bluuebunny/crossref_metadata_2025_split huggingface dataset:
The determinant of agriculture development in Indonesia
Authors: Anwar Aminuddin 
Published: February 2023

Abstract
Purpose – This study aims to analyze the determinants of agriculture in Indonesia, represented by the variables of labor, land, fertilizer, and rainfall from 1991 to 2018.
Methods – This study uses the time series method by utilizing aggregate data at the national level in Indonesia. The method used in this research is the cointegration and error correction model (ECM).
Findings – The results of this study indicate that in the short term, the factors that determine agricultural conditions in Indonesia are the amount of land and the use of fertilizers which show a positive impact. Meanwhile, the long-term results show that all variables, namely labor, land, fertilizer, and rainfall, impact agricultural conditions in Indonesia. The adjustment in the short-term to long-term process is shown that there is an adjustment for agricultural conditions in Indonesia.
Implication – This study indicates that the policies carried out by the government in the agricultural sector are important for internal aspects, namely labor, land, and fertilizer, and external effects such as climate change so that appropriate policy interventions can increase agricultural production in Indonesia.
Originality – This research contributes to modeling the determinants of the agricultural sector in Indonesia with the error correction model (ECM).

Abstrak
Tujuan – Penelitian ini bertujuan untuk menganalisis determinan pertanian di Indonesia yang diwakili oleh variabel tenaga kerja, tanah, pupuk, dan curah hujan tahun 1991 sampai dengan tahun 2018.
Metode – Penelitian ini menggunakan metode time series dengan memanfaatkan data agregat tingkat nasional di Indonesia. Metode yang digunakan dalam penelitian ini adalah kointegrasi dan error correction model (ECM).
Temuan – Hasil penelitian ini menunjukkan bahwa dalam jangka pendek faktor yang menentukan kondisi pertanian di Indonesia adalah jumlah lahan dan penggunaan pupuk yang menunjukkan dampak positif. Sementara itu, hasil jangka panjang menunjukkan bahwa semua variabel yaitu tenaga kerja, tanah, pupuk, dan curah hujan mempengaruhi kondisi pertanian di Indonesia. Penyesuaian dalam proses jangka pendek ke jangka panjang menunjukkan adanya penyesuaian kondisi pertanian di Indonesia.
Implikasi – Penelitian ini menunjukkan bahwa kebijakan yang dilakukan pemerintah di bidang pertanian penting untuk aspek internal yaitu tenaga kerja, lahan, dan pupuk, serta terhadap dampak eksternal seperti perubahan iklim sehingga intervensi kebijakan yang tepat dapat meningkatkan produksi pertanian di Indonesia.
Orisinalitas – Penelitian ini berkontribusi dalam memodelkan determinan sektor pertanian di Indonesia dengan model error correction model (ECM).
Peran aspek pendidikan bagi pertumbuhan ekonomi: Analisis kelompok usia pendidikan
Authors: Mifrahi Mustika Noor , Hanif Nur Rahmat  
Published: February 2023

Purpose – This study reexamines the debate about the possible influence of human capital on economic growth in Indonesia by using an analysis per educational age group.
Methods – This study uses the Autoregressive Distributed Lag (ARDL) model approach using data from 1970 – 2019.
Findings – Empirical results show that short-term primary school enrollment and higher education positively affect economic growth. Meanwhile, in secondary school enrollment, the positive effect only occurs in short-term conditions. In addition, higher education has the highest impact among the three variables.
Implication – The results of this study emphasize the importance of all aspects of education as a representation of human resources, especially using different age specifications.
Originality – This study contributes to modeling the effect of human capital per educational age group using the ARDL method.

Abstrak
Tujuan – Penelitian ini menguji kembali perdebatan mengenai adanya kemungkinan pengaruh modal manusia terhadap pertumbuhan ekonomi di Indonesia dengan menggunakan analisis per kelompok usia Pendidikan.
Metode – Penelitian ini menggunakan pendekatan model Autoregressive Distributed Lag (ARDL) menggunakan data dari tahun 1970 – 2019.
Temuan – Hasil empiris menunjukkan bahwa pada jangka pendek pendaftaran sekolah dasar, dan Pendidikan tinggi berpengaruh posifit terhadap pertumbuhan ekonomi. Sedangkan pada pendaftaran sekolah menengah, pengaruh positif hanya terjadi pada kondisi jangka pendek. Selain itu, dampak pendidikan tinggi memberikan dampak tertinggi di antara ketiga variabel tersebut.
Implikasi – Hasil studi ini menekankan pentingnya semua aspek pendidikan sebagai representasi sumber daya manusia terutama menggunakan spesifikasi usia yang berbeda.
Orisinalitas – Penelitian ini berkontribusi dalam memodelkan pengaruh modal manusia per kelompok usia pendidikan dengan menggunakan metode ARDL.
Teaching Education Program and Teaching Experience of Two EFL Teachers: A narrative Inquiry of English Teachers’ Identity
Authors: Nainggolan Bernard Richard 
Published: February 2023

