people are navigating the social media landscape with a multifaceted approach, engaging in different corners for different experiences.

Evolving Social Media Landscape!

The presence of newer platforms like TikTok and Telegram in the top ranks reflects the dynamic nature of the social media landscape. Emerging platforms can quickly gain widespread popularity, reshaping user preferences and behaviors.

The popularity of messaging apps like WhatsApp and Facebook Messenger highlights the increasing role of social media in communication. These platforms have become integral parts of daily interactions for a significant portion of the global population.

Businesses and marketers can leverage the popularity of these social media platforms for advertising, brand promotion, and customer engagement. Understanding the user demographics and preferences on each platform is crucial for effective marketing strategies.

In conclusion, the findings suggest that social media platforms have become central to global communication, with user counts rivaling or surpassing the populations of large countries. The overlap in user counts between social media platforms and world populations may indicate that individuals are active on multiple platforms, reflecting the diverse and interconnected nature of the online social landscape.

Jadi Miskin itu MAHAL - kenapa?

Being Poor Is Expensive: Uncovering the Hidden Costs of Poverty

by HudaSani 

In a world of growing economic disparity, the stark reality is that being poor is expensive. This paradoxical phenomenon may not be immediately apparent, but when we delve into the intricacies of poverty, we discover that the cost of living for the poor is significantly higher compared to their more affluent counterparts. 

Have you ever think why being poor can be financially burdensome and the far-reaching implications it has on individuals and society as a whole.

1. Quantity Premiums: The Burden of Buying in Small Quantities 

One of the foremost reasons why poverty is expensive is the challenge of buying in bulk. For individuals or families living paycheck to paycheck, purchasing goods in larger quantities to benefit from economies of scale is often a luxury they cannot afford. This results in what economists refer to as "quantity premiums." Poor households end up paying more per unit for essential items like food, toiletries, and household supplies, compared to those who can buy in larger quantities.

2. Location Matters: The High Cost of Living in Disadvantaged Areas 

Many impoverished individuals find themselves residing in areas with higher transportation and infrastructure costs. These areas are often characterized by limited access to quality education, healthcare, and job opportunities. As a consequence, the prices of goods and services in these regions are inflated, further straining the financial resources of those already struggling to make ends meet. This disparity in living costs is a stark example of how poverty compounds itself.

Beyond the immediate financial strain, the higher cost of living associated with poverty exacerbates other development challenges, perpetuating the cycle of disadvantage. 

1. Limited Investment in Education and Opportunities 

The poor often find it challenging to invest in education or access opportunities that can lead to long-term benefits. The cycle of poverty restricts their ability to acquire the skills and knowledge necessary to escape its grasp. This not only hampers personal growth but also hinders economic development on a broader scale.

2. Environmental Consequences  

Poverty-induced financial constraints may force individuals to opt for cheaper but more environmentally damaging solutions. For instance, using cheaper, less eco-friendly fuel sources becomes a necessity when the cost of cleaner alternatives is prohibitive. This can contribute to increased carbon emissions and environmental degradation, impacting us all.

Tackling the problem of poverty premiums and creating a fairer society requires a multifaceted approach. Here are some strategies to consider:

1. Strengthening Social Protection Systems by implementing robust social safety nets can provide a financial buffer for the poor, helping them avoid high-cost loans and making ends meet during difficult times.

2. Boosting Agricultural Development via investments in agriculture can empower rural communities and reduce their dependence on costly imported food items, thereby lowering overall living costs.

3. Investing in Financial Infrastructure by expanding access to affordable financial services, such as microloans and savings accounts, can help the poor manage their finances more efficiently and escape the poverty trap.

4. Leveraging Innovation by utilizing technological advancements can lead to cost-effective solutions, such as mobile banking and online marketplaces, which can benefit the poor by reducing transaction costs.

5. Efficient Supply Chains will helps streamlining supply chains and reducing intermediaries can lower the prices of essential goods, making them more affordable for everyone.

In conclusion, being poor is undeniably expensive, and this harsh reality perpetuates a cycle of disadvantage that affects individuals and society as a whole. The hidden costs of poverty, from quantity premiums to constrained opportunities and environmental consequences, demand our attention and concerted efforts to address them. By implementing strategies such as strengthening social protection systems, investing in agriculture, and leveraging innovation, we can move closer to a society where the burden of poverty is alleviated, and the cycle of disadvantage is broken, paving the way for a more equitable future.

What is your secret with Allah ?

Dear myself.

Have a good secret between you and Allah.

Something that you are doing on the side, that no one else knows anything about it.

Just you and Allah.

and, tell yourself; 

"I want this things (deed) come out when I meet Allah on the day of judgement".

So, what' s your secret?

What is the thing, that when you meet Allah, "your happiest" gonna to come out?

like you are ready to say.

"Ya Allah, I'm ready for it now. Alhamdulillah, this is only between me and you. I used to do this when YOU re watching me. Here it is. This is my secret with you ya Allah".

Allahuakbar - such a deep reminder by imam omarsulaiman.

