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All Journal Jurnal Tirtayasa Ekonomika (Tirtayasa Economica Journal) JURNAL MANAJEMEN Penentuan harga obligasi dan teori tingkat bunga JENIUS (Jurnal Ilmiah Manajemen Sumber Daya Manusia) PINISI Discretion Review JEKPEND Jurnal Ekonomi dan Pendidikan Community Development Journal: Jurnal Pengabdian Masyarakat Sibatik Journal : Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, Dan Pendidikan Seminar Nasional Pengabdian Kepada Masyarakat KREATIF: Jurnal Pengabdian Masyarakat Nusantara Kompeten: Jurnal Ilmiah Ekonomi dan Bisnis Seminar Nasional Hasil Penelitian LP2M UNM Indo-Fintech Intellectuals: Journal of Economics and Business Economos : Jurnal Ekonomi dan Bisnis Cross-Border Journal of Business Management SMART: Jurnal Pengabdian Kepada Masyarakat Jurnal Akuntansi Pajak dan Manajemen IJRE
Anwar Anwar
Universitas Negeri Makassar
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Energy Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

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Pengaruh Disiplin Kerja, Motivasi Dan Gaya Kepemimpinan Terhadap Kinerja Karyawan pada PT PLN (PERSERO) Unit Pelaksana Proyek Pembangkit dan Jaringan Sulawesi Selatan Annisa Awaliyah Ridwan; Anwar Anwar
Jurnal Ilmiah Sumber Daya Manusia Vol 5, No 2 (2022): JENIUS (Jurnal Ilmiah Manajemen Sumber Daya Manusia)
Publisher : Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/JJSDM.v5i2.16507

Abstract

Penelitian ini bertujuan untuk mengetahui bagaimana pengaruh Disiplin Kerja, Motivasi dan Gaya Kepemimpinan terhadap Kinerja Pegawai. Jumlah sampel yang digunakan sebanyak 36 Karyawan PT. PLN ULP Sulawesi Selatan. Pengumpulan data dilakukan dengan menggunakan metode wawancara, Observasi dan angket. Teknis analisi data yang digunakan adalah analisi regresi linier berganda dengan menggunkan Statistical Product and Servise Solution (SPSS). Hasil Penelitian ini menunjukkan Disiplin Kerja (X1) secara parsial memberikan pengaruh positif dan signifikan terhadap Kinerja Karyawan. Motivasi (X2) secara parsial memberikan pengaruh positif namun tidak signifikan terhadap Kinerja Karyawan. Gaya Kepemimpinan (X3) secara parsial memberikan pengaruh positif dan signifikan terhadap Kinerja Karyawan.
Pengaruh Pertumbuhan Aset dan Struktur Modal terhadap Profitabilitas Perusahaan Sub Sektor Telekomunikasi di BEI Yunika Priscilla; Anwar Ramli; Anwar Anwar
Tirtayasa Ekonomika Vol 16, No 2 (2021)
Publisher : FEB Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35448/jte.v16i2.12050

Abstract

Penelitian ini bertujuan untuk mengetahui pengaruh pertumbuhan aset dan struktur modal (DER) terhadap profitabilitas (ROE) dengan menggunakan variabel kontrol ukuran perusahaan. Populasi dalam penelitian ini yaitu seluruh perusahaan yang ada di sub sektor telekomunikasi, sedangkan sampel yang digunakan adalah 5 perusahaan sub sektor telekomunikasi dengan periode pengamatan 2008-2019, dimana pengambilan sampelnya menggunakan teknik purposive sampling. Pengumpulan data menggunakan teknik dokumentasi dan  analisis data menggunakan regresi linear berganda.Penelitian ini memperoleh hasil bahwa adanya pengaruh positif dan signifikan antara variabel pertumbuhan aset terhadap profitabilitas (ROE), hal ini berarti semakin tinggi persentase pertumbuhan aset maka semakin bertambah pula kemampuan perusahaan untuk menghasilkan laba (profit) serta menunjukkan bahwa pertumbuhan aset yang meningkat akan diikuti pula dengan meningkatnya profitabilitas perusahaan dalam hal ini laba bersih yang menjadi hak pemegang saham perusahaan (ROE).Struktur modal (DER) berpengaruh negatif dan signifikan tehadap profitabilitas (ROE), arah yang negatif ini berarti semakin besar nilai DER yang dimiliki perusahaan yang diidentifikasikan dengan nilai total utang yang besar maka akan memperkecil nilai profitabilitas (ROE) yang diperoleh perusahaan. Dan secara bersama-sama (simultan) pertumbuhan aset dan DER berpengaruh signifikan terhadap profitabilitas (ROE), dimana pertumbuhan aset menggambarkan pertumbuhan aktiva perusahaan yang akan mempengaruhi profitabilitas perusahaan sedangkan struktur modal (DER) digunakan perusahaan agar mampu memaksimumkan profitabilitas dan nilai suatu perusahaan.  <img 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
PKM Edukasi Bisnis: Manajemen Usaha pada Usaha Gerabah Anwar Anwar; Inanna Inanna; Nurjannah Nurjannah
Seminar Nasional Pengabdian Kepada Masyarakat SEMINAR NASIONAL 2021 : PROSIDING EDISI 5
Publisher : Seminar Nasional Pengabdian Kepada Masyarakat

