bluuebunny/crossref_metadata_2025_split huggingface dataset:
ДОМАШНЄ ЗАВДАННЯ ЯК МЕХАНІЗМ КОНТРОЛЮ В НАВЧАННІ МАТЕМАТИКИ: СУЧАСНІ ВИМОГИ ДО ОРГАНІЗАЦІЇ ДОМАШНЬОГО ЗАВДАННЯ
Authors: Турка Тетяна , Стьопкін Андрій , Зінченко Ірина 
Published: July 2023

Авторами статті здійснено теоретичний аналіз проблеми організації домашнього завдання на уроці математики. Домашнє завдання вже давно визнано невід’ємною складовою навчального процесу, слугуючи засобом закріплення знань і оцінки розуміння учнями предмета. У цій статті досліджується концепція домашнього завдання, його обсяг і потенційне навантаження, яке воно несе для учнів. Зокрема, досліджується необхідність домашніх завдань у навчанні математики, ідеальний обсяг домашніх завдань, найефективніша форма завдань і час, необхідний для їх виконання. Додатково розглядаються сучасні вимоги до організації домашніх завдань з математики під час дистанційного навчання.
У статті досліджено сучасний стан виконання домашніх завдань у математичній освіті з урахуванням проблем, з якими стикаються учні під час виконання завдань великого обсягу. Відображено питання впливу надмірної кількості домашніх завдань на психічне благополуччя учнів та підкреслена необхідність збалансованого підходу, який сприяє ефективному навчанню, не перевантажуючи учнів. Обговорення також стосується важливості чіткої комунікації та вказівок з боку вчителів, щоб забезпечити відповідність домашніх завдань запланованим результатам навчання.
Крім того, у статті наголошено на сучасних вимогах до організації домашніх завдань у позакласній математичній освіті. Розглянуті інноваційні підходи та методології, що можуть підвищити ефективність домашніх завдань, такі як використання технологій, сприяння спільному навчанню та персоналізація завдань на основі індивідуальних потреб та інтересів учнів. У статті також висвітлюється роль формувального оцінювання в рамках домашнього завдання, що дає змогу педагогам надавати своєчасний зворотний зв’язок і підтримувати прогрес учнів.
Досліджуючи еволюцію організації домашніх завдань у математичній освіті, ця стаття сприяє постійному діалогу щодо вдосконалення педагогічної практики та залучення учнів. Отримані результати підкреслюють важливість досягнення балансу між освітніми перевагами домашнього завдання та потенційним тягарем, який воно може накласти на учнів.
Relationship between English Proficiency and Academic Achievement of Indonesian EFL Postgraduate Students
Authors: Devi Anit Pranita 
Published: July 2023

There is still a debate about using English proficiency in determining one's academic success or access to an opportunity. Hence, research on the correlation of language proficiency and academic achievement is urgently needed. This study attempted to investigate the relationship between Indonesian postgraduate students’ English language proficiency and their academic achievement. To achieve the objective, 54 male and female postgraduate students majoring in English education at a university in Bandung were involved as the sample. Students’ language proficiency was seen from their Test of English as a Foreign Language (TOEFL) scores and their grade point average (GPA) was used to indicate their academic achievement. All data were analyzed through manual computation of Pearson Product-moment correlation. The result revealed that there is a significant positive linear correlation between English language proficiency and academic achievement. This result suggests that as the English proficiency increases, so does academic achievement. The results are expected to provide insight in understanding whether English language proficiency can increase academic success, especially in educational settings where English is the primary medium of instruction.
Faktor-Faktor Determinan Keputusan Pembelian secara Online Produk Fashion
Authors: Pattipeilohy Victor Ringhard , Tousalwa Carla Caroline , Ferdinandus Stanley - 
Published: July 2023

