Religion — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear word for word on 2 other registered channels. They sit inside a group of 4 channels that share the same post bodies with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 7 of the 10 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 35 comparable posts for this entry, running 3 August 2026 to 8 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 4, the earliest publisher we hold is @galeriSC. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_copy · clone_source, last confirmed 8 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 3 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
36 measurements spanning 50 days, net -301. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 27,934–28,325 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 36
Measured (UTC)
Subscribers
Change
25 Sept 2026, 04:19
27,979
-36
18 Sept 2026, 23:40
28,015
-11
16 Sept 2026, 16:20
28,026
-2
14 Sept 2026, 17:36
28,028
-8
13 Sept 2026, 01:21
28,036
-10
11 Sept 2026, 05:19
28,046
-18
8 Sept 2026, 06:39
28,064
-13
4 Sept 2026, 22:22
28,077
-3
3 Sept 2026, 09:22
28,080
-8
2 Sept 2026, 03:17
28,088
-7
1 Sept 2026, 06:13
28,095
-7
31 Aug 2026, 05:25
28,102
-15
30 Aug 2026, 07:16
28,117
-2
29 Aug 2026, 04:58
28,119
+1
28 Aug 2026, 02:24
28,118
+1
27 Aug 2026, 04:38
28,117
-2
26 Aug 2026, 05:04
28,119
-14
25 Aug 2026, 03:36
28,133
-15
23 Aug 2026, 22:54
28,148
-12
22 Aug 2026, 07:38
28,160
first reading
Engagement
289 posts held, back to 3 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 66 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
4.01%
avg views ÷ 27,979 subscribers
Avg views / post
1,120
117 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
117
of 289 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 24 September 2026
Posts held
289 (3 August 2026 – 24 September 2026)
Views total
131,347
Reactions total
—
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
24 Sept 2026, 17:50 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Video runtime
5m 15s
Average length
1m 45s
Measured directly from 3 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
🌕🔛🌙 FAEDAH MALAM
✓ Petikan Akhlak Salaf
••••••••••••••••••••••••••••••••••••••
☝🏻 MENGAJARKAN TAUHID KETIKA MASIH KECIL
📜 Ali bin Al Husain (Zainul Abidin) mengajarkan anaknya. beliau berkata : Katakanlah :
"Aku beriman kepada Allah dan aku kufur terhadap Thogut (yang disembah selain Allah)."
📚 [Mushannaf Ibnu Abi Syaibah Fil Mushannaf : 3518]
➖➖➖➖➖➖➖➖➖➖➖
📜 كَانَ عَلِيُّ بْنُ الْحُسَيْنِ ( #زين_العابدين )
…
🌟 Mutiara Ayat Suci Alquran
💎💎 BERTAKWA DAN BERBUATBAIKLAH!
📌 Allah subhanallahu wa ta'ala berfirman:
إِنَّ ٱللَّهَ مَعَ ٱلَّذِينَ ٱتَّقَوا۟ وَّٱلَّذِينَ هُم مُّحْسِنُونَ
✅ Sesungguhnya Allah beserta orang-orang yang bertakwa dan orang-orang yang berbuat kebaikan.
📚 An-Nahl:128
#Mutiara_Quran
https://twitter.com/Arafatbinhassan/status/1361896855047729152
━━━━━━━━━━━━━
📡 SALAFY CIREBON
━━━━━━━━━━━━━
📲 WA Offi…
📚 KAJIAN UMUM - KITAB NAHWU
Kajian Kitab Al Mumti' Fii Syarh Al Ajurrumiyyah bersama Al-Ustadz Ahmad Syahroni حفظه الله
📻 Simak via aplikasi Radio Indah Siar: https://bit.ly/indahsiar
▶️ SIARAN LANGSUNG MA'HAD DHIYA'US SUNNAH CIREBON
🔊 Update audio kajian dan video dakwah bisa bergabung ke channel telegram kami: https://t.me/radioindahsiar
📡 www.radioindahsiar.com
📚 KAJIAN UMUM - INDAHNYA BELAJAR BAHASA ARAB
Kajian Kitab Durusul Lughoh Jilid 3 bersama Al-Ustadz Ahmad Syahroni حفظه الله
📻 Simak via aplikasi Radio Indah Siar: https://bit.ly/indahsiar
▶️ SIARAN LANGSUNG MA'HAD DHIYA'US SUNNAH CIREBON
🔊 Update audio kajian dan video dakwah bisa bergabung ke channel telegram kami: https://t.me/radioindahsiar
📡 www.radioindahsiar.com
📚 *KAJIAN TELECONFERENCE TIMIKA - KITAB NAHWU*
_Kajian Kitab Al-Kawakibud Durriyyah fi Syarhi Nazhmil Aajurrumiyah bersama Al-Ustadz Hamzah Al Fathin حفظه الله_
📻 *Simak via aplikasi Radio Indah Siar:* https://bit.ly/indahsiar
▶️ *SIARAN LANGSUNG DARI STUDIO INDAH SIAR 2, CIREBON*
🔊 Update audio kajian dan video dakwah bisa bergabung ke channel telegram kami: https://t.me/radioindahsiar
📡 www.radioindahsiar.com
🔰𝗠𝗘𝗡𝗚𝗚𝗔𝗕𝗨𝗡𝗚𝗞𝗔𝗡 𝗗𝗨𝗔 𝗢𝗥𝗔𝗡𝗚 𝗗𝗔𝗟𝗔𝗠 𝗦𝗔𝗧𝗨 𝗞𝗨𝗕𝗨𝗥
-----------------
Dari Jabir ibn Abdillah, dia berkata :
"Nabi menggabungkan dua orang laki-laki yang gugur dalam perang Uhud dalam satu kain, lalu bersabda :
"Siapakah diantara mereka yang lebih banyak mempunyai hafalan al-Qur'an?"