What is our preparation to meet Allah.

How many good deeds we do sincerely just for the sake of Allah not for the sake of likes, content on social media.

Insaf sangat. 

What is my secret

Deep.

Semoga sempat untuk mempunya secret with Allah.

Semoga Huda dapat masuk syurga Allah tanpa hisab.

Pengajaran banjir 2021

Terbaca catatan ini di muka buku membuatkan aku terus mengemas nak menilai untuk meminima kan item di dalam rumah dan minima kan "beban" dalam kehidupan. Semoga hisab kita semua dipermudahkan Allah kelak.

Nafsu nafsi manusia - banyak yang kita mahu tapi sebenarnya kita tak perlu.

Jom minimakan keperluan.  Banyak lagi orang yang boleh kita "belanja makan" jika kita tak membazir membeli kemahuan yang bukan keperluan.

Ingat 3 mentera ni sebelum menambah "beban" !

Adakah kita PERLU

Adakah kita MAHU

Adakah kita MAMPU.

Kalau ter X salah satu, cuba tangguhkan dulu. Acapkali kita mahu dan mampu tapi kita tak perlu puan. Sebab tu PERLU berada dalam carta nombor 1. 

****************************************

Faiz Mansor

24 Dec 2021  · 

Satu lagi pelajaran berharga.

Ada rumah barangnya penuh segenap sudut. Ada rumah ringkas saja isinya, cukup2 utk kegunaan harian saja.

Apabila disapu bah dan disalut lumpur, rumah yg isinya ringkas itu mudah dan cepat diuruskan. Manakala rumah yg isinya penuh, memerlukan berpuluh tenaga kerja, mengambil masa sampai berhari2 utk diselesaikan.

Di masa itu, pemilik rumah yg ringkas itu pasti berasa sgt2 bersyukur kerana dimudahkan urusan walau dlm musibah.

Begitulah AKHIRAT nanti. Mereka yg hidup sekadarnya amat mudah dan ringan hisabnya dihadapan Allah. Manakala yg mengumpul harta dan berlumba2 mengejar dunia, hisabnya AMAT BERAT (seperti beratnya lumpur), lambat dan siksa sekali kerana memakan masa ribuan tahun kerana setiap butir harta dan masa kita akan dihitung, apa tujuan harta itu dan bagaimana ia dimanfaatkan.

Bersediakah kita dgn jawapan? Kerana yg memberi jawapan di hadapan Allah itu nanti hanyalah KEBENARAN. Mustahil lagi berlaku tipu helah.

Sama2 kita dalami dan mentadabbur surah At-Takathur.

At-Takathur: 1

أَلۡهَىٰكُمُ ٱلتَّكَاثُرُ

Kamu telah dilalaikan (daripada mengerjakan amal bakti) oleh perbuatan berlumba-lumba untuk mendapat dengan sebanyak-banyaknya (harta benda, anak-pinak pangkat dan pengaruh), -

At-Takathur: 2

حَتَّىٰ زُرۡتُمُ ٱلۡمَقَابِرَ

Sehingga kamu masuk kubur.

Fahamilah hingga akhir ayat.

Ujian dunia ini adalah nikmat. Kerana mereka yg beriman akan benar2 diuji. Dan mereka yg beriman, ganjarannya SYURGA YG KEKAL ABADI.

****************************************

Semoga bermanfaat.

Harapan 2022 Sayonara 2021

31 Disember 2021

Hari jumaat dan hari terakhir 2021 ... 

Saya doakan semoga kita semua dimurahkan rezeki yang diberkati

diberikan kesihatan yang baik,

hidup yang tenang, senang, bahagia dan membahagiakan.

jadi orang yang lebih baik, anak yang lebih soleh/solehah, 

pekerja yang cemerlang untuk membangunkan semula negara 

dan semoga kita semua beroleh kesudahan yang baik dalam hidup dan diberi syurga tingkatan yang paling best.

insha Allah.

Percaya dan yakinla

Tiada yang mustahil

Tidak ada yang mustahil dengan adanya harapan.

Percaya dan yakinla

Jadilah mulia seperti awan

Jadilah sumber untuk memberi

Hulurkan tangan dan

Hapuskanlah kesedihan

TANPA MENGHARAPKAN BALASAN DAN PUJIAN

Walaupun tahun-tahun berlalu

jangan rasakan sudah terlambat

Kita semai / tanam, dan yang lain mendapat maanfaat darinya

itulah aturan alam dan kehidupan

Jika hidup dengan HARAPAN

Perkara yang mustahil boleh jadi NYATA

Dengan keteguhan IMAN, 

anda boleh mencapainya

lebih tinggi dari puncak gunung

lihatlah impian mu yang kau rasakan jauh

dan hiasilah dengan keyakinan dan IMAN

dan kemahuan sekuat BESI

Kau akan dapati impianmu bisa menjadi NYATA

Insha Allah.

Sayonara 2021.

Semoga diberi perhitungan yang baik di sisi NYA.

Kat mana nak guna AI dan Machine Learning dalam real life?

