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Analisis tren - Riwayat revisi
2026-09-16T17:58:36Z
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Maintenance script: Presentation V4: sitasi, referensi, Math, Wikimedia Commons, dan atribusi
2026-08-25T08:56:48Z
<p>Presentation V4: sitasi, referensi, Math, Wikimedia Commons, dan atribusi</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Revisi sebelumnya</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revisi per 25 Agustus 2026 08.56</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l4">Baris 4:</td>
<td colspan="2" class="diff-lineno">Baris 4:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Metode Least Square ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Metode Least Square ==</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Metode yang dapat digunakan untuk analisis time series ini adalah</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Metode yang dapat digunakan untuk analisis time series ini adalah</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Metode Garis Linier Secara Bebas (Free Hand Method),</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Metode Garis Linier Secara Bebas (Free Hand Method),</div></td></tr>
<tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l20">Baris 20:</td>
<td colspan="2" class="diff-lineno">Baris 19:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>: a = ΣY / N dan</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>: a = ΣY / N dan</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>: b = ΣXY / ΣX<sup>2</sup></div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>: b = ΣXY / ΣX<sup>2</sup></div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">== Referensi ==</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* Bianchi M., Boyle M., Hollingsworth D. (1999), "A comparison of methods for trend estimation", ''Applied Economics Letters'', 6(2): 103–109.</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* Chatfield, C. (1993), "Calculating Interval Forecasts", ''Journal of Business and Economic Statistics'', 11(2): 121–135.</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Sumber dan atribusi ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Sumber dan atribusi ==</div></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Konten artikel ini diadaptasi dari [https://id.wikipedia.org/w/index.php?title=Analisis+tren&oldid=22477909 Wikipedia bahasa Indonesia], revisi 22477909 (2022-12-26T11:29:56Z), yang tersedia berdasarkan lisensi Creative Commons Atribusi-BerbagiSerupa (CC BY-SA). Mohon gunakan konten ini secara bijak serta sesuai dengan ketentuan lisensi yang berlaku.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Konten artikel ini diadaptasi dari [https://id.wikipedia.org/w/index.php?title=Analisis+tren&oldid=22477909 Wikipedia bahasa Indonesia], revisi 22477909 (2022-12-26T11:29:56Z), yang tersedia berdasarkan lisensi Creative Commons Atribusi-BerbagiSerupa (CC BY-SA). Mohon gunakan konten ini secara bijak serta sesuai dengan ketentuan lisensi yang berlaku.</div></td></tr>
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Maintenance script: Impor teks terkontrol dari Wikipedia bahasa Indonesia; revisi 22477909; atribusi sumber disertakan.
2026-08-25T08:19:04Z
<p>Impor teks terkontrol dari Wikipedia bahasa Indonesia; revisi 22477909; atribusi sumber disertakan.</p>
<p><b>Halaman baru</b></p><div>'''Analisis [http://trendsdaily.net trends]''' merupakan suatu metode analisis [[statistika]] yang ditujukan untuk melakukan suatu estimasi atau peramalan pada masa yang akan datang. Untuk melakukan peramalan dengan baik maka dibutuhkan berbagai macam [[informasi]] ([[data]]) yang cukup banyak dan diamati dalam periode waktu yang relatif cukup panjang, sehingga hasil analisis tersebut dapat mengetahui sampai berapa besar fluktuasi yang terjadi dan faktor-faktor apa saja yang memengaruhi terhadap perubahan tersebut.<br />
<br />
Secara teoristis, dalam analisis [[runtun waktu]] ('''time series''') hal yang paling menentukan adalah kualitas dan keakuratan dari data-data yang diperoleh, serta waktu atau periode dari data-data tersebut dikumpulkan. Jika data yang dikumpulkan tersebut semakin banyak maka semakin baik pula estimasi atau peramalan yang diperoleh. Sebaliknya, jika data yang dikumpulkan semakin sedikit maka hasil estimasi atau peramalannya akan semakin jelek.<br />
<br />
== Metode Least Square ==<br />
<br />
Metode yang dapat digunakan untuk analisis time series ini adalah<br />
* Metode Garis Linier Secara Bebas (Free Hand Method),<br />
* Metode Setengah Rata-Rata (Semi Average Method),<br />
* Metode Rata-Rata Bergerak (Moving Average Method) dan<br />
* Metode Kuadrat Terkecil (Least Square Method).<br />
<br />
Secara khusus, analisis time series dengan metode '''kuadrat terkecil''' dapat dibagi dalam dua kasus, yaitu kasus data genap dan kasus data ganjil. Persamaan [[garis linear]] dari analisis time series akan mengikuti:<br />
: Y = a + b X.<br />
Keterangan:<br />
Y adalah variabel dependen (tak-bebas) yang dicari [http://trendsdaily.net trends] nya dan<br />
X adalah variabel independen (bebas) dengan menggunakan waktu (biasanya dalam tahun).<br />
<br />
Sedangkan untuk mencari nilai konstanta (a) dan parameter (b) dapat dipakai persamaan:<br />
: a = ΣY / N dan<br />
: b = ΣXY / ΣX<sup>2</sup><br />
<br />
== Referensi ==<br />
* Bianchi M., Boyle M., Hollingsworth D. (1999), "A comparison of methods for trend estimation", ''Applied Economics Letters'', 6(2): 103–109.<br />
* Chatfield, C. (1993), "Calculating Interval Forecasts", ''Journal of Business and Economic Statistics'', 11(2): 121–135.<br />
<br />
<br />
<br />
== Sumber dan atribusi ==<br />
<br />
Konten artikel ini diadaptasi dari [https://id.wikipedia.org/w/index.php?title=Analisis+tren&oldid=22477909 Wikipedia bahasa Indonesia], revisi 22477909 (2022-12-26T11:29:56Z), yang tersedia berdasarkan lisensi Creative Commons Atribusi-BerbagiSerupa (CC BY-SA). Mohon gunakan konten ini secara bijak serta sesuai dengan ketentuan lisensi yang berlaku.</div>
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