{"id":10739,"date":"2022-08-09T14:26:12","date_gmt":"2022-08-09T11:26:12","guid":{"rendered":"https:\/\/bestessayhomework.com\/tr\/?p=10739"},"modified":"2022-08-09T14:26:12","modified_gmt":"2022-08-09T11:26:12","slug":"dogrusal-olmayan-maliyet-davranisi-muhasebe-alaninda-tez-yaptirma-muhasebe-tez-yaptirma-ucretleri-muhasebe-odevleri-muhasebe-odev-ucretleri","status":"publish","type":"post","link":"https:\/\/bestessayhomework.com\/tr\/dogrusal-olmayan-maliyet-davranisi-muhasebe-alaninda-tez-yaptirma-muhasebe-tez-yaptirma-ucretleri-muhasebe-odevleri-muhasebe-odev-ucretleri\/","title":{"rendered":"Do\u011frusal Olmayan Maliyet Davran\u0131\u015f\u0131 \u2013 Muhasebe Alan\u0131nda Tez Yapt\u0131rma \u2013 Muhasebe Tez Yapt\u0131rma \u00dccretleri \u2013 Muhasebe \u00d6devleri \u2013 Muhasebe \u00d6dev \u00dccretleri"},"content":{"rendered":"

\u00c7oklu Regresyon<\/span><\/strong><\/h3>\n

Anderson Company \u00f6rne\u011finde, malzeme ta\u015f\u0131ma maliyetindeki de\u011fi\u015fkenli\u011fin y\u00fczde 86’s\u0131, faaliyet \u00e7\u0131kt\u0131s\u0131ndaki (hareket say\u0131s\u0131) de\u011fi\u015fikliklerle a\u00e7\u0131kland\u0131. Sonu\u00e7 olarak, \u015firket ek a\u00e7\u0131klay\u0131c\u0131 de\u011fi\u015fkenler aramak isteyebilir. \u00d6rne\u011fin, ta\u015f\u0131nan toplam mesafe, \u00f6zellikle tesis yerle\u015fimi, par\u00e7alar\u0131n ve \u00fcr\u00fcnlerin bir konumdan di\u011ferine ta\u015f\u0131nmas\u0131 i\u00e7in \u00f6nemli zaman harcanacak \u015fekildeyse yararl\u0131 olabilir.<\/span><\/p>\n

\u00dc\u00e7 de\u011fi\u015fkenle (Y, X1, X2), F, V1 ve V2 parametrelerini hesaplamak i\u00e7in en az \u00fc\u00e7 nokta gereklidir. Noktalar\u0131 g\u00f6rmek zorla\u015f\u0131r \u00e7\u00fcnk\u00fc \u00fc\u00e7 boyutlu olarak \u00e7izilmeleri gerekir. Da\u011f\u0131l\u0131m grafi\u011fi y\u00f6ntemini veya y\u00fcksek-d\u00fc\u015f\u00fck y\u00f6ntemini kullanmak pratik de\u011fildir.<\/span><\/p>\n

Bununla birlikte, en k\u00fc\u00e7\u00fck kareler y\u00f6nteminin geni\u015fletilmesi basittir. En uygun denklemi veren F, V1 ve V2 i\u00e7in de\u011ferler sa\u011flayan bir denklem seti geli\u015ftirmek nispeten basittir.<\/span><\/p>\n

\u0130ki veya daha fazla a\u00e7\u0131klay\u0131c\u0131 de\u011fi\u015fken i\u00e7eren bir denklemi uydurmak i\u00e7in en k\u00fc\u00e7\u00fck kareler kullan\u0131ld\u0131\u011f\u0131nda, y\u00f6nteme \u00e7oklu regresyon denir. \u00d6nemli \u00f6l\u00e7\u00fcde artan \u00e7oklu regresyonun hesaplama karma\u015f\u0131kl\u0131\u011f\u0131 bilgisayar taraf\u0131ndan kolayla\u015ft\u0131r\u0131lmaktad\u0131r. Asl\u0131nda, \u00e7oklu regresyonun herhangi bir pratik uygulamas\u0131 bir bilgisayar kullan\u0131m\u0131n\u0131 gerektirir.<\/span><\/p>\n