AI tu bukan semata²

Artificial Intelligence.

AI tu lebih penting lagi 

 * Akhlak Intelligence

 * Adab Intelligence

Mana mungkin Artificial Intelligence itu menandingi "Adam" Intelligence. 

#bilahudatulis

*************************

With all the excitement and hype about AI that’s “just around the corner”—self-driving cars, instant machine translation, etc.—it can be difficult to see how AI is affecting the lives of regular people from moment to moment. What are examples of artificial intelligence that you’re already using—right now?

Some old example of using artificial intelligence and machine learning in real life practice.

There are so many amazing ways artificial intelligence and machine learning are used behind the scenes to impact our everyday lives and inform business decisions and optimize operations for some of the world’s leading companies. Here are 27 amazing practical examples of AI and machine learning.

Consumer goods

Using natural language processing, machine learning and advanced analytics, Hello Barbie listens and responds to a child. A microphone on Barbie’s necklace records what is said and transmits it to the servers at ToyTalk. There, the recording is analyzed to determine the appropriate response from 8,000 lines of dialogue. Servers transmit the correct response back to Barbie in under a second so she can respond to the child. Answers to questions such as what their favorite food is are stored so that it can be used in conversation later.

Coca-Cola’s global market and extensive product list—more than 500 drink brands sold in more than 200 countries—make it the largest beverage company in the world. Not only does the company create a lot of data, it has embraced new technology and puts that data into practice to support new product development, capitalize on artificial intelligence bots and even trialing augmented reality in bottling plants.

Even though Dutch company Heineken has been a worldwide brewing leader for the last 150 years, they are looking to catapult their success specifically in the United States by leveraging the vast amount of data they collect. From data-driven marketing to the Internet of Things to improving operations through data analytics, Heineken looks to AI augmentation and data to improve its operations, marketing, advertising and customer service.

Creative Arts

Culinary arts require the human touch, right? Yes and no. AI-enabled Chef Watson from IBM offers a glimpse of how artificial intelligence can become a sous-chef in the kitchen to help develop recipes and advise their human counterparts on food combinations to create completely unique flavors. Working together, AI and humans can create more in the kitchen than working alone.

Another way AI and big data can augment creativity is in the world of art and design. In one example, IBM’s machine learning system, Watson, was fed hundreds of images of artist Gaudi’s work along with other complementary material to help the machine learn possible influences for his work including Barcelona, its culture, biographies, historical articles and song lyrics. Watson analyzed all the information and delivered inspiration to the human artists who were charged with the creating a sculpture “informed” by Watson and in the style of Gaudi.

Music-generating algorithms are now inspiring new songs. Given enough input—millions of conversations, newspaper headlines and speeches—insights are gleaned that can help create a theme for lyrics. There are machines such as Watson BEAT that can come up with different musical elements to inspire composers. AI helps musicians understand what their audiences want and to help determine more accurately what songs might ultimately be hits.

Energy

Global energy leader, BP is at the forefront of realizing the opportunities big data and artificial intelligence has for the energy industry. They use the technology to drive new levels of performance, improve the use of resources and safety and reliability of oil and gas production and refining. From sensors that relay the conditions at each site to using AI technology to improve operations, BP puts data at the fingertips of engineers, scientists and decision-makers to help drive high performance.

In an attempt to deliver energy into the 21^st century, GE Power uses big data, machine learning and Internet of Things (IoT) technology to build an “internet of energy.” Advanced analytics and machine learning enable predictive maintenance and power, operations and business optimization to help GE Power work toward its vision of a “digital power plant.”

Financial Services

With approximately 3.6 petabytes of data (and growing) about individuals around the world, credit reference agency Experian gets its extraordinary amount of data from marketing databases, transactional records and public information records. They are actively embedding machine learning into their products to allow for quicker and more effective decision-making. Over time, the machines can learn to distinguish what data points are important from those that aren’t. Insight extracted from the machines will allow Experian to optimize its processes.

American Express processes $1 trillion in transaction and has 110 million AmEx cards in operation. They rely heavily on data analytics and machine learning algorithms to help detect fraud in near real time, therefore saving millions in losses. Additionally, AmEx is leveraging its data flows to develop apps that can connect a cardholder with products or services and special offers. They are also giving merchants online business trend analysis and industry peer benchmarking. 

Healthcare

AI and deep learning is being put to use to save lives by Infervision. In China, where there aren’t enough radiologists to keep up with the demand of reviewing 1.4 billion CT scans each year to look for early signs of lung cancer. Radiologists need to review hundreds of scans each day which is not only tedious, but human fatigue can lead to errors. Infervision trained and taught algorithms to augment the work of radiologists to allow them to diagnose cancer more accurately and efficiently.

Neuroscience is the inspiration and foundation for Google’s DeepMind, creating a machine that can mimic the thought processes of our own brains. While DeepMind has successfully beaten humans at games, what’s really intriguing are the possibilities for healthcare applications such as reducing the time it takes to plan treatments and using machines to help diagnose ailments.

