Diari RMCO2020 (Day - Lost count) COVID-19 : Bala atau Ujian

 بِسۡـــــــــمِ ٱللهِ ٱلرَّحۡـمَـٰنِ ٱلرَّحِـــــــيم

اَللَّهُمَّ صَلِّ َعلى سيدنا مُحَمَّدٍ وَ عَلَى آِل سيدنا مُحَمَّدٍ ْ ِ  

‏أَلًْلّٰهُمَّ إِنِّي أَسأَلُكَ الۡعَافِيَۃَ

Ya Allah, TERIMA KASIH atas kehidupan hari ini untuk NAFAS dan REZEKI yang Engkau limpahkan.

Jadikanlah permulaan hari ini penuh dengan KEBAIKAN, pertengahannya membawa KEJAYAAN dan pengakhirannya suatu KEBERUNTUNGAN..

Jadikan awalnya RAHMAT, pertengahannya NIKMAT dan penghujungnya PENUH BERKAT..

Ya Allah, beri kan lah kami semua ‘Afiyah serta kesihatan yang baik, dipermudahkan segala urusan duniawi dan juga ukhurawi, mendapat rahmat, nikmat, keberkatan dan keredhaan dari mu Ya Allah.  

رَبَّنَا ظَلَمْنَا أَنْفُسَنَا وَإِنْ لَّمْ تَغْفِرْلَنَا وَتَرْحَمْنَا لَنَكُوْنَنَّ مِنَ الْخَاسِرِيْنَ

رَبَّنَا ءَاتِنَا فِى الدُّنْيَا حَسَنَةً وَفِى اْلآخِرَةِ حَسَنَةً وَقِنَا عَذَابَ النَّارِ

Sehinggan 23 Disember 2020, jumlah kes kumulatif Covid-19 di Malaysia telahpun mencecah angka 98,737 kes mengatasi China yang mencatatkan kes 86,882 (ada yang mendakwa China tidak mengemaskini atau tidak berkongsi rekod penularan wabak di negara mereka yang terkini)

Disaat kebanyakkan negara masih mengawal pintu sempadan dan sedang berura-ura untuk kembali menutup pintu sempadan antarabangsa ekoran penemuan variant Covid-19 yang baru yang telah termutasi dengan genom yang lebih mengganas (katanya).

Tekanan baru muncul di Britain pada akhir November dimana UK mula menyiasat mengapa kadar jangkitan COVID-19 di Kent tidak menurun. Kajian sekumpulan pakar di UK menemui sekumpulan penyebaran yang cepat di England dan London tenggara yang dikaitkan dengan varian coronavirus. Namun, banyak yang masih belum diketahui mengenai jenis virus ini, yang dikenali sebagai garis keturunan B.1.1.7. Strain ini terkenal karena jumlah kes yang meningkat di beberapa bahagian di England, dan jumlah kes dan jumlah wilayah yang melaporkan jangkitan daripadanya semakin meningkat, menurut COVID-19 Genomics Consortium UK (COG-UK).

Semalam (23 Disember 2020), Malaysia pula mengesan mutasi baharu virus A701V. Tetapi masih belum mengesahkan kekuatan mutasi baru ini.

Dalam masa yang sama kerajaan sedang merancang kesesuaian untuk membuka kembali pintu sempadan bagi pemacuan ekonomi.  Yang mana saya pasti keputusan ini membimbangkan sebahagian besar rakyat terutamanya petugas barisan hadapan.

Pelbagai reaksi masyarakat bila disebut tentang waba ini. Penyakit “Wahn” – cinta dunia takut mati.

Sekarang ni memang semua sedang wahn dari wuhan (takut mati). Adakah waba yang melanda petanda kemurkaan, ujian, teguran atau bala ?

Apa sahaja penyakit dan musibah, waba yang berlaku, itu petanda dunia semakin menuju ke penghujung.

Apa tanda burung perepat,

dalam semak kaki tersula.

Apa tanda kiamat dah dekat

Bumi bergolak mengirim bencana.

(pantun ustaz badlishah)

 

Bencana ni ada banyak bentuk, antaranya

Kegagalan teknologi (contoh pesawat jatuh, keretapi tergelincir, kapal karam, pesawat hilang tak jumpa sampai sudah) 

Bencana sosial politik (konflik, rusuhan, peperangan termasuklah penyebaran waba.

Macam sekarang ni covid-19, sebelum ni ada h1n1, influenza, denggi, sars, merscov dan macam2 lagi.

Bencana geogologis klimatologis (tsunami, gempa bumi, taufan, banjir)

Orang Islam dah lama diperingatkan tentang semua ini. Tapi jangan sampai kita tak dapat melihat rahmat di sebalik kejadiann.

