{"id":12710,"date":"2021-07-09T19:04:53","date_gmt":"2021-07-09T10:04:53","guid":{"rendered":"https:\/\/adc-japan.com\/uk\/?p=12710"},"modified":"2026-10-18T08:00:09","modified_gmt":"2026-10-17T23:00:09","slug":"tes-uchida-kraepelin-dan-transformasi-digital-dx","status":"publish","type":"post","link":"https:\/\/adc-japan.com\/uk\/id\/tips-id\/12710.html","title":{"rendered":"Tes Uchida-Kraepelin dan Transformasi Digital (DX)"},"content":{"rendered":"<aside class=\"uk-ai-translation-notice\" lang=\"id\" style=\"box-sizing:border-box;clear:both;margin:0 0 1.5em;padding:1em;border:1px solid #ccd5de;border-left:4px solid #486581;background:#f4f7fa;color:#243746;font-size:14px;line-height:1.8;overflow-wrap:anywhere;\">\n<p style=\"margin:0;\">Halaman ini diterjemahkan secara otomatis dari teks asli bahasa Jepang menggunakan AI generatif. Terjemahan dapat mengandung kesalahan. Silakan hubungi kami untuk mengonfirmasi informasi penting.<\/p>\n<\/aside>\n<h3>Menggunakan DX untuk mengolah karakteristik manusia<\/h3>\n<p>Tes Uchida-Kraepelin sangat sesuai untuk mengolah karakteristik kemampuan dan kepribadian\/perilaku manusia dalam transformasi digital (DX).<\/p>\n<h3>Apa itu DX?<\/h3>\n<p>Transformasi digital merujuk pada gagasan bahwa <strong><span style=\"color: #ff6600;\">meluasnya teknologi informasi mengubah kehidupan manusia ke arah yang lebih baik dalam segala aspek<\/span><\/strong>. Konsep ini umumnya dikaitkan dengan Profesor Erik Stolterman dari Universitas Ume\u00e5, Swedia, pada 2004, dan biasa disingkat DX.<\/p>\n<p>Kementerian Ekonomi, Perdagangan dan Industri Jepang menjelaskan DX dalam Pedoman Promosi DX sebagai berikut (parafrasa):<\/p>\n<p><span style=\"color: #ff6600;\"><strong>Perusahaan merespons perubahan lingkungan bisnis yang cepat dengan memakai data dan teknologi digital untuk mentransformasi produk, layanan dan model bisnis sesuai kebutuhan pelanggan serta masyarakat, sekaligus mengubah pekerjaan, organisasi, proses dan budaya perusahaan demi membangun keunggulan kompetitif.<\/strong><\/span><\/p>\n<h3>Tes Uchida-Kraepelin dan DX<\/h3>\n<p>Karena dikerjakan dengan kertas dan pensil, Tes Uchida-Kraepelin mungkin tampak tidak berhubungan dengan teknologi digital.<br \/>\nNamun, metode unik yang hanya berisi tugas penjumlahan serta mengolah data volume kerja dan jumlah kesalahan tiap menit ini pada dasarnya bersifat digital.<br \/>\nGrafik dan teks dalam laporan penilaian hanyalah visualisasi data digital agar mudah dibaca manusia.<\/p>\n<figure class=\"uk-dx-image\" style=\"margin:0 0 24px;\"><a href=\"https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-id.png\"><img decoding=\"async\" width=\"1680\" height=\"830\" class=\"wp-image-12037 alignnone\" src=\"https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-id.png\" alt=\"Tes Uchida-Kraepelin: mendigitalkan karakteristik kemampuan dan perilaku; Big data\" style=\"max-width:100%;height:auto;width:600px;\" srcset=\"https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-id.png 1680w, https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-id-300x148.png 300w, https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-id-1024x506.png 1024w, https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-id-768x379.png 768w, https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-id-1536x759.png 1536w\" sizes=\"(max-width: 1680px) 100vw, 1680px\" \/><\/a><figcaption>\n<details>\n<summary>Tes Uchida-Kraepelin: mendigitalkan karakteristik kemampuan dan perilaku<\/summary>\n<div class=\"uk-dx-diagram\" style=\"max-width:600px;border:1px solid #ccc;padding:16px;box-sizing:border-box;line-height:1.7;overflow-wrap:anywhere;\">\n<p style=\"background:#20478f;color:#fff;padding:12px;text-align:center;\"><strong>Tes Uchida-Kraepelin: mendigitalkan karakteristik kemampuan dan perilaku<\/strong><br \/>\u2193<br \/>Data mentah hasil tes<\/p>\n<p style=\"background:#e7f0f5;padding:12px;text-align:center;\"><strong>Big data<\/strong><br \/>&#x2194; Bandingkan dengan data klinis<br \/>\u2193 Kembangkan dan perbarui model penilaian<br \/>Hasil penilaian dari berbagai model<\/p>\n<ul style=\"margin-bottom:0;\">\n<li>Kesesuaian pekerjaan: penilaian rekrutmen, penempatan dan mutasi<\/li>\n<li>Manajemen