Anderson \u015eirketi \u00f6rne\u011fine d\u00f6nelim. R2’nin sadece y\u00fczde 86 oldu\u011funu ve sabit maliyet katsay\u0131s\u0131n\u0131n anlaml\u0131 olmad\u0131\u011f\u0131n\u0131 hat\u0131rlay\u0131n. Belki de malzeme ta\u015f\u0131ma maliyetlerini a\u00e7\u0131klamaya yard\u0131mc\u0131 olabilecek ba\u015fka bir de\u011fi\u015fken vard\u0131r. Anderson \u015eirketi’nin kontrol\u00f6r\u00fcn\u00fcn ara\u015ft\u0131rd\u0131\u011f\u0131n\u0131 ve baz\u0131 aylarda di\u011fer aylara g\u00f6re \u00e7ok daha fazla libre malzemenin ta\u015f\u0131nd\u0131\u011f\u0131n\u0131 buldu\u011funu varsayal\u0131m. Daha a\u011f\u0131r malzemeler ta\u015f\u0131nd\u0131\u011f\u0131nda, artan y\u00fck\u00fcn \u00fcstesinden gelmek i\u00e7in ek ekipman kullan\u0131ld\u0131.<\/span><\/p>\n

\u015eimdi, ba\u011f\u0131ms\u0131z de\u011fi\u015fkenler olarak hareket say\u0131s\u0131n\u0131 ve ta\u015f\u0131nan pound say\u0131s\u0131n\u0131 kullanarak \u00e7oklu bir regresyon \u00e7al\u0131\u015ft\u0131ral\u0131m. Regresyon i\u00e7in bir bilgisayar ekran\u0131 g\u00f6sterilir.<\/span><\/p>\n

Bilgisayar ekran\u0131 baz\u0131 \u00e7ok ilgin\u00e7 ve faydal\u0131 bilgiler aktar\u0131yor. Maliyet denklemi, en alttaki tablonun ilk iki s\u00fctunu taraf\u0131ndan tan\u0131mlan\u0131r. \u0130lk s\u00fctun, bireysel maliyet bile\u015fenlerini tan\u0131mlar.<\/span><\/p>\n

Kesi\u015fme, sabit faaliyet maliyetidir, ilk X de\u011fi\u015fkeni hareket say\u0131s\u0131d\u0131r ve ikinci X de\u011fi\u015fkeni, ta\u015f\u0131nan pound say\u0131s\u0131d\u0131r. “Katsay\u0131lar” etiketli s\u00fctun, her bir faaliyet s\u00fcr\u00fcc\u00fcs\u00fc i\u00e7in tahmini sabit maliyeti ve birim ba\u015f\u0131na de\u011fi\u015fken maliyeti tan\u0131mlar. B\u00f6ylece maliyet denklemi a\u015fa\u011f\u0131daki gibi yaz\u0131labilir.<\/span><\/p>\n

\n

Maliyet<\/a> HESAPLAMA form\u00fcl\u00fc<\/span>
\nTam maliyet Y\u00f6ntemi<\/span>
\nSafha maliyet Sistemi form\u00fclleri<\/span>
\nGenel \u00fcretim maliyeti HESAPLAMA<\/span>
\n\u00dcretim maliyeti HESAPLAMA form\u00fcl\u00fc<\/span>
\nHedef maliyet Nedir<\/span>
\nStandart maliyet y\u00f6ntemi<\/span>
\nSafha maliyet sistemi \u00f6rnek<\/span><\/p>\n

\n

Tek bir faaliyet etkenini i\u00e7eren maliyet denkleminde oldu\u011fu gibi, faaliyet maliyetini tahmin etmek i\u00e7in \u00f6nceki denklem kullan\u0131labilir. Diyelim ki Kas\u0131m ay\u0131nda \u015firketin 17.000 pound malzeme ta\u015f\u0131nmas\u0131yla 350 hamle yapmas\u0131 bekleniyor. Tahmini malzeme ta\u015f\u0131ma maliyeti a\u015fa\u011f\u0131daki gibidir.<\/span><\/p>\n

