Merge branch 'main' of https://github.com/mphstar/ksuli-sibi

feat: add model fix gerakan bukan abjad sibi
change(picture): change image
2025-03-21 01:54:33 +07:00 · 2025-03-21 01:54:17 +07:00 · 2025-03-19 21:34:16 +07:00 · 2025-03-17 09:40:41 +07:00 · 2025-03-16 17:13:05 +07:00 · 2025-03-12 00:11:43 +07:00
22 changed files with 287 additions and 90 deletions
--- a/index.html
+++ b/index.html
@ -1,9 +1,37 @@
-<!doctype html>
+<!DOCTYPE html>
 <html lang="en">
  <head>
    <meta charset="UTF-8" />
    <link rel="icon" type="image/svg+xml+png" href="/assets/images/logo.png" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <meta
+      name="description"
+      content="Ksuli SIBI adalah aplikasi yang membantu pengguna mengenal abjad dalam
+      Sistem Isyarat Bahasa Indonesia (SIBI). Aplikasi ini menyediakan panduan
+      visual dan interaktif untuk mempelajari huruf-huruf dalam SIBI, sehingga
+      memudahkan komunikasi bagi penyandang tuli dan orang-orang yang ingin
+      belajar bahasa isyarat."
+    />
+    <meta
+      name="keywords"
+      content="ksuli, kedai susu tuli, mphstar, 'ksuli sibi"
+    />
+    <meta name="robots" content="index, follow" />
+    <meta property="og:title" content="Ksuli SIBI" />
+    <meta
+      property="og:description"
+      content="Ksuli SIBI adalah aplikasi yang membantu pengguna mengenal abjad dalam
+      Sistem Isyarat Bahasa Indonesia (SIBI). Aplikasi ini menyediakan panduan
+      visual dan interaktif untuk mempelajari huruf-huruf dalam SIBI, sehingga
+      memudahkan komunikasi bagi penyandang tuli dan orang-orang yang ingin
+      belajar bahasa isyarat."
+    />
+
+    <meta
+      property="og:image"
+      content="https://ksuli-sibi.vercel.app/assets/images/logo.png"
+    />
+    <meta property="og:url" content="https://ksuli-sibi.vercel.app" />
    <title>Kedai Susu Tuli - SIBI</title>
  </head>
  <body>
--- a/public/assets/images/susun_1.svg
+++ b/public/assets/images/susun_1.svg
--- a/public/assets/images/susun_2.svg
+++ b/public/assets/images/susun_2.svg
--- a/public/assets/images/susun_3.svg
+++ b/public/assets/images/susun_3.svg
--- a/public/assets/images/susun_4.svg
+++ b/public/assets/images/susun_4.svg
--- a/public/assets/images/susun_5.svg
+++ b/public/assets/images/susun_5.svg
--- a/public/assets/images/susun_6.svg
+++ b/public/assets/images/susun_6.svg
--- a/public/model/group1-shard1of1.bin
+++ b/public/model/group1-shard1of1.bin
--- a/public/model/group1-shard1of3.bin
+++ b/public/model/group1-shard1of3.bin
--- a/public/model/group1-shard2of3.bin
+++ b/public/model/group1-shard2of3.bin
--- a/public/model/group1-shard3of3.bin
+++ b/public/model/group1-shard3of3.bin
--- a/public/model/model.json
+++ b/public/model/model.json
--- a/src/components/organisms/CarouselSusunHuruf.tsx
+++ b/src/components/organisms/CarouselSusunHuruf.tsx
@ -12,21 +12,21 @@ const slides = [
  {
    title: "Gerakan",
    description:
-      "Gerakkan tangan Anda di depan kamera untuk melanjutkan. Sistem akan mendeteksi gerakan Anda untuk navigasi tanpa sentuhan.",
-    image: "/assets/images/susun_2.svg",
+      "Gerakkan tangan Anda di depan kamera. Sistem akan mendeteksi gerakan Anda.",
+    image: "/assets/images/susun_5.svg",
    button: "Next",
  },
  {
    title: "Susun abjad",
    description:
-      "Susun huruf-huruf menjadi kata yang benar. Ini adalah latihan untuk meningkatkan keterampilan kognitif dan kecepatan berpikir Anda.",
-    image: "/assets/images/susun_3.svg",
+      "Susun huruf-huruf menjadi kata pada soal.",
+    image: "/assets/images/susun_6.svg",
    button: "Next",
  },
  {
    title: "Score",
    description:
-      "Selesaikan tugas dengan cepat untuk mendapatkan skor tertinggi. Skor Anda akan dibandingkan dengan pengguna lain di papan peringkat.",
+      "Selesaikan soal dengan cepat untuk mendapatkan skor tertinggi. Skor Anda akan dibandingkan dengan pengguna lain di papan peringkat.",
    image: "/assets/images/susun_4.svg",
    button: "Get Started",
  },
@ -63,7 +63,7 @@ export default function Carousel() {
                  className="h-60"
                />
                {/* <h2 className="mt-4 text-xl font-bold">{slide.title}</h2> */}
-                <p className="mt-8 text-gray-500 text-sm">
+                <p className="mt-8 text-gray-800 text-sm">
                  {slide.description}
                </p>
                {/* <button
--- a/src/components/organisms/CarouselTebakHuruf.tsx
+++ b/src/components/organisms/CarouselTebakHuruf.tsx
@ -12,7 +12,7 @@ const slides = [
  {
    title: "Tebak Huruf",
    description:
-      "Tebak huruf sesuai soal yang ditampilkan. Ini adalah latihan untuk meningkatkan keterampilan kognitif dan kecepatan berpikir Anda.",
+      "Tebak huruf sesuai soal yang ditampilkan.",
    image: "/assets/images/susun_2.svg",
    button: "Next",
  },
@ -59,7 +59,7 @@ export default function Carousel() {
              >
                <img src={slide.image} alt={slide.title} className="h-60" />
                {/* <h2 className="mt-4 text-xl font-bold">{slide.title}</h2> */}
-                <p className="mt-8 text-gray-500 text-sm">
+                <p className="mt-8 text-gray-800 text-sm">
                  {slide.description}
                </p>
                {/* <button
--- a/src/pages/Home.tsx
+++ b/src/pages/Home.tsx
@ -2,12 +2,14 @@ import LayoutPage from "@/components/templates/LayoutPage";
 import { useEffect, useRef, useState } from "react";
 import { FaCircleCheck } from "react-icons/fa6";
 import * as tf from "@tensorflow/tfjs";
-import { FilesetResolver, HandLandmarker } from "@mediapipe/tasks-vision";
+import { HandLandmarker } from "@mediapipe/tasks-vision";
 import calcLandmarkList from "@/utils/CalculateLandmark";
 import preProcessLandmark from "@/utils/PreProcessLandmark";
 import ConvertResult from "@/utils/ConvertResult";
 import useNavbarStore from "@/stores/NavbarStore";
 import { AnimatePresence, motion } from "framer-motion";
+import { loadTensorFlowModel } from "@/utils/tensorflowModelLoader";
+import { loadHandLandmarker } from "@/utils/handLandmarkerLoader";