Apa makna musibah?

Diambil dari ayat quran

Surah At-Taghabun. Ayat 11: Tidak ada sesuatu yang berlaku kepada seseorang melainkan dengan izin Allah dan sesiapa yang beriman kepada Allah, Allah akan memimpin hatinya (untuk menerima apa yang telah berlaku itu dengan tenang dan sabar) dan (ingatlah), Allah Maha Mengetahui akan tiap-tiap sesuatu.

Baik atau buruk semua dengan izin Allah.

Tapi bagi manusia kalau buruk tu musibah, yang baik tu nikmat.

Wallahualam.

Hakikatnya, tiada wang pun mati, kena covid pun mati.

Sesungguhnya mati iku sangat pasti. Ianya sunnatullah.

Doalah sungguh-sungguh

Ya Allah Ya Rahman, Ya Rahim, Ya Rauf, Ya Ghaffur, Ya Ghaffar, Ya Affuw, Ya Tawwab, semoga Huda sekeluarga dan semua yang membaca doa ini diberi kesudahan yang baik, dengan iman sempurna dan taubat yang diterima Allah dan ada tempat disyurga NYA buat kita semua. Insha Allah. Ameen.

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

Jom Simpan Emas

Bab1: Jom Simpan Emas | Bab 2: Tips beli simpan jual emas | Bab 3: Kenali Jenis Emas | 

Bab 4: Jangan Tangguh Menyimpan Emas

 Assalamualaikum dan Hye

Lamanya tak menulis tentang benda yang saya suka nak tulis. Hi hi hi. Nak tulis pasal travel pun dah lama tak travel. Nak balik kampung pun kena kebenaran polis segala bagai. Ya Allah lamanya covid-19 ni membumi. Semoga segeralah covid durjana ni berlalu pergi.

Tayyib.  Hari ini kalut beberapa group whatsApp sembang tentang kejatuhan harga emas.

Ada yang rasa "alaaaa menyesal beli kelmarin dulu"

harga pada 24/11 RM267

harga pada 25/11 RM261

harga pada 28/11 RM259

Ni harga emas 999 di public gold tau.

 HAKIKATNYA ...

So korang nak jatuh kategori menyesal yang mana?

Momentum jangka pendek untuk harga emas dilihat menurun, dan Chris Vermeulen, ketua strategi pasaran dri Technical Traders mengatakan bahawa support level harga $1,810 dapat diuji sebelum ‘langkah besar’ seterusnya.

Namun, jika harga terus menunjukkan trend di bawah $1,810 per auns, harga emas dijangka akan terus turun hingga $1,600.

Beberapa isu dibincangkan yang merupakan faktor penurunan harga ini adalah:

1. Kesan pengumuman vaksin pandemik Covid-19 ke atas emas
2. Ekuiti
3. Emas: tahap sokongan dan ramalan jangka panjang, dan
4. Pelombong emas

Video analisa teknikal penuh boleh rujuk kat LINK SINI

Ada banyak sebab kenapa kita perlu / boleh simpan emas. Tapi bagi saya, keperluan untuk ada simpanan emas ialah 

1. Mempelbagaikan bentuk simpanan untuk kelangsungan hidup masa depan
2. Harga emas meningkat dalam jangka masa panjang i.e. kuasa beli emas adalah stabil
3. Ketidak tentuan nilai matawang kertas di mana bagi menerbit mata wang kertas, cagarannya masih lagi emas.
4. Simpan emas mungkin tidak menjadikan kita kaya tapi simpan emas kita boleh KEKAL kaya. 

Analogi dia mudah je.

nilai RM100  pada tahun 2000 besar tau, boleh beli groceries penuh trolley.

nilai RM100 pada tahun 2020 1/4 trolley je weih.

tapi kata la pada tahun 2000 korang ada 10 gram emas (pada harga RM100)

tapi pada tahun 2020 korang masih ada 10 gram emas (pada harga RM 2500)

Meh tengok graf ni:

Sumber: https://goldprice.org/

Simpanan emas ni keuntungan dia nampak untuk jangka masa panjang.  

Tapi tengok graf ni ada turun naik. Acaner tu?

Betul kalau kita tengok graf ni, harga emas memang ada turun naik dalam jangka masa pendek.  Tetapi dalam jangka masa panjang, harga emas masih lagi dalam momentum menaik.

Emas mampu mengekalkan kuasa beli pada barangan dalam jangka masa yang panjang. Kiranya emas ni kalis inflasi la.

1 dinar emas suatu ketika dahulu boleh beli seekor kambing.

1 dinar emas hari ini masih sama boleh beli seekor kambing.