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Abstract

Abstrak. Mitra Pengabdian Kepada Masyarakat (PKM) ini adalah pemilik usaha mikro kecil gerabah. Pengetahuan tentang manajemen usaha masih sangat terbatas pada pemilik usaha gerabah. Adapun tujuan dari pengabdian ini adalah memotivasi pemilik usaha gerabah dalam memiliki pengetahuan dan keterampilan untuk bisa melakukan manajemen usaha yang benar sebagai pendukung dalam pengembangan usahanya. Metode pelaksanaan mengggunakan kombinasi ceramah dan praktek. Peserta terdiri atas pemilik usaha gerabah di Kelurahan Pallantikan Kecamatan Pattallassang Kabupaten Takalar. Teknik pelaksanaan kegiatan terdiri atas tiga tahap dimulai dari tahap persiapan, tahap pelaksanaan, dan tahap evaluasi kegiatan. Hasil yang dicapai dari pengabdian ini adalah (1) pemilik usaha sudah memahami analisis kelayakan usaha dengan titik pulang pokok dan potensi pasar, (2) pemilik usaha sudah memiliki pengetahuan dalam menentukan optimalisasi laba, (3) pemilik usaha sudah mampu menganalisis kinerja keuangan. Keterbatasan dalam pelatihan ini adalah metode pelaksanaan belum menggunakan teknik pendampingan, sehingga pengetahuan manajemen strategi belum dapat diimplementasikan dalam aktivitas usaha.Kata Kunci: Manajemen Usaha, Usaha Gerabah
Pelatihan Manajemen Keuangan Pada Pemilik Usaha Gerabah di Kecamatan Pattallassang Kabupaten Takalar Anwar Anwar; Sitti Hasbiah; Abd. Muis Dilla; Hety Budiyanti
Seminar Nasional Pengabdian Kepada Masyarakat PROSIDING EDISI 10: SEMNAS 2020
Publisher : Seminar Nasional Pengabdian Kepada Masyarakat

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Abstract

Abstrak. Pengetahuan tentang manajemen keuangan merupakan salah satu bagian utama dalam membangun kelanjutan dan daya saing usaha. Membekali para pemilik dengan pengetahuan tersebut akan sangat membantu perkembangan profesionalisme mereka dalam manajemen usaha. Adapun tujuan dari pengabdian ini adalah memotivasi pemilik usaha gerabah dalam memiliki pengetahuan dan keterampilan untuk bisa melakukan manajemen keuangan yang benar sebagai penunjang dalam pengembangan usahanya. Pengabdian ini mengggunakan kombinasi metode ceramah dan praktek. Peserta terdiri atas pemilik usaha gerabah di Kecamatan Pattallassang Kabupaten Takalar. Teknik pelaksanaan kegiatan terdiri atas tiga tahap dimulai dari tahap persiapan, tahap pelaksanaan, dan tahap evaluasi kegiatan. Hasil pengabdian menunjukkan bahwa pemilik usaha gerabah kesulitan dalam melakukan manajemen keuangan karena masih terbiasa dengan manajemen konvensional. Hasil yang dicapai dari pengabdian ini adalah (1) Pemilik usaha gerabah sudah mampu melakukan analisis pendanaan, (2) Mampu mengenal teknik-teknik dalam analisis investasi, (3) Sudah mengetahui  analisis pengelolaan aset. Keterbatasan dalam pelatihan ini adalah metode pelaksanaan belum menggunakan teknik pendampingan, sehingga pengetahuan tentang penyusunan setiap jenis laporan keuangan dapat diimplementasikan dalam aktivitas usaha.  Kata Kunci: Manajemen Keuangan, Usaha Gerabah
Penggunaan single index model dalam pembentukan portofolio optimal saham syariah Wilda Wilda; Uhud Darmawan Natsir; Anwar Anwar
JURNAL MANAJEMEN Vol 14, No 3 (2022): September
Publisher : Faculty of Economics and Business Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jmmn.v14i3.11551