keselamatan: pencegahan kecelakaan dan sistem perizinan mengemudi<\/li>\n<li>Pendidikan dan pelatihan: perencanaan pendidikan, konsultasi studi lanjut, pendidikan masyarakat dan dukungan karier<\/li>\n<li>Kesehatan mental: dukungan psikologis, penilaian kesehatan dan dukungan kembali bekerja<\/li>\n<\/ul>\n<\/div>\n<\/details>\n<\/figcaption><\/figure>\n<p>Tes ini terutama menghasilkan dua jenis data:<\/p>\n<ol>\n<li>Data mentah tes, seperti volume kerja dan jumlah kesalahan tiap menit serta usia<\/li>\n<li>Data hasil penilaian yang diperoleh dengan memasukkan data mentah ke model penilaian<\/li>\n<\/ol>\n<p>Model penilaian adalah fungsi yang diperoleh dari perbandingan data mentah dengan data klinis, misalnya perilaku kerja sehari-hari, gaya belajar, kecocokan dengan tugas tertentu, kecelakaan dan kesehatan. Model terus diperbarui agar sesuai dengan tujuan yang berubah seiring waktu.<\/p>\n<p>Layanan penilaian berbasis cloud Tes Uchida-Kraepelin menyediakan berkas CSV berisi hasil penerapan suatu model tertentu pada data mentah.<\/p>\n<p>Jika model sesuai tujuan sudah tersedia, hasilnya dapat digunakan. Jika belum, AI dapat menganalisis hubungan data klinis dengan data mentah atau hasil penilaian yang ada untuk membantu mengembangkan model baru.<\/p>\n<p>Pertimbangkan Tes Uchida-Kraepelin sebagai sumber daya bagi inisiatif DX Anda.<\/p>\n<h3>Usulan DX: menggunakan tes untuk membantu mengurangi kecelakaan jalan<\/h3>\n<p>SDG 3 mengenai kesehatan dan kesejahteraan untuk semua mencakup target 3.6 tentang pengurangan separuh kematian dan cedera akibat kecelakaan lalu lintas, dengan tenggat awal 2020. Dari berbagai pendekatan keselamatan jalan, mari pertimbangkan pemanfaatan Tes Uchida-Kraepelin.<\/p>\n<p>Untuk menilai kegunaannya, perlu diteliti apakah karakteristik kemampuan, kepribadian dan perilaku berkorelasi dengan kecelakaan. Artikel asli melaporkan perbedaan distribusi karakteristik hasil penilaian antara orang yang pernah menyebabkan kecelakaan serius dan yang tidak pernah menyebabkan kecelakaan.<\/p>\n<p>Dengan menetapkan kriteria penilaian sementara untuk membedakan kecenderungan risiko lebih rendah dan lebih tinggi, lalu memakai data nyata membagi masing-masing populasi menjadi A dan B, diperoleh tabel berikut.<\/p>\n<div class=\"uk-dx-data-table\" tabindex=\"0\" role=\"region\" aria-label=\"Ilustrasi keselamatan jalan: perbandingan kelompok\" style=\"max-width:100%;overflow-x:auto;\">\n<table style=\"min-width:420px;width:100%;\" border=\"0\" cellspacing=\"0\" cellpadding=\"0\">\n<tbody>\n<tr style=\"height: 18.0pt;\">\n<td class=\"xl65\" style=\"height: 18pt; width: 52pt; text-align: center;\" width=\"69\" height=\"24\"><\/td>\n<td class=\"xl65\" style=\"border-left: none; width: 52pt; text-align: center;\" align=\"left\" width=\"69\">Kelompok mengalami kecelakaan<\/td>\n<td class=\"xl65\" style=\"border-left: none; width: 52pt; text-align: center;\" align=\"left\" width=\"69\">Kelompok tanpa kecelakaan<\/td>\n<\/tr>\n<tr style=\"height: 18.0pt;\">\n<td class=\"xl65\" style=\"height: 18pt; border-top: none; text-align: center;\" align=\"left\" height=\"24\">Kelompok A<\/td>\n<td class=\"xl66\" style=\"border-top: none; border-left: none; text-align: center;\" align=\"right\">38%<\/td>\n<td class=\"xl66\" style=\"border-top: none; border-left: none; text-align: center;\" align=\"right\">76%<\/td>\n<\/tr>\n<tr style=\"height: 18.0pt;\">\n<td class=\"xl65\" style=\"height: 18pt; border-top: none; text-align: center;\" align=\"left\" height=\"24\">Kelompok B<\/td>\n<td class=\"xl66\" style=\"border-top: none; border-left: none; text-align: center;\" align=\"right\">62%<\/td>\n<td class=\"xl66\" style=\"border-top: none; border-left: none; text-align: center;\" align=\"right\">24%<\/td>\n<\/tr>\n<tr>\n<td style=\"border-top: none; text-align: center;\">Total<\/td>\n<td style=\"border-top: none; border-left: none; text-align: center;\">100%<\/td>\n<td style=\"border-top: none; border-left: none; text-align: center;\">100%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>Pembagian ini tidak memisahkan semua orang yang mengalami kecelakaan dari yang bebas kecelakaan. Namun, dalam perbandingan ini A memiliki kecenderungan terkait kecelakaan yang lebih rendah daripada B.