<p>Previous personal beliefs about teaching, impressions with good teachers, and memories of good teachers might have contributed to motivating students to enroll in the teacher education program. The shape of teacher identity is influenced by students before teaching education programs. However, a question arises on how the teachers’ identity is formed during the teaching education program and how its shift remains to change in the context of teaching at school. My narratives and Puji's were used as the data to answer the research question. This study used the narrative inquiry, which used my narratives and my colleague’s being the primary sources of data. The theories selected, used as the framework, were the ‘Situated Learning’ and the ‘image-text teacher identity. Coding was done to narratives and fundamental concepts were generated. The fundamental concepts of the analyzed data are (1) teacher education program vs teaching experiences, (2) the importance of senior guidance in the learning community, (3) teacher relations as a weapon, (4) affects of a new identity. The findings also show what makes the teacher identity formation different both in the teacher education program and in teaching experience. My study also provides the recommendation for the next research and implications for teacher identity formation.</p><p> </p>
Heterogeneity of Students’ Mathematical Critical Thinking Ability Re-viewed from Education Levels: A Meta-Analysis
Authors: Suparman Suparman , Juandi Dadang , Martadiputra Bambang Avip Priatna 
Published: February 2023

<p>Study of meta-analysis by selecting the random effect model was employed to investigate and examine students’ education level predicted as one of the causative factors of the heterogeneity of mathematical critical thinking ability (MCTA) through problem-based learning (PBL). Search engines such as Google Scholar and Semantic Scholar were used to find thirty journal or proceeding articles published in 2011 – 2021 and indexed by Scopus, Sinta, and Web of Science. The Z and Q Cochrane test were used to analyze the data. The results revealed that education level was one of the significant factors causing the heterogeneity of students’ MCTA through PBL. Therefore, mathematics teachers or lecturers should minimize the gap by improving the learning quality through PBL in education level in which students’ MCTA was still low. </p><p> </p>
Analisis Tekstual Dalam Konstruksi Wacana Berita Wacana Jokowi 3 Periode, Klaim Demokrasi dan Gejala Otoritarianisme di Kompas.com Dalam Perspektif Analisis Wacana Kritis Norman Fairclough
Authors: Amalia Husnil , Manaf Ngusman Abdul 
Published: February 2023

Penelitian ini bertujuan untuk menemukan wacana kritis dalam Rubrik <em>Wacana Jokowi 3 Periode, Klaim Demokrasi dan Gejala Otoritarianisme</em> di Kompas.Com dari analisis wacana kritis Norman Fairclough. Jenis penelitian ini deskriptif-kualitatif, dengan pendekatan teori tindak tutur. Sumber data penelitian ini adalah Rubrik Rubrik <em>Wacana Jokowi 3 Periode, Klaim Demokrasi dan Gejala Otoritarianisme</em> di Kompas.Com dan data penelitian ini adalah tuturan di dalamnya mengandung beberapa jenis wacana kritis Teknik pengumpulan data dalam penelitian ini menggunakan teknik dokumentasi. Data yang akan diteliti sudah didokumentasikan sebelumnya, hal ini bertujuan untuk membantu peneliti dalam memperoleh data yang diinginkan. Pengambilan data dalam penelitian ini dilakukan dengan cara pencatatan tuturan bahasa berupa penggalan kalimat yang mempunyai konteks utuh. Data diidentifikasi berdasarkan jenis wacana data dikumpulkan dan diurutkan secara sistematis berdasarkan format data identifikasi dan klasifikasi yang telah ditentukan. Berdasarkan hasil analisis data, ditemukan hasil penelitian, berdasarkan representasi, berhubungan dengan, bagaimana seseorang, kelompok, peristiwa, dan kegiatan ditampilkan pada teks. Unsur relasi disini dimaksudkan untuk menemukan pola hubungan pada partisipan teks berita. Analisis identitas dimaksudkan untuk melihat bagaimana wartawan menempatkan dirinya ke dalam teks berita.<span style="color: #555555; font-family: 'Helvetica Neue', Helvetica, Arial, sans-serif; font-size: 15.4px; text-align: justify; background-color: #fafafa;">ngusman_abdul_manaf@gmail.com</span>
Analisis Indeks Aiken untuk Mengetahui Validitas Isi Instrumen Asesmen Kompetensi Minimum Berbasis Konteks Sains Kimia
Authors: An Nabil Naimina Restu , Wulandari Ika , Yamtinah Sri , Ariani Sri Retno Dwi , Ulfa Maria 
Published: February 2023

