Direct answer
A "deteksi tulisan AI" app is a tool that analyses a piece of writing and estimates how much of it was likely produced by a generative AI model such as ChatGPT, Claude, or Gemini. The most widely used detector in universities is Turnitin's AI writing detection, which is built into the similarity report instructors already open, and it returns a percentage of qualifying prose rather than a yes/no verdict [1]. Because that number is probabilistic, the useful question is not "which app says AI?" but "what does this score mean for my draft, and what should I do before I submit?"
How Do AI Writing Detector Apps Actually Work, And How Accurate Are They?
Detector apps do not work like plagiarism checkers. A similarity checker compares your text against an indexed database of documents; an AI detector instead measures statistical properties of the prose itself — chiefly how predictable each next word is, and how much sentence length and structure vary across a passage. Human academic writing tends to be less predictable and more uneven than model output, so the detector scores segments of your document on those patterns rather than matching stored text [2]. This is why a detector can flag writing that is entirely your own, and why it can miss lightly edited AI text: it is reading style, not provenance.
Accuracy is the part most students misunderstand. Turnitin segments a document and only evaluates passages that contain enough qualifying prose, and the published guidance is explicit that a flag is an indicator rather than proof of misconduct [2]. False positives cluster around predictable writing — heavily templated lab reports, formulaic literature reviews, and the work of writers using English as an additional language, whose phrasing can look statistically flat to a model trained on native-speaker corpora. Treat any single score, from any app, as one signal among several.
That has a practical consequence for how you use a detector app. If you run your draft and get a high percentage, the productive response is to inspect which passages were flagged and ask whether those passages genuinely reflect your own drafting process [2]. If the flagged text is a methods paragraph you wrote from a template, the fix is rewriting it in your own voice, not panicking. If it is a paragraph you pasted from a chatbot, the fix is different. The score tells you where to look; it does not tell you what happened.
What Does The Turnitin AI Score Percentage And The *% Marker Actually Mean?
The AI writing report gives you two views at once: an overall percentage for the document, and a segment-level breakdown that highlights the specific passages the detector attributed to AI [3]. The overall figure is the share of qualifying prose flagged — not the share of the whole file. References, bibliographies, quoted material, and short fragments typically sit outside that qualifying count, so a 100-page dissertation and a 1,500-word essay are not scored on the same basis [3]. Reading the segment view matters more than reading the headline number, because it shows you exactly where the detector's attention landed.
The *% display is the detail that causes the most confusion. When Turnitin's confidence in an AI signal falls below its internal threshold, the report shows an asterisk instead of an exact figure rather than showing zero [3]. Students often read *% as "no AI detected" and relax; in practice it means the signal was too weak or too short to express as a confident percentage. It is a low-confidence result, which is a different thing from a clean result, and it is worth knowing before you interpret a report as a pass.
Segment length also shapes what you see. Very short submissions, or documents where most of the text is headings, tables, and citations, may produce little or no qualifying prose for the detector to evaluate [3]. That is not evidence of innocence or guilt — it is a limitation of the instrument. If your assignment is a data-heavy appendix or a slide deck export, expect the AI report to say less than it would about a continuous essay, and plan your pre-submission check accordingly.
How Can A Student Check A Draft For AI Writing Before Submitting It?
The safest pre-submission habit is to check your own draft against the same kind of report your institution will see, rather than relying on a free web tool with unknown methodology. Turnitin's own student-facing guidance emphasises keeping your drafting trail — earlier versions, notes, and revision history — because authorship is ultimately demonstrated by process, not by a single number [4]. A pre-submission check is most useful when you pair it with that trail: you see the flagged passages, you know what you actually wrote, and you can decide what needs revising.
It also helps to know that the score is not the policy. Institutions set their own rules on acceptable AI use, and the same percentage can be a non-issue in one module and a formal integrity conversation in another [4]. Before you chase a number down to zero, confirm what your department actually permits — assisted editing, brainstorming, and code generation are treated very differently across programmes. Chasing an arbitrary target can push you into rewriting good sentences into worse ones for no policy reason.
Finally, be transparent rather than tactical. If your draft was polished with a model, say so where your institution asks you to declare it; the guidance for students is that honest disclosure and a visible drafting process resolve far more cases than a screenshot of a low score [4]. Use a detector app to find the passages that need your own voice, then actually put your own voice into them. That is the only intervention that improves both the score and the work.
If you would rather see the actual report before your deadline does, turnitin0 lets you run your draft through a real Turnitin AI detection and similarity check — non-repository, English documents between 300 and 30,000 words, with both PDFs delivered in one order, usually in under 15 minutes. You get the same cover, score, flagged passages, and similarity summary your instructor opens, so the segment view above is something you can read for yourself instead of guessing at.
※ Turnitin0.com - Actual Turnitin AI Report Cover, Score, Flag And Similarity Summary
FAQ
Is a Turnitin AI detector the same as a plagiarism checker?
No. A similarity checker compares your text against indexed sources, while AI detection analyses statistical patterns in your own prose to estimate whether a model generated it [1]. The two reports sit side by side in the same file, which is why students often conflate them.
Can a detector app prove I used AI?
Not on its own. Turnitin's own guidance frames the result as an indicator that should be read alongside drafting history and instructor judgement [2]. A high percentage is a prompt for a conversation, not a verdict.
Why does my report show *% instead of a number?
The asterisk appears when the AI signal falls below Turnitin's confidence threshold, so no exact percentage is displayed [3]. It signals a low-confidence result, not a confirmed zero.
How much text does a detector need before it reports anything?
Detection depends on qualifying prose, and references, citations, and very short fragments are generally excluded from that count [3]. Documents dominated by tables or headings may produce little evaluable text.
Should I rewrite everything until my score is zero?
Only if your institution's policy requires it. Check your department's rules on AI assistance first, since the score is not the policy [4], and prioritise rewriting passages that genuinely are not in your own voice.