Belirleme katsay\u0131s\u0131n\u0131n y\u00fczde 99 oldu\u011funa dikkat edin, ta\u015f\u0131nan pound de\u011fi\u015fkeni eklenerek a\u00e7\u0131klama g\u00fcc\u00fcnde \u00f6nemli bir geli\u015fme elde edilir. Ayr\u0131ca, her \u00fc\u00e7 katsay\u0131 da olduk\u00e7a anlaml\u0131d\u0131r.<\/span><\/p>\n

\u00c7oklu regresyon i\u00e7in, R2 genellikle \u00e7oklu belirleme katsay\u0131s\u0131 olarak adland\u0131r\u0131l\u0131r. Ayr\u0131ca standart tahmin hatas\u0131n\u0131n, Se’nin \u00e7oklu regresyon ayar\u0131nda mevcut oldu\u011funa dikkat edin. Daha \u00f6nce belirtildi\u011fi gibi, standart tahmin hatas\u0131, maliyet tahminleri etraf\u0131nda g\u00fcven aral\u0131klar\u0131 olu\u015fturmak i\u00e7in kullan\u0131labilir. \u00d6rneklemek i\u00e7in, X1 \udbff\udc00 350 hareket etti\u011finde tahmini malzeme ta\u015f\u0131ma maliyeti i\u00e7in y\u00fczde 95 g\u00fcven aral\u0131\u011f\u0131n\u0131 g\u00f6z \u00f6n\u00fcnde bulundurun.<\/span><\/p>\n

i\u00e7in bir kez daha ba\u015fvurun. En alttaki tablonun d\u00f6rd\u00fcnc\u00fc ve be\u015finci s\u00fctunlar\u0131, \u00fc\u00e7 parametreyle ilgili baz\u0131 istatistiksel verileri sunmaktad\u0131r. D\u00f6rd\u00fcnc\u00fc s\u00fctun, bu parametrelerin her biri i\u00e7in t istatistiklerini sunar. Bu t istatistikleri, parametrelerin s\u0131f\u0131rdan farkl\u0131 oldu\u011fu hipotezini test etmek i\u00e7in kullan\u0131l\u0131r.<\/span><\/p>\n

Be\u015finci s\u00fctun, elde edilen \u00f6nem d\u00fczeyini g\u00f6sterir. T\u00fcm parametreler 0,0001 d\u00fczeyinde anlaml\u0131d\u0131r. B\u00f6ylece, iki itici g\u00fcc\u00fcn yararl\u0131 oldu\u011funa ve malzeme ta\u015f\u0131ma faaliyetinin sabit bir maliyet bile\u015fenine sahip oldu\u011funa biraz g\u00fcvenebiliriz. Bu \u00f6rnek, \u00e7oklu regresyonun faaliyet maliyetlerinin davran\u0131\u015f\u0131n\u0131 belirlemek i\u00e7in yararl\u0131 bir ara\u00e7 olabilece\u011fini \u00e7ok a\u00e7\u0131k bir \u015fekilde g\u00f6stermektedir.<\/span><\/p>\n

\u00d6\u011frenme E\u011frisi ve Do\u011frusal Olmayan Maliyet Davran\u0131\u015f\u0131<\/span><\/strong><\/h3>\n

Do\u011frusal olmayan maliyet e\u011frisinin \u00f6nemli bir t\u00fcr\u00fc \u00f6\u011frenme e\u011frisidir. \u00d6\u011frenme e\u011frisi, \u00fcretilen hacim artt\u0131k\u00e7a birim ba\u015f\u0131na \u00e7al\u0131\u015f\u0131lan emek saatlerinin nas\u0131l azald\u0131\u011f\u0131n\u0131 g\u00f6sterir. \u00d6\u011frenme e\u011frisinin temeli, bir eylemi tekrar tekrar ger\u00e7ekle\u015ftirdi\u011fimiz i\u00e7in neredeyse sezgiseldir, geli\u015ftiririz ve her ek performans \u00f6ncekilerden daha az zaman al\u0131r.<\/span><\/p>\n