 type PredictResult = {
  abjad: String;
@ -33,6 +35,7 @@ const Home = () => {
    try {
      const stream = await navigator.mediaDevices.getUserMedia({
        video: true,
+        
      });

      if (videoRef.current) {
@ -49,12 +52,13 @@ const Home = () => {
  const loadModel = async () => {
    setLoadCamera(false);
    try {
-      const lm = await tf.loadLayersModel("/model/model.json");
+      const lm = await loadTensorFlowModel();
      model = lm;

-      const emptyInput = tf.tensor2d([[0, 0]]);
+      // const emptyInput = tf.tensor2d([[0, 0]]);

-      model.predict(emptyInput) as tf.Tensor;
+      // model.predict(emptyInput) as tf.Tensor;
+      

      setLoadCamera(true);
    } catch (error) {
@ -64,17 +68,8 @@ const Home = () => {

  const initializeHandDetection = async () => {
    try {
-      const vision = await FilesetResolver.forVisionTasks(
-        "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@latest/wasm"
-      );
-      handLandmarker = await HandLandmarker.createFromOptions(vision, {
-        baseOptions: {
-          modelAssetPath: `https://storage.googleapis.com/mediapipe-models/hand_landmarker/hand_landmarker/float16/1/hand_landmarker.task`,
-        },
-        numHands: 2,
-        runningMode: "VIDEO",
-      });
-
+      handLandmarker = await loadHandLandmarker();
+      
      detectHands();
    } catch (error) {
      console.error("Error initializing hand detection:", error);
@ -116,11 +111,13 @@ const Home = () => {
        performance.now()
      );