<\/p>\n<p>Bagaimana angka ilustrasinya jika B tidak mengemudi? Artikel Jepang tahun 2021 menggunakan asumsi probabilitas kecelakaan sekitar 1% setahun. Menerapkannya pada 10.000 orang menghasilkan tabel berikut.<\/p>\n<div class=\"uk-dx-data-table\" tabindex=\"0\" role=\"region\" aria-label=\"Ilustrasi keselamatan jalan: perbandingan kelompok\" style=\"max-width:100%;overflow-x:auto;\">\n<table style=\"min-width:420px;width:100%;\">\n<tbody>\n<tr>\n<td style=\"text-align: center;\" width=\"69\"><\/td>\n<td style=\"text-align: center;\" width=\"68\">Kelompok mengalami kecelakaan<\/td>\n<td style=\"text-align: center;\" width=\"69\">Kelompok tanpa kecelakaan<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">Kelompok A<\/td>\n<td style=\"text-align: center;\">38<\/td>\n<td style=\"text-align: center;\">7524<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">Kelompok B<\/td>\n<td style=\"text-align: center;\">62<\/td>\n<td style=\"text-align: center;\">2376<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">Total<\/td>\n<td style=\"text-align: center;\">100 (1%)<\/td>\n<td style=\"text-align: center;\">9900 (99%)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>Perhitungan dalam artikel asli:<br \/>\nKelompok A: 38 \u00f7 7524 \u2248 0,5%<br \/>\nKelompok B: 62 \u00f7 2376 \u2248 2,6%<br \/>\nDalam ilustrasi ini, angka B lebih dari lima kali angka A. Jika B tidak mengemudi, angka pada pengemudi yang tersisa sekitar 0,5%, bukan asumsi 1%, atau kira-kira separuh. Lihat catatan di bawah untuk penyebut berupa seluruh anggota kelompok.<br \/>\nNamun, menolak izin mengemudi B juga akan melarang 2.376 orang tanpa kecelakaan mengemudi, sehingga tidak realistis.<br \/>\nDi sinilah teknologi informasi mungkin membantu. Artikel mengusulkan agar B diprioritaskan dalam dorongan beralih ke ASV (Advanced Safety Vehicles) atau kendaraan otomatis, dengan tujuan memperoleh manfaat keselamatan serupa.<\/p>\n<p>Artikel asli menggambarkan Jepang memiliki relatif sedikit kecelakaan secara internasional dan menyarankan potensi lebih besar di negara dengan sistem perizinan atau aturan lalu lintas yang belum berkembang. Ini adalah usulan artikel, bukan efek yang telah dibuktikan di semua negara.<br \/>\nKesehatan dan kesejahteraan bagi semua.<\/p>\n<div class=\"uk-editorial-note\" style=\"border-left:4px solid #777;padding:12px;background:#f5f5f5;\"><strong>Catatan tentang contoh asli dan perhitungan<\/strong><\/p>\n<p>Terjemahan ini mempertahankan tabel dan contoh artikel Jepang tertanggal 9 Juli 2021. Angka tahunan 1% adalah asumsi contoh, bukan statistik nasional terkini. Tenggat awal target SDG 3.6 adalah 2020. Rumus asli membagi jumlah orang mengalami kecelakaan dengan orang tanpa kecelakaan; proporsi terhadap seluruh anggota kelompok ialah 38\/(38+7524) \u2248 0,50% dan 62\/(62+2376) \u2248 2,54%. Ilustrasi ini bukan bukti sebab-akibat, prediksi risiko individu yang tervalidasi, atau jaminan penurunan kecelakaan melalui tes, ASV maupun kendaraan otomatis. Penerapan pada populasi lain memerlukan validasi. Jangan menentukan penerimaan kerja, izin mengemudi atau kelayakan lain hanya dari tes ini.<\/p>\n<p><a href=\"https:\/\/sdgs.un.org\/goals\/goal3\">SDG 3.6 \u2014 United Nations<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Halaman ini diterjemahkan secara otomatis dari teks asli bahasa Jepang menggunakan AI generatif. Terjemahan da &hellip; <a href=\"https:\/\/adc-japan.com\/uk\/id\/tips-id\/12710.html\" class=\"more-link\">\u7d9a\u304d\u3092\u8aad\u3080 <span class=\"screen-reader-text\">Tes Uchida-Kraepelin dan Transformasi Digital (DX)<\/span> <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":12007,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[134],"tags":[],"class_list":["post-12710","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tips-id"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 - aioseo.com -->\n\t<meta name=\"description\" content=\"Pemanfaatan data mentah dan model penilaian Tes Uchida-Kraepelin untuk DX, disertai ilustrasi keselamatan jalan serta batasan perhitungannya.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" 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