Sedangkan dari segi RM, harga kambing tu dah berubah.

Ha silakan pergi cek harga kambing sekarang. hi hi hi.

SO APA TUNGGU LAGI!

Jom simpan emas.

Emas tu mungkin tak jadikan kita kaya.

Tapi dengan simpan emas, kita kekal kaya.

Insha Allah.

Nak tahu cara? Jom pm sis laju² .

Emas ni tak semestinya la korang buka dengan Public Gold. Ada banyak institusi yang korang boleh beli / simpan gold. Tapi kalau dah tak tahu sangat nak buka akaun simpanan emas, korang boleh mulakan dengan public gold.  Dia macam bank la, cuma bank tu korang simpan duit RM kertas (syiling pun boleh la. ha ha ha), tapi ni korang simpan GOLD. Dan gold ni korang boleh keluarkan fizikalnya pada bila-bila masa yang korang suka.

Kenapa korang boleh consider untuk buka akaun dengan public gold?

1. Sebab boleh buka secara online sahaja. Dan transaksi secara atas talian. Sistem online 24jam dan dikemaskini turun naiknya mengikut pasaran emas dunia. 
2. Nak keluarkan fizikal gold savings korang tu, boleh dibuat di branch atau menggunakan khidmat GIT (Gold in transit)
3. Belum ada lagi orang yang beli emas dari Public Gold dan tak dapat emas, semua dapat emas masing-masing.
4. syarikat emas di malaysia yang ada Sijil Patuh Syariah untuk semua jenis kaedah belian

 

Akaun gap public gold ni boleh dibuka dengan serendah rm100 dan tiada had maksimum.

Nak mulakan dengan 1gram pun boleh. 0.5gram pun boleh.

Macam kawan saya last week (25/11) dia buka akaun GAP RM100 so dalam akaun GAP dia ada (0.3831 gram).

Macam saya masa start beberapa tahun lepas sy mulakan dengan 1gram(saya bank in rm160++ utk harga 1gram gold pada masa tu).

Jadinya, kalau sekarang ni (28/11) awak nak start akaun harga gold 1gram rm259 pun boleh.

So dalaam akaun awak akan ada 1gram gold.

Sebab harga saat ni 1gram gold ialah rm259.

Tapi kalau buka dengan rm100, dalam akaun awak akan ada 0.3861 gram gold. 

Dalam akaun PG kita, dia tak papar RM tau.  Dia akan papar gram gold tu.

You can purchase gold anytime anywher as minimum as RM100 je.  Ala korang main kutu pun lebih rm100 kan sebulan.  So apa kata korang main kutu gold pula sekarang. simpan la RM100 sebulan dalam bentuk gold.

Tapi macam saya lebih prefer simpan dalam nilaian 1gram setiap kali atau 0.5 gram sebab senang nak kira. Hi hi hi. Ikut la masing-masing preference macam mana. 

Public gold di rekodkan gram emas kita up to 4 decimal point tau.

macam ni maksudnya.

sama ada korang nak purchase rm100 minimum at every transaction.

atau beli 1 gram terus senang kira.

SO APA TUNGGU LAGI!

Jom simpan emas.

Emas tu mungkin tak jadikan kita kaya.

Tapi dengan simpan emas, kita kekal kaya.

Insha Allah.

Nak tahu cara? Jom pm sis laju² 

reallife.nhhas@gmail.com

Kita ada support team untuk kekal kaya (survival mode) bersama-sama. Insha Allah.

Semoga bermanfaat ya kawan-kawan semua.

@loves_nhhas

First Batch

First Batch Master of Data Science and Analytics, PPST FST UKM

first-sem

kelas-terakhir

sebelum-final-exam-semester1

lecturer lagi muda dari iols.

lecturer ajak ambil gambar.

hihihi

mujur.

kalau tidak.

tak ada kenangan.

Graduation 03-11-2019

rezeki saya habis ontime

3 semester siap.

alhamdulillah.

walau pada awal nya sangat banyak drama.

siap call penaja nak quit sebab takut fail.

belum exam dah mimpi fail.

ntah apa2 huda. hihihi.

yang lain buat 4 semester atas kekangan yang pelbagai.

seperti bekerja sambil belajar dan sebagainya

apa yang penting, dapat konvokesyen sesi dan tarikh yang sama.

sekali harung

2nd batch pun konvo pada sidang yang sama.

hi hi hi.

first batch 7 orang

second batch 4 orang

saja simpan buat kenangan.

entri autopublish sempena setahuan graduation.

World Statistics Day 20-10-2020

Alhamdulillah.