Manufacturing

Cars are increasingly connected and generate data that can be used in a number of ways. Volvo uses data to help predict when parts would fail or when vehicles need servicing, uphold its impressive safety record by monitoring vehicle performance during hazardous situations and to improve driver and passenger convenience. Volvo is also conducting its own research and development on autonomous vehicles.

BMW has big data-related technology at the heart of its business model and data guides decisions throughout the business from design and engineering to sales and aftercare. The company is also a leader in driverless technology and plans for its cars to deliver Level 5 autonomy—the vehicle can drive itself without any human intervention—by 2021.

The AI tech revolution has hit farming as well, and John Deere is getting data-driven analytical tools and automation into the hands of farmers. They acquired Blue River Technology for its solution to use advanced machine learning algorithms to allow robots to make decisions based on visual data about whether or not a plan is a pest to treat it with a pesticide. The company already offers automated farm vehicles to plough and sow with pinpoint-accurate GPS systems and its Farmsight system is designed to help agricultural decision-making.

Media

The BBC project, Talking with Machines is an audio drama that allows listeners to join in and have a two-way conversation via their smart speaker. Listeners get to be a part of the story as it prompts them to answer questions and insert their own lines into the story. Created specifically for smart speakers Amazon Echo and Google Home, the BBC expects to expand to other voice-activated devices in the future.

UK news agency Press Association (PA) is hoping robots and artificial intelligence might be able to save local news. They partnered with news automation specialist Urbs Media to have robots write 30,000 local news stories each month in a project called RADAR (Reporters and Data and Robots). Fed with a variety of data from government, public services and local authorities, the machine uses natural language generation technology to write local news stories. These robots are filling a gap in news coverage that wasn’t being filled by humans.

Big data analytics is helping Netflix predict what its customers will enjoy watching. They are also increasingly a content creator, not just a distributor, and use data to drive what content it will invest in creating. Due to the confidence they have in the data findings, they are willing to buck convention and commission multiple seasons of a new show rather than just a pilot episode.

Retail

When you first think of Burberry, you likely consider its luxury fashion and not first consider them a digital business. However, they have been busy reinventing themselves and use big data and AI to combat counterfeit products and improve sales and customer relationships. The company’s strategy for increasing sales is to nurture deep, personal connections with its customers. As part of that, they have reward and loyalty programs that create data to help them personalize the shopping experience for each customer. In fact, they are making the shopping experience at their brick-and-mortar stores just as innovative as an online experience.

As the world’s second-largest retailer, Walmart is on the cutting edge of finding ways to transform retail and provide better service to its customers. They use big data, machine learning, AI and the IoT to ensure a seamless experience between the online customer experience and the in-store experience (with 11,000 brick-and-mortar stores, something rival Amazon isn’t able to do. Enhancements include using the Scan and Go feature on the app, Pick-up Towers and they are experimenting with facial recognition technology to determine if customers are happy or sad.

Service

Central to everything Microsoft does is leveraging smart machines. Microsoft has Cortana, a virtual assistant; chatbots that run Skype and answer customer service queries or deliver info such as weather or travel updates and the company has rolled out intelligent features within its Office enterprise. Other companies can use the Microsoft AI Platform to create their own intelligent tools. In the future, Microsoft wants to see intelligent machines with generalized AI capabilities that allow them to complete any task.

When you bring together cloud computing, geo-mapping and machine learning, some really interesting things can happen. Google is using AI and satellite data to prevent illegal fishing. On any given day, 22 million data points are created that show where ships are in the world’s waterways. Google engineers found that when they applied machine learning to the data, they could identify why a vessel was at sea. They ultimately created Global Fishing Watch that shows where fishing is happening and could then identify when fishing was happening illegally.

Always at the top of delivery extraordinary service, Disney is getting even better thanks to big data. Every visitor gets their own MagicBand wristband that serves as ID, hotel room key, tickets, FastPasses and payment system. While guest enough the convenience, Disney gets a lot of data that helps them anticipate guests’ needs and deliver an amazing, personalized experience. They can resolve traffic jams, give extra services to guests who may have been inconvenienced by a closed attraction and data even allows the company to schedule staff more efficiently.

Google is one of the pioneers of deep learning from its initial foray with the Google Brain project in 2011. Google first used deep learning for image recognition and now is able to use it for image enhancement. Google has also applied deep learning to language processing and to provide better video recommendations on YouTube, because it studies viewers’ habits and preferences when they stream content. Next up, Google’s self-driving car division also leverages deep learning. Google also used machine learning to help it figure out the right configuration of hardware and coolers in their data centers to reduce the amount of energy expended to keep them operational. AI and machine learning has helped Google unlock new ways of sustainability.

Social Media

From what tweets to recommend to fighting inappropriate or racist content and enhancing the user experience, Twitter has begun to use artificial intelligence behind the scenes to enhance their product. They process lots of data through deep neural networks to learn over time what users preferences are.

Deep learning is helping Facebook draw value from a larger portion of its unstructured datasets created by almost 2 billion people updating their statuses 293,000 times per minute. Most of its deep learning technology is built on the Torch platform that focuses on deep learning technologies and neural networks.