+      
+
      setHandPresence(detections.handedness.length > 0);
      // Assuming detections.landmarks is an array of landmark objects
      if (detections.landmarks) {
        if (detections.handednesses.length > 0) {
-          console.log(detections);
+          // console.log(detections);

          if (detections.handednesses[0][0].displayName === "Right") {
            const landm = detections.landmarks[0].map((landmark) => landmark);
@ -183,10 +180,7 @@ const Home = () => {
                  d="M13 16h-1v-4h-1m1-4h.01M21 12a9 9 0 11-18 0 9 9 0 0118 0z"
                ></path>
              </svg>
-              <p className="ml-2">
-                Gunakan tangan kanan dan pastikan gambar pada kamera terlihat
-                jelas
-              </p>
+              <p className="ml-2">Gunakan tangan kanan. Pencahayaan ideal 120 Lux, jarak maksimal 2 meter dari kamera.</p>
            </div>
            <button
              onClick={() => setInfo(false)}
--- a/src/pages/Kamus.tsx
+++ b/src/pages/Kamus.tsx
@ -80,7 +80,13 @@ const Kamus = () => {
              <div className="flex flex-col md:flex-row gap-6 overflow-y-auto flex-1">
                <div className="flex flex-col order-2 md:order-1">
                  <p>{selectedKamus?.keterangan}</p>
-                  <div className="flex flex-wrap gap-2 mt-3">
+
+                  <a href="/">
+                    <button className="btn mt-8 bg-slate-900 text-white hover:bg-slate-950 w-fit">
+                      Coba Sekarang
+                    </button>
+                  </a>
+                  {/* <div className="flex flex-wrap gap-2 mt-3">
                    {selectedKamus?.badge.map((item, index) => (
                      <span
                        key={index}
@ -89,7 +95,7 @@ const Kamus = () => {
                        {item}
                      </span>
                    ))}
-                  </div>
+                  </div> */}
                </div>
                <img
                  className="h-[250px] object-cover rounded-md order-1 md:order-2"
--- a/src/pages/Kuis/MenyusunHuruf/Quiz.tsx
+++ b/src/pages/Kuis/MenyusunHuruf/Quiz.tsx
@ -1,7 +1,7 @@
 import LayoutPage from "@/components/templates/LayoutPage";
 import { useEffect, useRef, useState } from "react";
 import * as tf from "@tensorflow/tfjs";
-import { FilesetResolver, HandLandmarker } from "@mediapipe/tasks-vision";
+import { HandLandmarker } from "@mediapipe/tasks-vision";
 import calcLandmarkList from "@/utils/CalculateLandmark";
 import preProcessLandmark from "@/utils/PreProcessLandmark";
 import { abjads } from "@/utils/ConvertResult";
@ -10,6 +10,8 @@ import { MdOutlineQuiz } from "react-icons/md";
 import useMenyusunHurufStore from "@/stores/MenyusunHurufStore";
 import { useNavigate } from "react-router-dom";
 import Swal from "sweetalert2";
+import { loadTensorFlowModel } from "@/utils/tensorflowModelLoader";
+import { loadHandLandmarker } from "@/utils/handLandmarkerLoader";

 // type PredictResult = {
 //   abjad: String;
@ -61,7 +63,7 @@ const Quiz = () => {
  const loadModel = async () => {
    setLoadCamera(false);
    try {
-      const lm = await tf.loadLayersModel("/model/model.json");
+      const lm = await loadTensorFlowModel();
      model = lm;

      const emptyInput = tf.tensor2d([[0, 0]]);
@ -76,16 +78,7 @@ const Quiz = () => {

  const initializeHandDetection = async () => {
    try {
-      const vision = await FilesetResolver.forVisionTasks(
-        "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@latest/wasm"
-      );
-      handLandmarker = await HandLandmarker.createFromOptions(vision, {
-        baseOptions: {
-          modelAssetPath: `https://storage.googleapis.com/mediapipe-models/hand_landmarker/hand_landmarker/float16/1/hand_landmarker.task`,
-        },
-        numHands: 2,
-        runningMode: "VIDEO",
-      });
+      handLandmarker = await loadHandLandmarker();

      detectHands();
    } catch (error) {
@ -180,6 +173,8 @@ const Quiz = () => {
        answerTime = answerTime += elapsedTime;