<p>Penelitian ini merupakan penelitian pengembangan instrumen asesmen kompetensi minimum literasi numerasi dan membaca bentuk pilihan ganda kompleks berbasis sains kimia. Penelitian ini bertujuan untuk menganalisis validitas isi instrumen asesmen kompetensi minimum literasi numerasi dan membaca berdasarkan indeks validitas Aiken sehingga instrumen dapat mengukur apa yang seharusnya diukur. Metode penelitian yang digunakan adalah metode deskriptif kuantitatif berdasarkan hasil validitas isi yang dihitung dengan formula Aiken. Data validitas isi diperoleh dari 8 orang ahli yaitu guru kimia SMA di Surakarta melalui focus group discussion (FGD). Uji validasi isi dalam penelitian ini menggunakan empat kriteria penilaian, yaitu tidak relevan tidak relevan (TR), kurang relevan (KR), cukup relevan (CR), dan relevan (R). Instrumen asesmen kompetensi minimum literasi numerasi menghasilkan 18 item soal valid dengan indeks Aiken ≥ 0,75 dan 2 item soal tidak valid dengan indeks Aiken &lt;0,75. Sedangkan instrumen asesmen kompetensi minimum literasi membaca menghasilkan 20 item valid dengan indeks Aiken ≥ 0,75.</p>
Trajectory optimization of high-speed robotic positioning with suppressed motion jerk via improved chicken swarm algorithm
Authors: Li Yankun , Lu Yuyang , Li Dongya , Li Rui , Xu Chonghai , Gao Xiaozhi , Liu Yu 
Published: February 2023

Abstract
To address the problems of premature convergence and low solution accuracy of the basic swarm optimization algorithm an improved chicken swarm algorithm based on parallel strategy and dynamic constraints (PDCSO) is proposed for the rooster update method with a parallel strategy while introducing X-best guidance and Levy flight step; dynamic constraints are given for the rooster followed by the hen, and the optimal rooster position is introduced, which improves the convergence accuracy while avoiding falling into local optimum. The simulation experiments on 18 classical test functions show that the PDCSO algorithm outperforms other comparative algorithms in terms of convergence speed, solution accuracy and solution stability. In addition, PDCSO is applied to robotic arm trajectory optimization by fitting the joint trajectory with 5 times B-sample curve, and after algorithm optimization and simulation verification in ADAMS, it is proved that PDCSO can effectively reduce the running time and motion shock of robotic arm and improve the execution efficiency of robotic arm.
Reversible Anisotropic Wet Adhesion Enabled by Rigid Amphiphiles
Authors: Wu Tongyue , Gao Shuitao , Zhao Hongxin , Ma Cheng , Jiang Lingxiang , huang jianbin , Yan Yun 
Published: February 2023

Abstract
Wet adhesives such as glues are extensively used in everyday life and various engineering processes to integrate two different objects together. Usually a firm adhesion is desired in all applications, but the strong adhesion often brings up difficulties in revising an undesired adhesion or reusing the adhered objects. To solve this dilemma, we report an anisotropic wet adhesive that combine the advantages of strong adhesion and easy deadhesion together by incorporating a rigid amphiphile glycyrrhizic acid (GA) and a flexible polyelectrolyte poly (diallyldimethylammonium) chloride (PDDA) into the glue. The rigidity of the GA molecules allows formation of oriented hydrophobic GA bilayers on smooth surfaces under the mild pressure required for adhesion. The van der Waals forces between the hydrophobic chains are much weaker than hydrogen bonds, coordination, and electrostatic forces occurred between the glue and the adhered substrate. As a result, the shear force along the hydrophobic chain, which is vertical to the surface, is 6 ~ 13 times smaller than that along the surface. This immediately generates an anisotropic adhesion, which makes it possible to revise or detach an undesired adhesion by applying a gentle pulling force vertical to the surface. Reversible adhesion is possible by pressing back the detached part, and the undesired adhesives can be facilely cleaned with water. As the GA molecule is replaced by other rigid ones, similar anisotropic adhesion is observed. We envision the rigid molecules facilitated anisotropic wet glue would open a new paradigm in developing smart wet adhesives for building sustainable societies.
Remote Sensing and GIS-based landslide susceptibility mapping using bivariate statistical approach of Chhukha District
Authors: Gyeltshen Sangay , Dem Phub , Sharma Vasker , Adhikari Rabindra 
Published: February 2023