Instagram also uses big data and artificial intelligence to target advertising and fight cyberbullying and delete offensive comments. As the amount of content grows in the platform, artificial intelligence is critical to be able to show users of the platform information they might like, fight spam and enhance the user experience.

RUJUKAN:

https://emerj.com/ai-sector-overviews/everyday-examples-of-ai/

https://www.forbes.com/sites/bernardmarr/2018/04/30/27-incredible-examples-of-ai-and-machine-learning-in-practice/#7194c80b7502

https://bigdata-madesimple.com/top-10-real-life-examples-of-machine-learning/

Apa itu Gig Economy

 What do you know about gig economy?

Sebut dah macam hipster dah. hahaha.

Kalau ikut kamus, gig tu maksud mudah dia temporary.

Kalau ikut asal usul gig ni - dia muncul sebab gig performance dalam music/ street music. Rasional dia, orang music buat performance kan bukan selamanya. Akan ada pengakhiran. So key dia temporary.

Tapi gig economy - betul ke macam tu?

Economy yang sementara?

Dulu-dulu zaman mak ayah or kakak abang kita, nature nya kalau dapat keje gomen, seseorang tu dikira bertuah yang amat.

Sebab full time job dan secure job, and key point dia ada pencen, pastu kalau sakit boleh p spital kerajaan.

Pastu seiring dengan peredaran zaman, ecewah zaman kita (eh zaman saya la - sebab "kita" tu subjective la pula bergantung sapa yang baca kan.... hihihi).

Ok zaman saya, we always tot that orang yang dapat kerja private, mnc, glc, perh kira hebat tau. Sebab kerja tetap, gaji banyak, dapat profit sharing, bonus, medical benefit, etc.

So key point dia dulu2 orang nak cari kerja tetap dan secure. Tapi mungkin dulu2 kerja boleh balik on time, still ada masa untuk buat aktiviti lain selain daripada kerja hakiki, ada masa dengan keluarga etc.

Tapi sekarang, kerja macam tak sudah2, tak habis2, So banyak dah beralih nak cari kerja yang ada work life-balance.

Maka seiring dengan kemajuan teknologi dan peningkatan / pengukuhan ekonomi.... nature tu berubah lagi.

Bukan semua orang look forward nak kerja gomen or nak kerja mnc.... tapi mungkin nature sekarang nak cari kerja senang i.e. flexible dan boleh susun jadual sendiri sebab nak ada freedom. Depa kalau boleh nak kerja dari atas katil je. Duit dihujung jari. Tapi ada juga flexible ni bagi sesetengah orang tapi pekerjaan yang sama tu as itu je la option yang seseorang yang lain tu pula ada. Contoh macam rider food delivery. Ada yang jadi rider tu saja suka2 nak cari duit poket, tapi ada yang betul2, tu je pekerjaan yang dia boleh buat dan dah jadi full time and main source of income dia.

So semakin hari semakin susah nak ukur pergerakan ekonomi yang melibatkan pergerakan manusia yang dinamik.

Kalau ikut term dan definisi ILO, ada 2 standard utama yang diguna pakai iaitu:

1) International Classification of Status in Employment (ICSE) - ni pecah 2 lagi iaitu "type of authority" dan satu lagi type of economic risk", 

dan standard kedua ialah:

2)International Classification of Status at Work (ICSaW)

Versi dulu2, status of employment ni ada basic 6 je. 

Employer,

Employee,

own account workers,

members of producers'cooperative,

contributing family workers (atau kalau kat sini digunakan unpaid family workers) dan

workers not classifiable by status. ni versi icse-93 kalau tak silap.

yang recent depa bincang icse-18 (merujuk kepada conference tahun 2018 kalau tak silap), list dan definisi status of employment tu makin panjang dan details. Which you'll find term such as dependent and independent worker with or without employees, crowdwork, just-in-time workforce and many more (boleh rujuk di laman web ILO). 

sorry sebab dah tak rajin nak tulis. hihihi....

So berbalik kepada gig economy ni, kebanyakan study adalah tentang orang yang kerja ada platform dan biasanya menggunakan digital platform. Digital platform ni pula terbahagi kepada 2 la at least iaitu berasaskan web (contoh freelance market place, jual beli online tu kan macam fashionvalet, shopee etc, pastu yang jadi youtubers / creative content, teaching online, eh ngajo buat kek online pun ada and a lot more sampai tak terkira). Dan satu lagi platform berasaskan lokasi contoh macam uber, air bnb etc.

Tapi tengah2 depa study, depa dok terfikir balik ehhh tadi kata gig tu sementara - so tak kisahla ada platform ke tidak kan. Haaa sudah. confuse.