        noSoal++;
+        tempAnswer = "";
+        setAnswer("");

        if (noSoal === quizStore.listSoal.length) {
          quizStore.setTime(answerTime);
--- a/src/pages/Kuis/TebakHuruf/Quiz.tsx
+++ b/src/pages/Kuis/TebakHuruf/Quiz.tsx
@ -1,7 +1,7 @@
 import LayoutPage from "@/components/templates/LayoutPage";
 import { useEffect, useRef, useState } from "react";
 import * as tf from "@tensorflow/tfjs";
-import { FilesetResolver, HandLandmarker } from "@mediapipe/tasks-vision";
+import { HandLandmarker } from "@mediapipe/tasks-vision";
 import calcLandmarkList from "@/utils/CalculateLandmark";
 import preProcessLandmark from "@/utils/PreProcessLandmark";
 import ConvertResult, { abjads } from "@/utils/ConvertResult";
@ -11,12 +11,23 @@ import { MdOutlineQuiz } from "react-icons/md";
 import useTebakHurufStore from "@/stores/TebakHurufStore";
 import { useNavigate } from "react-router-dom";
 import Swal from "sweetalert2";
+import { loadTensorFlowModel } from "@/utils/tensorflowModelLoader";
+import { loadHandLandmarker } from "@/utils/handLandmarkerLoader";

 // type PredictResult = {
 //   abjad: String;
 //   acc: String;
 // };

+const imagesToPreload = ["/assets/gif/betul.gif", "/assets/gif/salah.gif"];
+
+const preloadImages = () => {
+  imagesToPreload.forEach((src) => {
+    const img = new Image();
+    img.src = src;
+  });
+};
+
 const Quiz = () => {
  const videoRef = useRef<HTMLVideoElement>(null);
  const [loadCamera, setLoadCamera] = useState(false);
@ -54,7 +65,7 @@ const Quiz = () => {
  const loadModel = async () => {
    setLoadCamera(false);
    try {
-      const lm = await tf.loadLayersModel("/model/model.json");
+      const lm = await loadTensorFlowModel();
      model = lm;

      const emptyInput = tf.tensor2d([[0, 0]]);
@ -69,16 +80,7 @@ const Quiz = () => {

  const initializeHandDetection = async () => {
    try {
-      const vision = await FilesetResolver.forVisionTasks(
-        "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@latest/wasm"
-      );
-      handLandmarker = await HandLandmarker.createFromOptions(vision, {
-        baseOptions: {
-          modelAssetPath: `https://storage.googleapis.com/mediapipe-models/hand_landmarker/hand_landmarker/float16/1/hand_landmarker.task`,
-        },
-        numHands: 2,
-        runningMode: "VIDEO",
-      });
+      handLandmarker = await loadHandLandmarker();

      detectHands();
    } catch (error) {
@ -150,28 +152,31 @@ const Quiz = () => {
      setShowAnswer(true);

      setTimeout(() => {
-        isLoading = false;
        setShowAnswer(false);
-        setProgress(0);
-        noSoal++;
-        previousResult = [];
-        quizStore.setSoalIndex(noSoal);

-        if (noSoal === quizStore.listSoal.length) {
-          quizStore.setSession(false);
-          quizStore.setIsFinish(true);
+        setTimeout(() => {
+          isLoading = false;
+          setProgress(0);
+          noSoal++;
+          previousResult = [];
+          quizStore.setSoalIndex(noSoal);

-          Swal.fire({
-            title: "Loading",
-            text: "Proses menyimpan data...",
-            allowOutsideClick: false,
-            didOpen: () => {
-              Swal.showLoading();
-            },
-          });
+          if (noSoal === quizStore.listSoal.length) {
+            quizStore.setSession(false);
+            quizStore.setIsFinish(true);

-          navigate("/kuis/tebak-huruf");
-        }
+            Swal.fire({
+              title: "Loading",
+              text: "Proses menyimpan data...",
+              allowOutsideClick: false,
+              didOpen: () => {
+                Swal.showLoading();
+              },
+            });
+
+            navigate("/kuis/tebak-huruf");
+          }
+        }, 300);
      }, 2000);
    }

@ -221,7 +226,7 @@ const Quiz = () => {
  const store = useNavbarStore();
  const quizStore = useTebakHurufStore();

