Search results for: Ridho Al-Hamdi

Authors: Alhamdi Alfi Fajri

Abstract:

The purpose of this study is to analyze and to give empirical proof about the effect of fair value implementation on financial asset against information asymmetry in Indonesia’s banking sector. This research tested the effect of fair value implementation on financial asset based on Statement of Financial Accounting Standard (PSAK) No. 55 and the fair value reliability measurement based on PSAK No. 60 against level of information asymmetry. The scope of research is Indonesia’s banking sector. The test’s result shows that the use of fair value based on PSAK No. 55 is significantly associated with information asymmetry. This positive relation is higher than the amortized cost implementation on financial asset. In addition, the fair value hierarchy based on PSAK No. 60 is significantly associated with information asymmetry. This research proves that the more reliable measurement of fair value on financial asset, the more observable fair value measurement and reduces level of information asymmetry.

Keywords: fair value, PSAK No. 55, PSAK No. 60, information asymmetry, bank

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Authors: Muhammad Ridho Fakhrin, Leni Sagita Riantini, Yusuf Latief

Abstract:

Based on the 2015-2019 RPJMN data, the realization of toll road infrastructure development in Indonesia experienced a delay of 49% or 904 km of the total plan. One of the major causes of delays in development is caused by institutional factors. The case study taken in this research is the construction of the Trans Sumatra Toll Road (JTTS). The purpose of this research is to identify the institutional forms, functions, roles, duties, and responsibilities of each stakeholder and the risks that occur in the Trans Sumatra Toll Road Infrastructure Development. Risk analysis is implemented on functions, roles, duties, responsibilities of each existing stakeholder and is carried out at the Funding Stage, Technical Planning Stage, and Construction Implementation Stage in JTTS. This research is conducted by collecting data through a questionnaire survey, then processed using statistical methods, such as homogeneity, data adequacy, validity, and reliability test, continued with risk assessment based on a risk matrix. The results of this study are the evaluation and development of institutional functions in risk-based JTTS development can improve time performance and minimize delays in the construction process.

Keywords: institutional, risk management, time performance, toll road

Procedia PDF Downloads 163

Authors: Ridho Al-Hamdi, Sakir, Tanto Lailam

Abstract:

During the democratic period of 1999-present, Indonesia has consistently applied a List Proportional Representation (List PR) system in the parliamentary election. Between 1999 and 2004, it adopted a closed-list proportional representation (CLPR) system. In the meantime, it employed open-list proportional representation (OLPR) system from 2009 to 2019. Recently, some parties intended to propose the application of CLPR while others are still consistent in adopting OLPR. An unfinished debate is taking place. Thus, this article aims to evaluate the application of CLPR in Indonesia and, in turn, analyze its compatibility in contemporary parliamentary election system. From a methodological standpoint, it is qualitative research by applying a case study approach. Data-gathering relies on field data, mainly focus group discussion (FGD) and in-depth interviews with political parties, electoral management bodies (EMBs), NGO activists, and scholars spread in six provinces and nine regencies/cities across the country. Using SWOT analysis and the compatibility of CLPR and embedded democracy framework, the finding demonstrates that CLPR is no longer relevant for contemporary Indonesian elections. This paper recommends OLPR by considering that CLPR has numerous weaknesses and threats that can jeopardize embedded democracy. More importantly, CLPR can remove inclusive suffrage significantly.

Keywords: closed-list proportional representation, embedded democracy, Indonesia, parliamentary election

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Authors: Sarono, Hamim Zaky Hadibasyir, dan Ridho Kurniawan

Abstract:

Estimation of paddy production is one of the areas that can be examined using the techniques of remote sensing and geographic information systems (GIS) in the field of agriculture. The purpose of this research is to know the amount of the paddy production estimation and how remote sensing and geographic information systems (GIS) are able to perform analysis of paddy production estimation in Tegalallang and Payangan Sub district, Bali Province, Indonesia. The method used is the method of land suitability. This method associates a physical parameters which are to be embodied in the smallest unit of a mapping that represents a mapping unit in a particular field and connecting with its field productivity. Analysis of estimated production using standard land suitability from FAO using matching technique. The parameters used to create the land unit is slope (FAO), climate classification (Oldeman), landform (Prapto Suharsono), and soil type. Land use map consist of paddy and non paddy field information obtained from Geo-eye 1 imagery using visual interpretation technique. Landsat image of the Data used for the interpretation of the landform, the classification of the slopes obtained from high point identification with method of interpolation spline, whereas climate data, soil, use secondary data originating from institutions-related institutions. The results of this research indicate Tegallalang and Payangan Districts in known wetland suitability consists of S1 (very suitable) covering an area of 2884,7 ha with the productivity of 5 tons/ha and S2 (suitable) covering an area of 482,9 ha with the productivity of 3 tons/ha. The sum of paddy production estimation as a results in both districts are 31.744, 3 tons in one year.

Keywords: production estimation, paddy, remote sensing, geography information system, land suitability

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Authors: Ridho Widyantama Putra, Endang Wiwik Dyah Hastuti

Abstract:

The study area is located in Lahat Regency, South Sumatra and is part of a 500 m – 2000 m elevated perbukitan barisan zone controlled by the main fault of Sumatra (Semangko Fault), administratively located on S4.08197 - E103.01403 and S4.16786 - E103.07700, the product of Semangko Fault in the form of normal fault flight trending north-southeast, composed of lithologic is a pyroclastic rock, volcanic rock and plutonic rock intrusion. On the Manna and Enggano sheets of volcanic quartenary products are located along perbukitan barisan zone. Petrology types of pyroclastic rocks encountered in the form of welded tuff, tuff lapilli, agglomerate, pyroclastic sandstone, pyroclastic claystone, and lava. Some pyroclastic material containing sulfide minerals (pyrite), the type of sedimentation flow with different grain size from ash to lapilli. The present of tuff lapilli covers almost 50% of the total research area, through observation petrography encountered minerals in the form of glass, quartz, palgioklas, and biotite. Lava in this area has been altered characterized by the presence of minerals such as chlorite and secondary biotite, this change is caused by the structure that develops in the hilly zone and is proved by the presence of secondary structures in the form of stocky and normal faults as well as the primary structure of columnar joint, From medial facies to distal facies, the division of facies is divided based on geomorphological observations and dominant types of lithology.

Keywords: tuff lapili, pyroclastic, mineral, petrography, volcanic, lava

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Authors: Mustafa Alhamdi

Abstract:

Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

Procedia PDF Downloads 150