Hari Statistik Negara telah diisytiharkan dan disambut secara tahunan pada setiap 20 Oktober bertujuan mengiktiraf sumbangan ahli statistik di Malaysia dan meningkatkan kesedaran terhadap kepentingan statistik di kalangan komuniti.

20th October juga merupakan Hari Statistik Dunia.  World Statistics Day mula disambut pada 20-10-2010 dan disambut setiap 5 tahun diperingkat antarabangsa.

Tahun ini sambutan di adakan secara atas talian.

Untuk mengelakkan sistur terlupa point penting yang sempat dicatatkan sepanjang sesi pembentangan teknikal paper yang sistur sempat hadiri, sistur share nota ringkas di sini. Untuk rujukan bila diperlukan. Ringkasan ni ada yang senior sis yang tulis juga.

Technical Paper 1: Uncertainty and Exchange Rates - Global Dynamics (Suah Jing Lian, BNM)

Uncertainty has risen sharply towards end of the decade due to a few major risk events and substantially since the COVID-19 pandemic. Literature suggests output responds adversely to uncertainty, with ambiguity on the macro-financial end.

The presenter discussed two questions as follows:

1. Empirical: What are the dynamics between uncertainty, the exchange rate and aggregate output?
2. Theoretical: What may be the frictions and channels underlying these effects?

Empirical literature finds that real economic activity slows in response to uncertainty shocks, followed by minor corrections as such:

1. Persistent output slowdown without correction, arising from macroeconomic uncertainty shocks;
2. Evidence of nonlinearity;
3. Three strands of theoretical underpinnings - (I) precautionary savings (II) real options effects (III) aggregate demand shocks. 

Macro-financial responses are more ambiguous and given less attention in quantitative and empirical applications. Aggregate in efficiencies stem from rational inattentiveness and bounded expectations, and interact with uncertainty based on five main ingredients.

1. Households and firms have (I) time-varying risk preferences, are (II) rationally inattentive, and have (III) bounded expectations;
2. Policymakers are (IV) cognitively limited and (V) loss averse.

Uncertainty erodes forecast precision, and gravitates expectations towards the innate biases of agents. Central banks can stabilise inflation and the output gap by addressing macro-behavioural frictions. 

Panel data covers 16 advanced and emerging economies, with some granularity on the East Asian region as well as Malaysia, comprising macro-economic data on variables as such:

1. Aggregate Output - Industrial Production Index;
2. Prices - Consumer Price Index;
3. Exchange Rate - Nominal Effective Exchange Rate;
4. Risk Aversion -10-Year Government Bond Yields;
5. Uncertainty - Economic Policy Uncertainty Index.

Meanwhile, Malaysia-specific study also covers: 

1. Labour Market – Employment; Uncertainty - Global EPU Index
2. Global Output-  Global GDP.

Five approaches were used to estimate the dynamics between uncertainty, the exchange rate and aggregate output:

1. Max-Uncertainty VAR (Jackson, Kliesen and Owyang (2020))
2. Panel VAR, with GMM-style instruments (Abrigo and Love (2016));
3. Bayesian Hierarchical PVAR (Jarocinski (2010));
4. LASSO fixed effects regression (Ahrens, Hansen and Schaffer (2019)); and
5. Panel quantile regression (Machado and Silva (2018)).

 In summary, two contributions were discussed that are:

• Conceptual framework to analytically view uncertainty shock

1. Macro-behavioural frictions, specifically rationally inattentive agents with bounded expectations, can produce prolonged output slowdown;
2. Scope for central banks to employ communications-based MP to stablise output and prices when uncertainty spikes.

• Empirical analysis on the impact of uncertainty and exchange rate shocks in a range of open economies:

1. Output moderates across all VAR/PVAR specifications in response to uncertainty and ER appreciation shocks
2. There may be heterogeneous responses to ER shocks at the sectoral-level
3.  Ambiguity in price and bond yield responses to uncertainty shocks, but moderate in response to ER appreciation shocks;
4. Possible nonlinear statistical relationship in the output-exchange rate-bond yields nexus;
5. Possible statistical distributional dimension along output growth but is imprecisely estimated.

Okay ada beberapa paper lagi tapi dah letih nak taip. Lain kali la sambung. Hahaha.

Last but not least. 

Selamat menyambut Hari Statistik Negara 2020. 

Statistik asas kelestarian kehidupan bermasyrakat dan negara.

Data anda masa depan kita. 

Pastikan anda dibanci.

Connecting the World With Data We Can Trust

Cause true colors are beautiful

Show me a smile then

Don't be unhappy, can't remember

When I last saw you laughing

If this world makes you crazy

And you've taken all you can bear

You call me up

Because you know I'll be there

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