-  console.log(quizStore.jawaban);
+  // console.log(quizStore.jawaban);

  useEffect(() => {
    if (!quizStore.session) {
@ -231,6 +236,7 @@ const Quiz = () => {

  useEffect(() => {
    store.setNavSelected("kuis");
+    preloadImages();

    loadModel();
    startWebcam();
@ -249,22 +255,30 @@ const Quiz = () => {
      <div
        className={`fixed inset-0 w-screen h-screen bg-black/60 ${
          showAnswer ? "opacity-100" : "opacity-0"
-        }  z-[999] flex items-center justify-center pointer-events-none duration-300 ease-in-out`}
+        }  z-[999] flex items-center justify-center pointer-events-none  ease-in-out`}
      >
        <div className="rounded-md px-3 py-2 text-white flex flex-col justify-center items-center gap-3">
+        
          <img
-            className="h-56"
-            src={`/assets/gif/${
-              quizStore.jawaban[quizStore.soalIndex]?.isCorrect
-                ? "betul"
-                : "salah"
-            }.gif`}
-            alt={`Jawaban ${
-              quizStore.jawaban[quizStore.soalIndex]?.isCorrect
-                ? "Benar"
-                : "Salah"
+            className={`h-56 ${
+              quizStore.jawaban[quizStore.soalIndex]?.isCorrect ? "" : "hidden"
            }`}
+            src={`/assets/gif/betul.gif`}
+            loading="eager"
+            fetchPriority="high"
+            alt={`Jawaban Benar`}
          />
+
+          <img
+            className={`h-56 ${
+              quizStore.jawaban[quizStore.soalIndex]?.isCorrect ? "hidden" : ""
+            }`}
+            src={`/assets/gif/salah.gif`}
+            loading="eager"
+            fetchPriority="high"
+            alt={`Jawaban Salah`}
+          />
+
          <p className="text-center text-6xl font-bold">
            {quizStore.jawaban[quizStore.soalIndex]?.jawaban}
          </p>
--- a/src/utils/ConvertResult.ts
+++ b/src/utils/ConvertResult.ts
@ -23,9 +23,14 @@ export const abjads = [
  "W",
  "X",
  "Y",
+  "Tidak Dikenali",
 ];

 const ConvertResult = (result: number) => {
+  if (result < 0 || result > 23) {
+    return "Tidak Dikenali";
+  }
+
  return `Abjad ${abjads[result]}`;
 };