Macam ada satu research paper kat uk ni : Gig Economy: Introduction (House of Lords Library Briefing) Author: James Ainsworth, 2017, dia study gig workers/ economy ni berasaskan 6 sektor iaitu Taxi Driving, Food Delivery, Good Couriers,Skilled Manual Labours, Unskilled Manual Labours, dan yang ke-6, Professional, Creative and Administrative Labour

Sebabnya kewujudan bentuk ekonomi baharu ini yeah turut memberi isu dan ancaman kepada ekonomi tradisi contoh:

uber vs taxi

airbnb vs hotel

etc.

Dan disebabkan pergerakan kerja yang dikerjakan yang menghasilkan income ni terlalu robust, maka setiap pengkaji yang menjalankan kajian akan define sendiri apa term gig yang diaorang nak pakai dan nak kaji dan untuk tujuan apa.  

Why we need to measure this gig workers? Of course la, depa gheja, depa earn, depa spend bukankah itu ada pergerakan ekonomi. Perlu la ianya diukur. Flexibility, source of income, working hours, social protection, epf, tax etc. there are bundle of issues and challenges yang boleh disenaraikan.  SO end up kita perlukan la encik robot ai barangkali untuk tlg p study pasal gig ni. hihihi...

ok cukup la tu sebab nanti bebelan ni jadi panjang sangat pula.

nanti la kita baca lagi dan tengok apa yang boleh di buat.

Okay bye. #berentisecaratiba2danmengejutsebabdahmengantok

Wassalam.

#bilahudatulis

Apa itu BLOCK + CHAIN = BLOCKCHAIN

Sementelah kena buat kerja ni marilah kita melayan satu topik yang hipster iaitu BLOCKCHAIN.

Apa itu blockchain?

Alah alah alah.... Ramai acah-acah faham tapi ye ker faham atau banyak salah faham. hihihi. Yer termasuk saya la tu yang acah faham tapi ntah faham ke tidak sebenarnya.

Justeru marilah nak kisahkan apa yang difahami tentang blockchain ni.  Kalau ter salah faham, bolehlah yang faham tolong betulkan. kerana dakhuda baru belajar. Kalau salah tolong tunjukkan, jangan marah-marah. Gitcheww.

Kalau ikut kefahaman saya dengan bahasa mudah. 

BLOCKCHAIN = BLOCK + CHAIN

hihihi ....  mudah bukan? #siapamarahnantikenajualTQ

Konsepnya dia terdiri daripada BLOCK dan CHAIN. Tapi iyalah, apa yang di BLOCK kan dan apa pula yang di CHAIN kan.

Kalau ikut apa yang saya faham, dengan bahasa mudah

1. BLOCK - fungsi dia menyimpan maklumat dalam bentuk digital.

2. information yang disimpan tu mestilah information yang PENTING/ BERHARGA. Namun, Penting bagi setiap orang tu berbeza

tp commonly - aset/ harta.

kalau kita google blockchain dia mesti direct ke bitcoin. Tapi blockchain ni bukan bitcoin je sebenarnya. Ada group yang valuable information nya  ialah DATA erm contoh data voting, data kesihatan, dan macam2 lagi. Even kalau nak simpan rekod pelajar yang selesai bergraduasi pun boleh. Maka bolehlah kita trace and track kes ijazah palsu ni. hihihi.

Contoh mudah sikit (M-A-Y-B-E)

contoh transaction yang disimpan dalam BLOCK ni biasanya benda yang penting la.So apa benda yang penting untuk manusia harini? DUIT dan HARTA. 🤭

Kita simpan HARTA tu tadi lepas tu kita track and trace macam mana pergerakan harta tu tadi. Something like macam mana dia di pass down kan to others.

Macam contoh yang selalu diberi transaksi kewangan – macam mana direkodkan keluar masuk dari person A ke person B ke C dan seterusnya.

Memandangkan pergerakan tu secara digital, maka setiap transaksi akan diberi kod. Kod tu selalunya Panjang berjela dan biasanya nombor la. Kadang kalau perasan, bila kita buat transaksi akan keluar no Panjang-panjang kat url  contoh macam ni 18c177926650e5550973303c300e136f22673b74. 

Ok no panjang2 ni biasanya dia panggil digital signature …. Sebab everytime kita nak buat transaksi kewangan, kan kita kena log in, masuk username, and password, ada verification code lagi dan sebagainya.  So setiap tapisan ni adalah yang kita ketahui untuk tujuan keselamatan.  Tapi little that people know, setiap layer keselamatan ni la yang membentuk code nombor yang Panjang berjela tu.

Alaaa macam TAC Code Maybank2u yang korang terima tu. Haaa contoh mudah la tu nak bagi faham. Sebab tu kita diberi peringatan JANGAN KONGSI NO TAC dengan sesiapa. Ini mungkin salah satu sebabnya.

Cuma saya tak pasti nombor tu di generate ada algorithm atau tidak. Kalau ada pattern of algorithm, maknanya tak secure sebab finally dia akan boleh di hack. ini sis tak pasti - biasalah dah malas membaca. hahaha

Tapi transaction tu memang orang yang ada akses memang boleh tengok. Tengok transaksi tau – maksudnya pergerakan harta tu pergi mana. Yang sepatutnya dia tak boleh tengok ialah security code / algorithm yang menggerakkan harta tu. Dan security code tu biasanya susah dan dia claim tak ada sapa boleh tembusi la code tu sebab di generate beberapa layer dah.