Abstract

Penelitian ini bertujuan untuk mengetahui saham-saham perusahaan pada Jakarta Islamic Index (JII) yang membentuk portofolio optimal menggunakan single index model periode Juni 2017- November 2021, mengetahui proporsi dana masing-masing saham perusahaan yang membentuk portofolio optimal, serta mengetahui  return dan risiko dari portofolio optimal. Jenis penelitian ini adalah penelitian deskriptif dengan pendekatan kuantitatif. Populasi dalam penelitian ini adalah seluruh saham perusahaan yang tergabung dalam Jakarta Islamic Index periode Juni 2017 - November 2021. Adapun yang menjadi sampel dalam penelitian adalah 46 saham perusahaan yang termasuk dalam kriteria yang ditetapkan peneliti. Teknik pengumpulan data dilakukan dengan dokumentasi. Teknik analisis data menggunakan single index model. Hasil penelitian menunjukkan  bahwa 16 saham perusahaan sebagai penyusun portofolio optimal  yaitu saham ACES sebesar 1,52% ADRO sebesar 0,44%, ANTM sebesar 5,50%, BRPT sebesar 6,80%, CPIN sebesar 10,80%, ERAA sebesar 9,45%, INCO sebesar 7,42% INDY sebesar 3,83%, INKP sebesar 7,11%, ITMG sebesar 2,65% JPFA sebesar 2,10% MDKA sebesar 26,48%, MIKA sebesar 2,16%, PTBA sebesar 1,62% TKIM sebesar 8,80%, dan TPIA sebesar 3,30%. Expected return yang didapatkan investor dari portofolio optimal yang terbentuk adalah sebesar 0,0351 atau 3,51%. Risiko portofolio yang ditanggung oleh investor atas investasi dari portofolio saham optimal tersebut adalah 0,0066 atau 0,66%.
Financial Literature to Sustainbility Micro Business in Gowa Regency Serly Serly; Anwar Anwar; Nurman Nurman
PINISI Discretion Review Volume 6, Issue 1, September 2022
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/pdr.v6i1.37047

Abstract

This research is a qualitative research that aims to find out how the level of financial literacy on the sustainability of Micro Enterprises in Gowa Regency. The sample in this study consisted of 5 informants of micro business actors. Techniques for analyzing research data using the help of ATLAS.ti 9. The results of the analysis show that micro-enterprises are classified as not literate, so the financial literacy of micro-enterprises is still lacking. It can be concluded that micro-enterprises have no potential for business sustainability. 
Pengaruh pengalaman kerja terhadap kinerja pegawai Irawati Irawati; Anwar Anwar; Zainal Ruma; Muh. Ikhwan Maulana Haeruddin; Tenri S.P Dipoatmodjo
JURNAL MANAJEMEN Vol 14, No 4 (2022): Desember
Publisher : Faculty of Economics and Business Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jmmn.v14i4.11560

Abstract

Penelitian ini bertujuan untuk mengetahui pengaruh Pengalaman Kerja berpengaruh signifikan terhadap Kinerja Pegawai pada Kantor Satpol PP Kabupaten Barru. Penelitian ini merupakan penelitin kuantitatif, merupakan penelitian populasi. Subjek penelitian ini adalah karywan di Kantor Pegawai Satpol PP Kabupaten Barru dengan jumlah 37 orang. Pengumpulan data menggunakan kuisioner yang telah di uji validitas dan reliabilitasnya dengan analisis data dilakukan dengan menggunaan analisis regresi linear berganda yang menggunakan dua metode yaitu uji signifikan dengan menggunakan bantuan olah data Statistical Product and Service Solution (SPSS). Hasil penelitian ini menunjukkan bahwa Pengalaman kerja mempunyai pengaruh pengalaman kerja terhadap kinerja pegawai pada kantor Satpol PP kabupaten Barru, hal ini menunjukkan bahwa semakin baik pengalaman kerja maka semakin baik pula kinerja pegawai pada kanttor Satpol PP Kabupaten Barru, variabel pengalaman kerja terhadap kinerja pegawai pada variabel pengalaman kerja yang menunjukan nilai tertinggi terdapat pada indikator tingkat pengatahuan dan keterampilan, hal tersebut dilihat dari sebagian besar pegawai yang mampu untuk saling menghargai sesama pegawai. Sedangkan pada variabel kinerja pegawai yang menunjukan nilai tertinggi terdapat pada indikator kuantitas dan kualitas.
PENGARUH KETERAMPILAN, PENGETAHUAN DAN KEMAMPUAN SDM TERHADAP KINERJA KARYAWAN AGROINDUSTRI DANGKE DI KELURAHAN MATARAN KECAMATAN ANGGERAJA Anwar Anwar; Aulia Nurul Izmi; Agung Widhi Kurniawan
SIBATIK JOURNAL: Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, dan Pendidikan Vol. 2 No. 2 (2023): January
Publisher : Lafadz Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/sibatik.v2i2.534