G\u00f6revi nas\u0131l yapaca\u011f\u0131m\u0131z\u0131 \u00f6\u011freniyoruz, daha verimli oluyoruz ve p\u00fcr\u00fczleri gideriyoruz. Bir imalat firmas\u0131nda \u00f6\u011frenme s\u00fcre\u00e7 boyunca ger\u00e7ekle\u015fir: i\u015f\u00e7iler g\u00f6revlerini \u00f6\u011frenir ve y\u00f6neticiler \u00fcretimi daha verimli bir \u015fekilde planlamay\u0131 ve i\u015f ak\u0131\u015f\u0131n\u0131 d\u00fczenlemeyi \u00f6\u011frenir. Bu etki ilk olarak u\u00e7ak end\u00fcstrisinde belgelenmi\u015ftir.<\/span><\/p>\n

Y\u00f6neticiler art\u0131k \u00f6\u011frenme e\u011frisinin arkas\u0131ndaki fikirlerin imalat firmalar\u0131n\u0131n yan\u0131 s\u0131ra hizmet sekt\u00f6r\u00fcne de yay\u0131labilece\u011fini g\u00f6rebilirler. Pazarlama, da\u011f\u0131t\u0131m ve sat\u0131\u015f sonras\u0131 hizmet maliyetleri de \u00fcretilen ve sat\u0131lan birim say\u0131s\u0131 artt\u0131k\u00e7a azal\u0131r.<\/span>\u00a0\u00d6\u011frenme e\u011frisi modeli iki yayg\u0131n bi\u00e7im al\u0131r: k\u00fcm\u00fclatif ortalama zamanl\u0131 \u00f6\u011frenme e\u011frisi modeli ve art\u0131ml\u0131 birim zamanl\u0131 \u00f6\u011frenme e\u011frisi modeli.<\/span><\/p>\n

K\u00fcm\u00fclatif Ortalama S\u00fcreli \u00d6\u011frenme E\u011frisi<\/span><\/strong><\/h3>\n

K\u00fcm\u00fclatif ortalama-zaman \u00f6\u011frenme e\u011frisi modeli, birim ba\u015f\u0131na k\u00fcm\u00fclatif ortalama s\u00fcrenin, \u00fcretilen birimlerin k\u00fcm\u00fclatif miktar\u0131 her iki kat\u0131na \u00e7\u0131kt\u0131\u011f\u0131nda sabit bir y\u00fczde veya \u00f6\u011frenme oran\u0131 ile azald\u0131\u011f\u0131n\u0131 belirtir. \u00d6\u011frenme oran\u0131 y\u00fczde olarak ifade edilir ve bir \u00f6nceki \u00fcniteyi yapmak i\u00e7in ge\u00e7en s\u00fcreye ba\u011fl\u0131 olarak bir sonraki \u00fcniteyi yapmak i\u00e7in gereken zaman\u0131n y\u00fczdesini verir.<\/span><\/p>\n

\u00d6\u011frenme oran\u0131 deneyimle belirlenir ve y\u00fczde 50 ile 100 aras\u0131nda olmal\u0131d\u0131r. Y\u00fczde 50’lik bir \u00f6\u011frenme oran\u0131, sonunda, birim ba\u015f\u0131na hi\u00e7bir \u00e7al\u0131\u015fma s\u00fcresinin olmamas\u0131yla, sa\u00e7ma bir sonu\u00e7la sonu\u00e7lanacakt\u0131r. Y\u00fczde 100 \u00f6\u011frenme oran\u0131, \u00f6\u011frenme olmad\u0131\u011f\u0131n\u0131 g\u00f6sterir (\u00e7\u00fcnk\u00fc azalma miktar\u0131 s\u0131f\u0131rd\u0131r). Bu modeli g\u00f6stermek i\u00e7in genellikle y\u00fczde 80’lik bir \u00f6\u011frenme e\u011frisi kullan\u0131l\u0131r (muhtemelen orijinal \u00f6\u011frenme e\u011frisinin u\u00e7ak end\u00fcstrisi ile \u00e7al\u0131\u015fmas\u0131 y\u00fczde 80’lik bir \u00f6\u011frenme e\u011frisi buldu\u011fu i\u00e7in).<\/span><\/p>\n