ABSTRACTThe role of social media today greatly influences the lifestyle and activities of its users, one of which is shopping activities that used to be conventional in nature shifting to shopping activities through social media or online shopping activities. These changes must be responded to by online marketers carefully by implementing marketing strategies that involve customers proactively involved in the online marketing process, especially through social media so that they can create purchases.The purpose of this study was to examine the effect of variable trust and risk perception on the decision to purchase fashion products online through social media in Ambon City. The sample of this study was 106 female respondents, with the purposive sampling technique used in this case respondents who had been shopping online through social media. The research instrument used was a questionnaire measured by a Likert scale. The data analysis technique used in this study is multiple regression.The results showed that both the trust and risk perception variables were able to influence or create online purchasing decisions on fashion products on social media such as Facebook carried out by young women in Ambon City.ABSTRAKPeran media social saat ini sangat mempengaruhi gaya hidup dan aktifitas dari para penggunanya, salah satunya adalah aktifitas belanja yang dulunya masih bersifat konvesnional beralih ke aktifitas belanja melalui media social atau aktifitas belanja online. Perubahan ini harus direspon oleh para pemasar online secara cermat dengan cara menerapkan strategi pemasaran yang melibatkan pelanggan secara proaktif terlibat dalam proses pemasaran online terutama melalui media social sehingga dapat menciptakan pembelian. Tujuan penelitian ini adalah untuk menguji pengaruh variabel kepercayaan dan persepsi resiko terhadap keputusan pembelian secara online produk fashion melalui media sosial di Kota Ambon. Sampel penelitian ini adalah berjumlah 106 orang responden remaja puteri, dengan teknik sampel yang digunakan adalah purposive dalam hal ini responden yang pernah belanja secara online melalui media sosial. Instrumen penelitian yang digunakan adalah kuisioner yang diukur dengan skala likert. Teknik analisis data yang digunakan dalam penelitian ini adalah regresi berganda (Multiply regression). Hasil penelitian menunjukan bahwa baik variabel kepercayaan dan persepsi resiko mampu mempengaruhi atau menciptakan keputusan pembelian secara online produk fashion pada media social seperti facebook yang dilakukan oleh para remaja puteri di Kota Ambon. Kata Kunci: Kepercayaan, Persepsi Resiko, Pembelian Online
Strategi Peningkatan Kompetensi Mahasiswa Akuntansi Melalui Model Pembelajaran Berbasis Praktikum
Authors: Gasperz Jefry , Sososutiksno Christina , Atarwaman Rita J.D. 
Published: July 2023

Tujuan yang ingin dicapai dalam penelitian ini adalah mengembangkan model pembelajaran praktikum akuntansi sebagai strategi meningkatkan untuk meningkatkan kompetensi mahasiswa di bidang Akuntansi Keuangan. Penelitian ini akan menjawab masalah bagaimana model pembelajaran praktikum akuntansi yang sesuai di program studi akuntansi.Penelitian ini dilaksanakan dalam dua siklus dan setiap siklus terdiri dari empat tahap yaitu perencanaan, pelaksanaan, observasi, dan refleksi. Teknik pengumpulan data berupa: 1) Observasi; 2) Catatan Lapangan; 3) Dokumentasi. Instrumen penelitian berupa: 1) Lembar Observasi Aktivitas Belajar Akuntansi; 2) Catatan Lapangan; 3) Dokumentasi. Adapun perangkat pembelajaran yang digunakan adalah RPS(Rencana Pembelajaran Semester). Teknik analisis data dalam penelitian ini yaitu teknik analisis deskriptif dengan persentase. Analisis ini dilakukan dengan cara mengolah skor Aktivitas Pembelajaran Akuntansi, menghitung persentase rata-rata Aktivitas Pembelajaran Akuntansi, menyajikan data, dan menarik kesimpulan. Indikator keberhasilan yaitu Model Problem Based Learningdengan berbasis Praktikum mencapai nilai di atas 80% untuk setiap indikator Aktivitas Pembelajaran mahasiswa.Populasi dalam penelitian ini adalah mahasiswa jurusan akuntansi pada Universitas Pattimura. Sedangkan sampel yang diambil adalah 100 mahasiswa jurusan akuntansi yang akan mengambil mata kuliah akuntansi keuangan. Hasil penelitianmenunjukkan bahwa implementasi Model Problem Based Learning dapatmeningkatkanAktivitasBelajarAkuntansi.Haltersebutdidukung olehdatapenelitian yangmenunjukkanadanyapeningkatanpada delapan indikatoryang diamati. Secara umum, AktivitasBelajarAkuntansi juga mengalami peningkatanpadasiklusIdan siklusII. Penelitianyangakandatangpenelitidiharapkanlebihtelitidalam melakukanpengamatan sehinggadapatdiperolehdatayangbenar-benar mewakili kondisiAktivitasBelajarAkuntansi.
ANALISIS SISTEM ANTRIAN PADA STASIUN PENGISIAN BAHAN BAKAR UMUM STUDI KASUS PADA PENGISIAN SOLAR DI (SPBU) 84-983-02 JALAN ESAU SESA KABUPATEN MANOKWARI
Authors: Sudarwadi Dirarini 
Published: July 2023