Abstract
Chhukha, a southern district of Bhutan remains susceptible to landslides due to excessive temporal rainfall variability and land instability aggravated by anthropogenic factors. This has led to multiple fatalities, substantial financial losses, and damages to infrastructure, farmland, and transportation networks. This study developed the district scale Landslide susceptibility index (LSI) by a bivariate statistical approach called Probabilistic Frequency Ratio (FR) and logistic regression (LR) with the help of a geospatial technology system. A total of 236 historical landslide inventories were identified through field deputation and google earth interpretation with the rationing of 70:30. 70% of the existing landslides were used to train the models, while the remaining 30% of them were used for model validation. The FR model outperformed the LR model with an accuracy of 88.3% and 83.2% respectively. The AUC model verification shows satisfactory agreement to predict landslide susceptibility at the district scale in the Himalayan region. Both models indicated that the central and northern parts of the district account for the least susceptibility, while the southern portion of the Chhukha district accounts for the highest susceptibility to landslides. These authentic findings of the research enable the local government and other decision-making bodies in developing policies, implement innovative measures, and disseminate awareness and preparedness for the consequences of landslide disasters.
SVC-Net: A spatially vascular connectivity network for deep learning construction of microcapillary angiography from single-scan-volumetric OCT
Authors: Le David , Son Taeyoon , Kim Tae-Hoon , Adejumo Tobiloba , Abtahi Mansour , Ahmed Shaiban , Rossi Alfa , Ebrahimi Behrouz , Dadzie Albert , Yao Xincheng 
Published: February 2023

Abstract
As one modality extension of optical coherence tomography (OCT), OCT angiography (OCTA) provides unparalleled capability for depth-resolved visualization of retinal vasculature at the microcapillary level resolution. For OCTA image construction, repeated OCT scans from one location are required for temporally vascular connectivity (TVC), i.e., OCT signal variance among sequential images, to identify blood vessels with active blood flow. The requirement for multi-scan-volumetric OCT can reduce OCTA imaging speed, which will induce eye movements, and limit the image field-of-view. In principle, the blood flow should also affect the spatially vascular connectivity (SVC), i.e., reflectance brightness profile along the vessel direction, in a single-scan-volumetric OCT. In other words, the SVC in single-scan-volumetric OCT might be equivalent to the TVC in multi-scan-volumetric OCT for high fidelity OCTA construction. In this article, we report an SVC network (SVC-Net) for deep learning OCTA construction from single-scan-volumetric OCT. The effect of SVC for deep learning OCTA was evaluated by SVC-based speckle variance calculation, revealing three adjacent B-scans has the optimal performance. We further compare the effects of SVC with three adjacent B-scans and a single B-scan inputs into SVC-Net. The structural-similarity index measure (SSIM) loss function was selected to optimize deep learning contrast enhancement of microstructures, such as microcapillaries, in OCT. This was verified by comparative analysis of the SVC-Net performances with SSIM and mean-squared-error (MSE) loss functions. The combination of SVC involvement and SSIM loss function enabled microcapillary resolution OCTA construction from single-scan-volumetric OCT. The performance of the SVC-Net was verified with OCT datasets from both superficial and deep vascular plexus in mouse and human eyes.
When the Minister speaks: Framings of the vaccination hesitant and impact on the propensity to vaccinate girls for HPV
Authors: Compagni Amelia , Fattore Giovanni , Paraggio Diana 
Published: February 2023