Abstract

This objective of this research to determine the influence of skills, knowledge and human resources capabilities on the performance of dangke agro-industrial employees in the materi Village. In addition, this application can also be used to improve computer performance. The sample in this study using saturated sample techniques with the number of 30 respondents.This study was conducted using multiple lienar regression analysis. The results showed that there was a positive and significant influence on the overall ability, knowledge and ability of human resources on employee performance with a presentation of 91.1%. This shows the meaning that the dependent variable (employee performance) can be interpreted by the ability, knowledge and ability of human resources by 91.1%, while 8.9% (100% - 91.1%) is expressed by the cause and other factors that are under the variable ability, knowledge and ability of human resources studied. Such as aspects of salary or salary allowances (bonuses) required, work motivation to discipline individual employees in carrying out work in the agro-industry dangke Mataran Village.
Analisis Portofolio Optimal Dengan Model Markowitz pada Perusahaan Sektor Basic Materiasl di BEI Syarif Hidayatullah; Zainal Ruma; Anwar Anwar
Jurnal SEKURITAS (Saham, Ekonomi, Keuangan dan Investasi) Vol 6, No 2 (2023): Jurnal SEKURITAS
Publisher : Prodi Manajemen Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk mengatahui pembentukan portofolio optimal dengan menggunakan model Markowitz pada saham sektor basic materials di Bursa Efek Indonesia. Populasi dalam penelitian ini adalah seluruh saham sektor basic materials berdasarkan pembagian IDX IC di Bursa Efek Indonesia periode April 2021 – Maret 2022 yaitu sebanyak 93 saham, sedangkan yang menjadi sampel adalah 71 saham. Analisi data dilakukan dengan tahapan model Markowitz yang dimulai dengan mengupulkan data harga saham per hari selama periode penelitian, menghitung return realisasi, expected return, varian, standar deviasi, kovarian, korelasi, sampai mendapatkan portofolio optimal dengan risiko dan expected returnnya. Hasil penelitian menunjukkan bahwa, pembentukan portofolio optimal dengan model Markowitz pada perusahaan sektor basic materials periode April 2021-Maret 2022 didapatkan ada 35 saham yang masuk dalam portofolio optimal dengan expected return 0,118% dan risiko 0,56%
Analisis Portofolio Optimal Dengan Model Markowitz pada Perusahaan Sektor Basic Materiasl di BEI Syarif Hidayatullah; Zainal Ruma; Anwar Anwar
Jurnal SEKURITAS (Saham, Ekonomi, Keuangan dan Investasi) Vol 6, No 2 (2023): Jurnal SEKURITAS
Publisher : Prodi Manajemen Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/skt.v6i2.24085

Abstract

Penelitian ini bertujuan untuk mengatahui pembentukan portofolio optimal dengan menggunakan model Markowitz pada saham sektor basic materials di Bursa Efek Indonesia. Populasi dalam penelitian ini adalah seluruh saham sektor basic materials berdasarkan pembagian IDX IC di Bursa Efek Indonesia periode April 2021 – Maret 2022 yaitu sebanyak 93 saham, sedangkan yang menjadi sampel adalah 71 saham. Analisi data dilakukan dengan tahapan model Markowitz yang dimulai dengan mengupulkan data harga saham per hari selama periode penelitian, menghitung return realisasi, expected return, varian, standar deviasi, kovarian, korelasi, sampai mendapatkan portofolio optimal dengan risiko dan expected returnnya. Hasil penelitian menunjukkan bahwa, pembentukan portofolio optimal dengan model Markowitz pada perusahaan sektor basic materials periode April 2021-Maret 2022 didapatkan ada 35 saham yang masuk dalam portofolio optimal dengan expected return 0,118% dan risiko 0,56%
Co-Authors Abd. Muis Dilla Agung Widhi Kurniawan Aldi Alwi Amiruddin Tawe Amiruddin Tawe Andi Bintang Maulana A Andi Mustika Andi Mustika Amin Annisa Awaliyah Ridwan Anwar Ramli Aulia Nurul Izmi Basri Bado Burhanuddin Chalid Imran Musa Chalid Imran Musa Dwi Anugerah Lestari Musa Hardianti Hardianti Hety Budianty Hety Budiyanti Inanna Irawati Irawati M. Ikhwan Maulana Haeruddin Muhammad Idris Muhammad Syafri Muis Dilla Musfirah Mustika Amin Nur Rahma Rusdi Nurjannah Nurman Nurman Rahim, Abd Riska Yuniarti Romansyah Sahabuddin Serly Serly Siti Hasbiah Sitti Hasbiah sulistiawaty sulis Sun Dewi Putri Syarif Hidayatullah Tenri Sayu Puspitaningsih Dipoatmodjo Trisno Setiawan Usman Usman Wilda Wilda Windi Atriani Yunika Priscilla Zainal Ruma