Bila beliau telah ditunjukkan salah satu diantara keduanya, maka beliau mendahulukannya di dalam lahad lalu bersabda :
"Aku akan menjadi sa…
🌕🌙🔛 FAEDAH MALAM
✓ Petikan Kalam Salafus Shalih
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
❓ APA ITU MUSIBAH DAN KESEHATAN YANG HAKIKI?
📜Al Imam Ibnul Qayyim رحمَـہ الله تَعـَالَـى berkata :
"Pada hakikatnya musibah itu ada pada dosa-dosa dan akibat-akibatnya. Sedangkan Kesehatan yang sebenarnya itu ada pada ketaatan-ketaatan dan akibat-akibatnya. Maka yang terkena musibah sesungguhnya itu adalah mereka yang melaku…
• SIMAK SEKARANG!
"KAJIAN ISLAM ILMIAH"
(Bersama Menjaga Prinsip agama)
Bersama:
Al-Ustadz Muhammad bin Umar As Sewed حفظه الله
Akses melalui aplikasi:
➠ Radio Indah Siar Cirebon 91.8 FM
Aplikasi Radio Indah Siar:
➠ http://bit.ly/indahsiar
Radio Islam Indonesia (RII)
http://bit.ly/AplikasiRadioIslamIndonesia2
Akses melalui telegram:
➠ http://t.me/radioindahsiar
📚 KAJIAN STUDIO - INDAHNYA IBADAH DENGAN SUNNAH
Kajian Kitab Mulakhosh Al Fiqh bersama Al-Ustadz Helmi Bajri حفظه الله
📻 Simak via aplikasi Radio Indah Siar: https://bit.ly/indahsiar
▶️ SIARAN LANGSUNG DARI STUDIO INDAH SIAR, CIREBON
🔊 Update audio kajian dan video dakwah bisa bergabung ke channel telegram kami: https://t.me/radioindahsiar
📡 www.radioindahsiar.com
Showing the 12 most recent of 289 posts we hold for @salafy_cirebon. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Posts edited after publishing
@salafy_cirebon edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
24 September 2026
Most recent edit
24 September 2026
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 26 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 10 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
🌹SyarhusSunnahLinNisaa`🌹 @syarhussunnahlinnisa · 24,020 Telegram ranks this channel #1 of 85 here — alongside 84 others — read 17 September 2026
Nisaa` As-Sunnah @NisaaAssunnah · 22,860 Telegram ranks this channel #2 of 98 here — alongside 97 others — read 19 September 2026
Salafy Indonesia @forumsalafy · 57,167 Telegram ranks this channel #2 of 96 here — alongside 95 others — read 29 August 2026
SyababSalafy️ @syababsalafy · 22,909 Telegram ranks this channel #8 of 96 here — alongside 95 others — read 19 September 2026
Manhaj Salaf @Manhaj_salaf1 · 34,269 Telegram ranks this channel #38 of 89 here — alongside 88 others — read 3 September 2026
This channel appears in 5 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 25 September 2026 — this
entry's latest reading, not the date you are reading this.
“SALAFY CIREBON 🇮🇩” (@salafy_cirebon), 27,979 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/salafy_cirebon.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.