Tapi yang pasti dengan adanya block of information ni, kita boleh trace setiap transaksi kewangan tu pergi mana.

Kalau duit, kita mungkin la tak nampak sangat ke sebab kita tak pegang physical duit tu. 

Tapi ada satu video yang saya tonton tu, information yang disimpan dalam block tu – adalah geran tanah. Dan dia tunjuk macam mana geran tanah kan disimpan dari generasi ke genarasi tapi in between ada yang cuba macam manipulate la cakap geran tanah tu dia punya dan dah dijual oleh great great great grandfather or what not.   Tapi bila generasi baru yang faham blockchain ni, dia boleh call for investigation dan trace balik setiap transaction pasal geran tanah tu tadi. 

Okay itu BLOCK (contain of valuable digital information)

tapi information tak disimpan untuk jadi khazanah.

dia disimpan untuk di share tapi with selected people.

Maka CHAIN tu datang kat mana? The pass down transaction tu akan create many other BLOCK of information yang pada akhirnya membentuk rantaian.

Dan again macam konsep security (password, secure code etc as explained above), setiap chain tu akan dihubungkan melalui apa yang dipanggil NODES.

so, to hands down or pass down the information - perlukan CHAIN. dan chain perlu dikawal dengan security layer. Dan nak cerita pasal chain dan nodes ni mungkin perlu karangan siri lain.

Macam biasalah sis dah ngantok, jadi bebelan ni berhentilah secara mengejut macam biasa. 

Tapi sebelum bersurai sis nak bagitau, sebenarnya kalau di google, memang banyak article tentang blockchain ini. Antara kefahaman yang rasa acah-acah nak faham mungkin boleh cuba baca kat link ni:

RUJUKAN:

• https://www.investopedia.com/terms/b/blockchain.asp
• https://cointelegraph.com/bitcoin-for-beginners/how-blockchain-technology-works-guide-for-beginners?fbclid=IwAR32bipEV9QL6A4Knl2tUQZ3_Y5s2G0MDT1m-nUHyPofNmjbrlKJVfx7GDc
• https://hackernoon.com/blockchain-technology-explained-introduction-meaning-and-applications-edbd6759a2b2?fbclid=IwAR0ebeyRX2e2g1Z58FdZd6T4LbTKVZ_IHZCxIPywO1vqc6G45tQjHlz4R-U
• https://blockgeeks.com/guides/what-is-blockchain-technology/?fbclid=IwAR32bipEV9QL6A4Knl2tUQZ3_Y5s2G0MDT1m-nUHyPofNmjbrlKJVfx7GDc
• https://www.guru99.com/blockchain-tutorial.html?fbclid=IwAR2y_2kM0muFxEHpxKjU3JSV7B45xxdEexG800sBeQFd53skU3dQPqzGb70
• https://medium.com/@essentia1/50-examples-of-how-blockchains-are-taking-over-the-world-4276bf488a4b

so tu je la nak bebel. kalau sis salah faham, tolong perbetulkan ya. terima kasih.

Untuk itu sekian.

Selamat tidur.

#bilahudatulis

Trauma Pelancongan akibat Covid-19

Penutupan yang berkaitan dengan pandemik, pembatalan penerbangan, dan penutupan sempadan telah menyebabkan masalah pada rancangan percutian. Penurunan bilangan pelancong yang mendadak akan memberi kesan yang sangat besar pada negara-negara yang bergantung pada pelancong asing - dengan kesan yang berpotensi besar pada ekonomi mereka i.e the KDNK / GDP. Costa Rica, Greece, Morocco, Portugal, and Thailand antara yang paling terkesan dengan kerugian hasil pelancongan melebihi 3 peratus daripada nilai KDNK, menurut Laporan Sektor Luar 2020 yang dikeluarkan IMF baru-baru ini. Capaian asal di LINK INI.

Carta ini menunjukkan kesan langsung pelancongan terhadap import, eksport, dan baki akaun semasa dalam senario yang membayangkan pembukaan semula secara beransur-ansur pada bulan September tetapi menyaksikan penurunan sekitar 70 peratus dalam penerimaan pelancongan dan kedatangan pelancongan antarabangsa pada tahun 2020

Bagaimana situasi di Malaysia? 

Sektor pelancongan didapati mudah terdedah kepada konflik bersifat dalaman dan global seperti bencana alam, wabak, kemelut politik dan juga krisis kewangan. Sepanjang tempoh 1991-2019, ketibaan pelancong ke Malaysia beberapa kali mengalami kemerosotan, khususnya pada tahun 1998 yang berpunca daripada krisis ekonomi di peringkat global. Wabak SARS pula menyebabkan pertumbuhan bilangan ketibaan merosot pada tahun 2003 sebanyak 20.4 peratus. Pelancongan negara turut berhadapan dengan bencana jerebu pada tahun 2015 serta isu insiden MH370 dan MH17 pada tahun sebelumnya. Wabak COVID-19 merupakan cabaran paling getir kepada prestasi pelancongan negara dan memaksa pembatalan Kempen Melawat Malaysia 2020. Dijangkakan ketibaan pelancongan pada tahun tersebut mengalami pertumbuhan defisit sehingga 65 peratus.

