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All Journal Jurnal Pendidikan Indonesia Jurnal Manajemen TSARWATICA (Islamic Economic, Accounting, and Management Journal)
Riznaldi Akbar, Riznaldi
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Religion Economics, Econometrics & Finance Education

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Evaluating The Efficiency Of Indonesia’s Secondary School Education Akbar, Riznaldi
JPI (Jurnal Pendidikan Indonesia) Vol 7, No 1 (2018)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (323.806 KB) | DOI: 10.23887/jpi-undiksha.v7i1.13163

Abstract

This study employs a Data Envelopment Analysis (DEA) to investigate secondary school efficiency and Stochastic Frontier Analysis (SFA) to examine determinants that affect average secondary school student score in Indonesia. Using the DEA, this study measures the efficiency of the region with regards to the average student score using various input indicators including teacher-to-student ratio, number of teachers holding the first-degree qualification, average secondary school expense, average duration to school and average distance to school, while output variable is the average student score for 33 regions in Indonesia. The findings suggest the average technical efficiency of secondary school in the region is 89 percent with the most efficient regions are Sumatera Utara, Kepulauan Bangka Belitung, DKI Jakarta, Jawa Timur, Bali, Sulawesi Barat, Maluku, Maluku Utara and Papua Barat. With the SFA, this study identifies factors that significantly affect the average student score in the region. The results suggest that the higher ratio of teacher-to-student and higher numbers of the teacher with the first-degree qualification significantly affect the average student score in the region. However, there is no evidence that average secondary school expense and school proximity (average duration and distance to school) significantly affect secondary school efficiency.
UNDERSTANDING INVESTORS’ BEHAVIOR DURING STOCK PRICE MANIPULATION: A CASE OF INDONESIA’S STOCK MARKET Akbar, Riznaldi
Jurnal Manajemen Vol 20, No 1 (2016): February 2016
Publisher : Fakultas Ekonomi dan Bisnis, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (640.197 KB) | DOI: 10.24912/jm.v20i1.70

Abstract

Penelitian ini mencoba untuk mencari pola tekstual yang berkaitan dengan perilaku investor dan sentimen selama manipulasi harga saham di Bursa Efek Indonesia. Kami mengusulkan analisis text mining untuk menunjukkan proses penggalian informasi dari berita dan media rilis Tweeter selama periode 2000 sampai 2014. Kami mengambil tiga sampel perusahaan dari PT AGIS Tbk (TMPI), PT Garda Tujuh Buana Tbk (GTBO) dan PT Bumi Resources Tbk (BUMI) yang telah ditunjukkan mengalami manipulasi harga saham. Perusahaan-perusahaan ini mengalami harga saham apresiasi abnormal dan diikuti dengan penurunan tajam dari sekitar 90 persen dalam waktu singkat. Informasi yang diekstrak dari Tweeter dan analisis sentimen memberikan bukti bahwa berita dan media rilis cenderung menghasilkan umum istilah kunci negatif seperti "terjun", "drop", dan "jatuh"; serta istilah yang terkait dengan laporan laba rugi seperti "kehilangan", "keuntungan", "bersih", "penjualan" dan "pendapatan" .Ini menunjukkan bahwa sebagian besar investor akan memiliki bias negatif dan menderita lebih ketika harga saham mengalami signifikan menurun. Hal ini juga mengungkapkan bahwa investor lebih cupet pada laporan laba rugi daripada menganalisis gambaran besar dari penilaian dasar perusahaan secara keseluruhan. Dengan demikian kita berpendapat bahwa basis pengetahuan ini dan istilah kunci dapat digunakan untuk mencerminkan karakteristik umum dari perilaku investor selama manipulasi harga saham di pasar saham Indonesia.This study attempts to search textual patterns that are associated with investor behavior and sentiment during stock price manipulation in Indonesia’s Stock Market. We propose text mining analysis to demonstrate the process of extracting information from news and media release of Tweeter over the period of 2000 to 2014. We took three sample firms of PT AGIS Tbk (TMPI), PT Garda Tujuh Buana Tbk (GTBO) and PT Bumi Resources Tbk (BUMI) that have been indicated experiencing stock price manipulation. These firms experienced an abnormal stock price appreciation and followed with a sharp decline of about 90 per cent within short period of time. The extracted information from Tweeter and sentiment analysis provide evidence that news and media releases tend to yield common negative key terms such as “plunge”, “drop”, and “fall”; as well as terms related to income statements such as “loss”, “profit”, “net”, “sales” and “revenue”.It shows us that most investors would have negative bias and suffer more when the stock price experienced a significant decline. It also reveals that investors are more short-sighted on the profit and loss statements rather than analyzing the big picture of corporate fundamental valuation as a whole. We thus argue that these knowledge bases and key terms could be used to reflect common characteristics of investor behavior during stock price manipulation in the Indonesia’s stock market.
SCIENTOMETRIC ANALYSIS OF BIG DATA ANALYTIC AND HALAL SUPPLY CHAIN MANAGEMENT Kuncorosidi, Kuncorosidi; Nazier, Daeng M.; Akbar, Riznaldi; Prabowo, Eddy
TSARWATICA (Islamic Economic, Accounting, and Management Journal) Vol 6 No 1 (2024)
Publisher : STIESA Press