--- a/src/utils/handLandmarkerLoader.ts
+++ b/src/utils/handLandmarkerLoader.ts
@ -0,0 +1,34 @@
+import { FilesetResolver, HandLandmarker } from "@mediapipe/tasks-vision";
+import { getHandLandmarkerModel, saveHandLandmarkerModel } from "./indexedDBHelper";
+
+let handLandmarker: HandLandmarker | null = null;
+
+export async function loadHandLandmarker(): Promise<HandLandmarker> {
+  if (handLandmarker) return handLandmarker; // Jika model sudah ada, langsung kembalikan
+
+  let modelBlob = await getHandLandmarkerModel();
+
+  if (!modelBlob) {
+    console.log("🔄 Model Hand Landmarker tidak ditemukan di cache, mengunduh...");
+    const response = await fetch(
+      "https://storage.googleapis.com/mediapipe-models/hand_landmarker/hand_landmarker/float16/1/hand_landmarker.task"
+    );
+    modelBlob = await response.blob();
+    await saveHandLandmarkerModel(modelBlob);
+  } else {
+    console.log("✅ Model Hand Landmarker ditemukan di cache, menggunakan model lokal.");
+  }
+
+  const vision = await FilesetResolver.forVisionTasks(
+    "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@latest/wasm"
+  );
+
+  const modelURL = URL.createObjectURL(modelBlob);
+  handLandmarker = await HandLandmarker.createFromOptions(vision, {
+    baseOptions: { modelAssetPath: modelURL },
+    numHands: 2,
+    runningMode: "VIDEO",
+  });
+
+  return handLandmarker;
+}
--- a/src/utils/indexedDBHelper.ts
+++ b/src/utils/indexedDBHelper.ts
@ -0,0 +1,59 @@
+import * as tf from "@tensorflow/tfjs";
+
+const DB_NAME = "ModelCacheDB";
+const STORE_NAME = "models";
+const TENSORFLOW_MODEL_KEY = "tensorflow_model";
+const HAND_LANDMARKER_MODEL_KEY = "hand_landmarker_model";
+
+// Membuka IndexedDB
+export function openDB(): Promise<IDBDatabase> {
+  return new Promise((resolve, reject) => {
+    const request = indexedDB.open(DB_NAME, 1);
+
+    request.onupgradeneeded = (event: IDBVersionChangeEvent) => {
+      const db = (event.target as IDBOpenDBRequest).result;
+      if (!db.objectStoreNames.contains(STORE_NAME)) {
+        db.createObjectStore(STORE_NAME);
+      }
+    };
+
+    request.onsuccess = () => resolve(request.result);
+    request.onerror = () => reject(request.error);
+  });
+}
+
+// 🟢 **Simpan Model TensorFlow.js ke IndexedDB**
+export async function saveTensorFlowModel(model: tf.LayersModel): Promise<void> {
+  await model.save(`indexeddb://${TENSORFLOW_MODEL_KEY}`);
+}
+
+// 🟢 **Ambil Model TensorFlow.js dari IndexedDB**
+export async function getTensorFlowModel(): Promise<tf.LayersModel | null> {
+  try {
+    return await tf.loadLayersModel(`indexeddb://${TENSORFLOW_MODEL_KEY}`);
+  } catch (error) {
+    console.warn("⚠️ Model TensorFlow tidak ditemukan di cache:", error);
+    return null;
+  }
+}
+
+// 🟢 **Simpan Model Hand Landmarker ke IndexedDB**
+export async function saveHandLandmarkerModel(blob: Blob): Promise<void> {
+  const db = await openDB();
+  const transaction = db.transaction(STORE_NAME, "readwrite");
+  const store = transaction.objectStore(STORE_NAME);
+  store.put(blob, HAND_LANDMARKER_MODEL_KEY);
+}
+
+// 🟢 **Ambil Model Hand Landmarker dari IndexedDB**
+export async function getHandLandmarkerModel(): Promise<Blob | null> {
+  const db = await openDB();
+  return new Promise((resolve, reject) => {
+    const transaction = db.transaction(STORE_NAME, "readonly");
+    const store = transaction.objectStore(STORE_NAME);
+    const request = store.get(HAND_LANDMARKER_MODEL_KEY);
+
+    request.onsuccess = () => resolve(request.result as Blob | null);
+    request.onerror = () => reject(request.error);
+  });
+}
--- a/src/utils/tensorflowModelLoader.ts
+++ b/src/utils/tensorflowModelLoader.ts
@ -0,0 +1,20 @@
+import * as tf from "@tensorflow/tfjs";
+import { getTensorFlowModel, saveTensorFlowModel } from "./indexedDBHelper";
+
+let model: tf.LayersModel | null = null;
+
+export async function loadTensorFlowModel(): Promise<tf.LayersModel> {
+  if (model) return model; // Jika model sudah dimuat, langsung kembalikan
+
+  model = await getTensorFlowModel();
+
+  if (!model) {
+    console.log("🔄 Model TensorFlow tidak ditemukan di cache, mengunduh...");
+    model = await tf.loadLayersModel("/model/model.json");
+    await saveTensorFlowModel(model);
+  } else {
+    console.log("✅ Model TensorFlow ditemukan di cache, menggunakan model lokal.");
+  }
+
+  return model;
+}
Author	SHA1	Message	Date
mphstar	28a1a6be20	Merge branch 'main' of https://github.com/mphstar/ksuli-sibi	2025-03-21 01:54:33 +07:00
mphstar	1785fa98e1	feat: add model fix gerakan bukan abjad sibi	2025-03-21 01:54:17 +07:00
mphstar	7bdcea3915	change(picture): change image	2025-03-19 21:34:16 +07:00
mphstar	178fb250d4	update information recommendation lux	2025-03-17 09:40:41 +07:00
mphstar	472d78ff6a	fix delay answer picture	2025-03-16 17:13:05 +07:00
mphstar	2c9703f581	fix: finish quiz tebak huruf	2025-03-12 00:11:43 +07:00
mphstar	c7f37f589e	add caching model	2025-03-12 00:04:45 +07:00
mphstar	957a63ca7c	fix quiz	2025-03-05 20:53:17 +07:00
mphstar	6aa0ba590b	feat meta tag for seo	2025-03-03 11:44:54 +07:00
mphstar	57be0a1691	remove badge detail kamus	2025-03-03 11:39:41 +07:00