Pelancongan merupakan salah satu industri yang strategik, berpotensi dan menyumbang secara dinamik kepada pertumbuhan ekonomi negara. Akaun pengeluaran sektor pelancongan merekodkan sumbangan RM220.6 bilion (15.24%) pada tahun 2018 berbanding RM56.4 (10.38%) bilion pada tahun 2005 kepada pertumbuhan ekonomi.

Sumber carta : DOSM dan IMF

Halangan merentas sempadan negara di harapkan dapat memberi impak positif pada sektor pelancongan domestik. Tempahan penginapan sudah semakin rancak di mana rata-rata hotel telah mulai fully booked dengan tawaran harga yang menarik.

Jom sokong industri pelancongan tempatan.
Tapi awas. Jangan lupa jaga diri. COVID masih berleluasa.

Sekian.

#bilahudabebel

Isu Dan Cabaran Pekerjaan Masa Depan ((FUTURE OF WORK))

Kehidupan pasca-covid19

Tahun 2020 yang mencabar!

Sekiranya disemak daripada sudut sejarah, perubahan dan kemajuan teknologi telah mengubah struktur dan komposisi pekerjaan seperti dari pertanian dan pertukangan di abad ke 19, berubah ke sektor pembuatan dan pengkeranian, perkhidmatan dan pengurusan pentadbiran pada abad ke 20. Perubahan teknologi dikatakan tidak menyebabkan berlakunya kehilangan atau pengurangan pekerjaan tetapi melibatkan perubahan struktur dan kemahiran dalam pekerjaan.

Perubahan dan kemajuan teknologi yang turut membawa perubahan dalam struktur pekerjaan akan turut memberi implikasi kepada bidang pendidikan dan jurang pendapatan yang dijangka semakin besar. Krueger (1993) mendapati pekerja yang menggunakan komputer memperolehi pendapatan kira-kira 10 hingga 15 peratus lebih besar berbanding pekerja yang tidak menggunakan komputer. Penyesuaian terhadap teknologi dan kemahiran terkini ini menyebabkan ramai yang perlu menjalani latihan atau mengikuti kursus-kursus tambahan bagi menaik taraf kemahiran dan pengetahuan masing-masing supaya kekal relevan dalam industri masa kini.

Therefore, to ensure we remain relevant in the future of work league, the three main skills we need to have i.e.

cerdik,
inovasi,
entrepreneurship skills.

Tetapi cerdik tu bukan menisbahkan kepada bilangan A yang banyak semata-mata. End game kepada future works = working hours kurang, pengeluaran dan pencapaian meningkat, pendapatan meningkat.

Pembentukan talent yang berterusan.

Re-tooling dan re-skilling bukan semata-mata untuk dapat better master n degree certificate. Pembangunan modal insan perlu berlaku secara formal dan informal.
Supply and demand – will be forever issue

Indeed the need for Re-skilling, upskilling are crucial! Hakikatnya perubahan teknologi – bukan mudah reflect pada modul latihan dan silibus pengajian.
Bergerak ke negara maju. Tapi apa yang dimaksudkan?

Kita membayangkan semua orang di Malaysia perlu jadi pekerja mahir dan hebat. Negara yang maju macam mana sekalipun akan tetap ada pekerja yang mahir, separa mahir dan kurang mahir. Teknologi hebat BUKAN semata-mata bermaksud kena ada teknologi aeroangkasa, bukan mesti kena ada digital teknologi AI, ML, robotic semata. Tetapi apa yang lebih ideal, upgrade daily routine work jadi lebih baik.
DIRTY | DANGEROUS | DIFFICULT

Negara maju pun ada kerja 3D ni. Kutip sampah, panjat bangunan tinggi. Persoalan yang perlu kita selesaikan - adakah pekerjaan itu boleh digantikan oleh high technology. Adakah forever kerja mengutip sampah tu perlu nature kerjanya kotor, sampah air menitik2.
3D perlu masuk dalam polisi negara.

Pasca COVID-19 harini sepatutnya 3D bukan bermaksud mesti dibuat pekerja asing.

Dirty – make it cleaner

Dangerous - make it safer

Difficult – make it easier

Garbage collection is daily life routine. Juster harus difikirkan dan dipolisikan macam mana nak ubah nature kerja garbage collection di Malaysia supaya jadi lebih baik.

Reversing the 3D
Jawapan 3D bukan Foreign Workers, tapi membangunkan teknologi supaya 3D dapat ubah.

Persoalannya!

Bersediakah Malaysian untuk buat kerja 3D tu – ekoran sentiment dan income yang sangat rendah.

Bersediakah majikan nak bagi bayaran yang setimpal.

Sekian #bilahudatulis