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PENGARUH TRAINING, MASA KERJA DAN KUALITAS KERJA TERHADAP KINERJA di LINE PRODUKSI PT BUMI INDONESIA SUBUR DENGAN MENGGUNAKAN METODE REGRESI LINEAR BERGANDA Soleh Sofyan; Nia Kurniasih; Purnama Dewi, Desilia
Jurnal Sekretari Universitas Pamulang Vol. 11 No. 1 (2024): JURNAL SEKRETARI
Publisher : Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/skr.v11i1.38203

Abstract

ABSTRAK Di era globalisasi saat ini setiap organisasi atau perusahaan saling bersaing menunjukkan keunggulan perusahannya masing-masing. Persaingan yang terus-menerus berkembang saat ini menuntut perusahaan untuk mampu bertahan dalam persaingan yang ada, serta mengembangkan setiap sumber daya manusia yang berkualitas. Perusahaan akan berupaya memaksimalkan karyawan untuk mendapatkan keuntungan dan nilai bagi perusahaan, sehingga dapat meningkatkan kesejahteraan pemilik dan karyawan. Terdapat beberapa faktor yang berpengaruh terhadap sumber daya manusia yaitu training, masa kerja kerja dan kualitas kerja. Tujuan penelitian ini untuk menganalisis pengaruh training, masa kerja dan kualitas secara simultan terhadap kinerja karyawan pada PT Bumi Indonesia Subur. Populasi dalam penelitian ini adalah operator line PT Bumi Indonesia Subur. Jumlah sampel dalam penelitian ini adalah 50 dengan menggunakan teknik non propobability sampling. Teknik analisis data dalam penelitian ini menggunakan analisis regresi linier berganda, uji asumsi klasik, uji statistika. Kata kunci: Kinerja, Training, Masa Kerja, Kualitas kerja, Regresi linier berganda THE INFLUENCE OF TRAINING, PERIOD OF WORK AND QUALITY OF WORK ON PERFORMANCE IN THE PT BUMI INDONESIA SUBUR PRODUCTION LINE USING MULTIPLE LINEAR REGRESSION METHOD ABSTRACT In thel culrrelnt elra of globalization, elvelry organization or company compeltels with elach othelr to show thel advantagels of thelir relspelctivel companiels. Compeltition that is constantly delvelloping at this timel relqulirels companiels to bel ablel to sulrvivel in thel elxisting compeltition, and delvellop elvelry qulality hulman relsoulrcel. Thel company will selelk to maximizel elmployelels to gain profit and valulel for thel company, so as to increlasel thel wellfarel of ownelrs and elmployelels. Thelrel arel selvelral factors that influlelncel hulman relsoulrcels, namelly training, work pelriod and qulality of work. Thel pulrposel of this stuldy was to analyzel thel elffelct of training, yelars of selrvicel and qulality simulltaneloulsly on elmployelel pelrformancel at PT Bulmi Indonelsia Sulbulr. Thel popullation in this stuldy is thel linel opelrator PT Bulmi Indonelsia Sulbulr. Thel nulmbelr of samplels in this stuldy was 50 ulsing a non-probability sampling telchniqulel. Data analysis telchniqulels in this stuldy ulseld mulltiplel linelar relgrelssion analysis, classical assulmption telst, statistical telst. Keywords: Performance, training work period Quality of work, Linear Regression
Pengendalian Persediaan Kompresor Kaishan Kombina Metode TS dan EOQ di PT. Karya Teknik Semesta Nia Kurniasih; Soleh Sofyan; Patria Adhistian
EKOMA : Jurnal Ekonomi, Manajemen, Akuntansi Vol. 3 No. 5: Juli 2024
Publisher : CV. Ulil Albab Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/ekoma.v3i5.4686

Abstract

The study entited anaysis of merchandise inventory control compressor product of Kaishan at PT. Karya Teknik Semesta in Jakarta 2023. This event will be based on research from compressor orders made with to little or too much quantity, and orders that are not properly scheduled. Which led to the company losing saes at the end of 2022, which resulted in a shortage of inventory in Januari 2023. The purpose of this research is to know how many demand for compressor products for the next period using the Time Series method, how many orders to be done each time (EOQ), the amount of safety stock (SS), and reordering point (ROP). The data obtained are then processed bt the comparing severa methods included in the Time Series method, namely; Moving Average (MA), Weight Moving Average (WMA), Exponentia Smoothing. To obtain the smalest Mean Absolute Deviation (MAD) which will be used to caculate demand forcasting for the next period. From the result of the anaysis the Time Series, EOQ, SS, and ROP, inventory costs are more efficient than the past two years (2021 and 2022).