Abstract

Vaccination hesitancy is a complex phenomenon influenced by numerous factors, including the communicative messages to which individuals are exposed. Policy-makers, through public communication, might contribute to shape this behaviour. In the study we report the results of an experiment in which respondents were randomly exposed to three different messages about the vaccination against the human papilloma virus (HPV) of girls. The messages were derived from the public statements (2015–2017) of the Italian Minister of Health and contained different frames of the vaccination hesitant (misinformed, antiscientific, or socially dangerous) and correspondingly policy solutions to counteract vaccination hesitancy (information campaigns, compulsory vaccination or compulsory vaccination and sanctions). Results show how framing the vaccination hesitant as antiscientific or socially dangerous, that in turn supports coercive and sanctioning policies, tends to discourage vaccination. These findings alert us to the importance of designing with great care the communication about vaccinations and avoid counterproductive effects.
Performance Evaluation of State-of-the-Art Texture Feature Extraction Techniques on Medical Imagery Tasks
Authors: KUSI-DUAH SAMUEL , Appiah Obed , Appiahene Peter 
Published: February 2023

Abstract
Interpreting medical images is certainly a complex task which requires extensive knowledge [1]. According to [2]Computer Aided Diagnosis (CAD) serves as a second opinion that will help radiologists in diagnosis and on the other hand Content-based Image Retrieval uses visual content to help users browse, search and retrieve similar medical images from a database based on the user’s interest [3] [4]. The competency of the CBMIR system depends on feature extraction methods [5]. The textural features are very important to determine the content of a medical image. Textural features provide scenic depth, the spatial distribution of tonal variation, and surface orientation [6]. Therefore, this study seeks to compare and evaluate some of the hand-crafted texture feature extraction techniques in CBMIR. This is to help those concerned in enhancing CBIR systems to make informed decisions concerning the selection of the best textural feature extraction techniques.
Since there is no clear indication of which of the various texture feature extraction techniques is best suited for a given performance metric when considering which of the techniques to choose for a particular study in CBMIR systems. The objective of this work, therefore, is to comparatively evaluate the performance of the following texture feature extraction techniques; Local Binary Pattern (LBP), Gabor Filter, Gray-Level Co-occurrence Matrix (GLCM), Haralick Descriptor, Features from Accelerated Segment Test (FAST) and Features from Accelerated Segment Test and Binary Robust Independent Elementary Features (FAST &BRIEF) using the metrics; precision, recall, f1-score, mean squared error (MSE), accuracy and time. These techniques are coupled with specific similarity measure to obtain results.
The results showed that LBP, Haralick Descriptor, FAST, and GLCM had the best results in terms of (Precision and Accuracy), Time, F1-Score, and Recall respectively. LBP had 82.05% and 88.23% scores for precision and accuracy respectively. The following scores represent the performance of the Haralick descriptor, FAST, and GLCM models respectively; 0.88s, 38.7%, and 44.82%. These test scores are obtained from datasets ranging from 1k-10.5k.
Aside from LBP outperforming the other 5 models mentioned, it still outperformed the following proposed models ' [7]’, ‘Tamura texture feature and wavelet transform combined with Hausdorff distance - [8]’, ‘ [9]’ in terms of (precision, accuracy, and recall) and (precision and recall) respectively and probably f1-score (since f1-score is the weighted average of precision and recall). It is believed that an ensemble of LBP, Haralick descriptors, and Support Vector Machine (SVM) can represent a robust system for both medical image retrieval and classification.
Geomagnetically Induced Currents over Kazakhstan during Large Geomagnetic Storms
Authors: Mukasheva Saule , Andreyev Alexey , Vassilyev Ivan , Sokolova Olga 
Published: February 2023

Abstract
Extreme solar events, such as flares accompanied by the ejection of a powerful magnetic cloud, cause perturbation of the Earth's magnetic field and form fluctuating currents in the ionosphere and magnetosphere. One of the negative consequences of extreme solar phenomena for technological systems is the appearance of geomagnetically induced currents in conducting ground systems, power transmission lines and pipelines. Many countries of the world already have reliable ways to predict the appearance of geomagnetic-induced currents in the electric power system. Kazakhstan, which has extensive power transmission lines and pipelines, needs its own strategy to predict and mitigate the effects of geomagnetic-induced currents. This paper shows the formation of significant geomagnetically induced currents in the region of Kazakhstan during extreme helio-geoeffective events. The first results of modeling the geoelectric field for this region are presented. The description of measurements of telluric current in urban conditions in Almaty is given [43.25°N; 76.92°E].