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Abstract

This study aims to conduct a scientometric analysis of "Analitika Big Data in Halal Supply Chain Management" between 2018 and 2024 In this study, keyword analysis and citation analysis were carried out using Dimensions and VOS viewer software, as well as identifying the most commonly used keywords. In addition, this study also conducted a co-author analysis, co-citation analysis, and analysis of countries and organizations involved in the study. The keyword analysis results show that the most discussed topics in this field are information management, the Internet of Things (IoT), sustainable development, and competition. The countries most active in Analitika Big Data in supply chain management are Malaysia, The United Kingdom, India, Italy, China, the United States, Turkey, Saudi Arabia, Egypt, Germany, New Zealand, Australia, and Bangladesh. This study recommends a thorough Scientometrics Analysis as a future research direction. In addition, the importance of the application of evolutionary computing and interdisciplinary work in dealing with practical problems related to big data was also identified. This digest provides an overview of the study's objectives, methods, and main findings "Scientometric Analysis of Big Data Analytic in Supply Chain Management. The research provides insight into research trends, country and journal contributions, and recommendations for future research in Analitika Big Data in supply chain management
Evaluating The Efficiency Of Indonesia’s Secondary School Education Akbar, Riznaldi
Jurnal Pendidikan Indonesia Vol 7 No 1 (2018)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (226.631 KB) | DOI: 10.23887/jpi-undiksha.v7i1.13163

Abstract

This study employs a Data Envelopment Analysis (DEA) to investigate secondary school efficiency and Stochastic Frontier Analysis (SFA) to examine determinants that affect average secondary school student score in Indonesia. Using the DEA, this study measures the efficiency of the region with regards to the average student score using various input indicators including teacher-to-student ratio, number of teachers holding the first-degree qualification, average secondary school expense, average duration to school and average distance to school, while output variable is the average student score for 33 regions in Indonesia. The findings suggest the average technical efficiency of secondary school in the region is 89 percent with the most efficient regions are Sumatera Utara, Kepulauan Bangka Belitung, DKI Jakarta, Jawa Timur, Bali, Sulawesi Barat, Maluku, Maluku Utara and Papua Barat. With the SFA, this study identifies factors that significantly affect the average student score in the region. The results suggest that the higher ratio of teacher-to-student and higher numbers of the teacher with the first-degree qualification significantly affect the average student score in the region. However, there is no evidence that average secondary school expense and school proximity (average duration and distance to school) significantly affect secondary school efficiency.
Co-Authors Kuncorosidi, Kuncorosidi Nazier, Daeng M. Prabowo, Eddy