\u0130lk \u00fcnite i\u00e7in y\u00fczde 80 \u00f6\u011frenme oran\u0131 ve 100 do\u011frudan \u00e7al\u0131\u015fma saati ile k\u00fcm\u00fclatif ortalama zaman \u00f6\u011frenme e\u011frisi i\u00e7in veri verir.<\/span><\/p>\n

Kal\u0131n sat\u0131rlar\u0131n bize ikiye katlama form\u00fcl\u00fcne g\u00f6re k\u00fcm\u00fclatif ortalama s\u00fcreyi ve k\u00fcm\u00fclatif toplam zaman\u0131 verdi\u011fini g\u00f6r\u00fcyoruz. Orijinal miktar\u0131n iki kat\u0131 olmayan birimler i\u00e7in bu miktarlar\u0131 nas\u0131l elde ederiz? Bu, k\u00fcm\u00fclatif ortalama zamanl\u0131 \u00f6\u011frenme modelinin logaritmik bir ili\u015fki ald\u0131\u011f\u0131n\u0131 fark ederek yap\u0131l\u0131r.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

\u00c7oklu Regresyon Anderson Company \u00f6rne\u011finde, malzeme ta\u015f\u0131ma maliyetindeki de\u011fi\u015fkenli\u011fin y\u00fczde 86’s\u0131, faaliyet \u00e7\u0131kt\u0131s\u0131ndaki (hareket say\u0131s\u0131) de\u011fi\u015fikliklerle a\u00e7\u0131kland\u0131. Sonu\u00e7 olarak, \u015firket ek a\u00e7\u0131klay\u0131c\u0131 de\u011fi\u015fkenler aramak isteyebilir. \u00d6rne\u011fin, ta\u015f\u0131nan toplam mesafe, \u00f6zellikle tesis yerle\u015fimi, par\u00e7alar\u0131n ve \u00fcr\u00fcnlerin bir konumdan di\u011ferine ta\u015f\u0131nmas\u0131 i\u00e7in \u00f6nemli zaman harcanacak \u015fekildeyse yararl\u0131 olabilir. \u00dc\u00e7 de\u011fi\u015fkenle (Y, X1, X2), F, V1 ve V2…
Devam\u0131<\/a><\/p>\n","protected":false},"author":6,"featured_media":9964,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[26076,26078,26077],"tags":[26072,26074,26070,26071,26075,23409,26015,26073],"class_list":["post-10739","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-safha-maliyet-sistemi-formulleri","category-safha-maliyet-sistemi-ornek","category-uretim-maliyeti-hesaplama-formul","tag-genel-uretim-maliyeti-hesaplama","tag-hedef-maliyet-nedir","tag-maliyet-hesaplama-formulu","tag-safha-maliyet-sistemi-formulleri","tag-safha-maliyet-sistemi-ornek","tag-standart-maliyet-yontemi","tag-tam-maliyet-yontemi","tag-uretim-maliyeti-hesaplama-formulu"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/bestessayhomework.com\/tr\/wp-json\/wp\/v2\/posts\/10739","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bestessayhomework.com\/tr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bestessayhomework.com\/tr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bestessayhomework.com\/tr\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/bestessayhomework.com\/tr\/wp-json\/wp\/v2\/comments?post=10739"}],"version-history":[{"count":0,"href":"https:\/\/bestessayhomework.com\/tr\/wp-json\/wp\/v2\/posts\/10739\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/bestessayhomework.com\/tr\/wp-json\/wp\/v2\/media\/9964"}],"wp:attachment":[{"href":"https:\/\/bestessayhomework.com\/tr\/wp-json\/wp\/v2\/media?parent=10739"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bestessayhomework.com\/tr\/wp-json\/wp\/v2\/categories?post=10739"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bestessayhomework.com\/tr\/wp-json\/wp\/v2\/tags?post=10739"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}