ABSRTAKPenelitian ini berjudul Analisis Teori Antrian Pada Stasiun PengisianBahan Bakar Umum (SPBU) Esau Sesa Manokwari bertujuan untuk menganalisisjumlah jalur fasilitas yang optimal dan kinerja pelayanan pada tingkat optimal.Jenis data yang digunakan adalah data kuantitatif dan sumber data yang digunakanadalah data primer yaitu observasi dan wawancara. Metode analisis yangdigunakan adalah analisis teori antrian sesuai dengan model antrian yang di terapkan pada SPBU Esau Sesa Manokwari yaitu Model Antrian Jalur Bergandaartinya terdapat lebih dari satu jalur fasilitas dan hanya ada satu tahapanpelayanan yang harus dilalui oleh pelanggan untuk menyelesaikan pelayanan.Hasil dari penelitian pada SPBU Esau Sesa Manokwari denganmenggunakan analisis teori antrian yaitu dengan perhitungan Model Antrian jalur berganda di peroleh antrian terpanjang dalam Sistem (Wq) 0,60 dan terpendek (Wq) 0,28. Dalam perhitungan kinerja sistem antrian pada penelitian masih optimal sesuai dengan standar layanan yang telah ditetapkan.Kata Kunci : Teori Antrian, model antrian jalur berganda (M/M/S), pengoptimalan pelayanan. ABSTRACT This study entitled Analysis of Queuing Theory at Esau Sesa Manokwari Public Gas Station (SPBU) aims to analyze the optimal number of facilities and service performance at optimal levels. The type of data used is quantitative data and data sources used are primary data, namely observation and interviews. The analytical method used is queuing theory analysis in accordance with the queuing model applied to Esau Sesa Manokwari gas stations, namely the Multiple Line Queue Model, meaning that there are more than one facility line and there is only one service stage that the customer must complete to complete the service. The results of the study at the Esau Sesa Manokwari gas station using queuing theory analysis, namely the calculation of the Multiple Path Queue Model obtained the longest queue in the System (Wq) 0.60 and the shortest (Wq) 0.28. In calculating the performance of the queuing system in research is still optimal in accordance with predetermined service standards.Keywords : Queue Theory, multiple path queue model (M/M/S), service optimization.
A review on biogenic silver nanoparticles as efficient and effective antidiabetic agents
Authors: Wahab Maryam , Janaswamy Srinivas 
Published: July 2023

The frontiers of nanomedicine are consistently being challenged by the gradually expanding knowledge of the properties of nanoparticles. Toward this end, biogenic synthesis of silver nanoparticles utilizing natural compounds in plants as reducing and capping agents grabbed considerable attention, in lieu of synthetic hazardous physical and chemical techniques. Green synthesis of silver nanoparticles (AgNPs) has proven safe and effective in treating type 2 diabetes mellitus. Currently, biogenic silver nanoparticles have gained importance as safe and efficient antiglycation agents. Therapeutic strategies by employing nanomedicines from natural sources have been initiated to end the limitations of currently available medications for the treatment of various disorders, including diabetes, Alzheimer’s, cancer, and hepatitis. This article highlights the medicinal efficacy of silver nanoparticles synthesized from different plant extracts for their antidiabetic potential characterized through various in vivo and in vitro assays and unravels their unique properties. This article also focuses on the signaling pathways linked to type II diabetes and the demand for nanomedicine and greener pathways for future pharmacological industries.Keywords: Biogenic silver nanoparticles, antioxidant, Type 2 Diabetes Mellitus (T2DM), α-glucosidase assay, α-amylase assay
Persepsi Pengguna Terhadap Warna Interior Mesjid
Authors: Kahir Shapardi , Syam Syahriana , Harisah Afifah 
Published: July 2023

Seorang arsitek harus memberikan nuansa keheningan dan keagungan, khususnya warna ruang dalam mesjid. Para jamaah mesjid memiliki persepsi akan warna interior itu sendiri yang memberikan dampak psikologis sehingga tercapai kekhusukan dalam melaksanakan ibadah. Tujuan penelitian adalah untuk menganalisis persepsi pengguna terhadap warna interior dan mengidentifikasi warna pada elemen-elemen interior masjid Agung Syekh Yusuf Gowa dan Mesjid Muhammad Ceng Hoo. Metode penelitian kuntitatif yang menganalisis data secara statistik-deskriptif. Instrument penelitian adalah angket, ceklist/daftar centang atau berupa pilihan ganda (Skala Likert), Jenis data yaitu data kuantitatif yang mempertimbangkan data numerik dari pengumpulan data kuosioner lalu data tesebut ditabulasikan untuk melihat hasil/grafik dari setiap jawaban-jawaban responden dan diintrepertasikan oleh peneliti. Hasil penelitian yaitu warna mempengaruhi tingkat kehusyukan ibadah. Pada dua sampel tersebut, sama-sama terbukti bahwa jika pengguna melaksanakan ibadah atau sholat pada mesjid dominan interior gelap ataupun terang, tetap warna menjadi salah satu faktor yang mempengaruhi kekhusyukan ibadah pengguna. Dengan penelitian ini diharapkan dapat menjadi referensi tentang persepsi, warna dan interior masjid.
A machine learning pipeline for extracting decision-support features from traffic scenes1
Authors: Fraga Vitor A. , Schreiber Lincoln V. , da Silva Marco Antonio C. , Kunst Rafael , Barbosa Jorge L.V. , Ramos Gabriel de O. 
Published: July 2023

Traffic systems play a key role in modern society. However, these systems are increasingly suffering from problems, such as congestions. A well-known way to efficiently reduce this kind of problem is to perform traffic light control intelligently through reinforcement learning (RL) algorithms. In this context, extracting relevant features from the traffic environment to support decision-making becomes a central concern. Examples of such features include vehicle counting on each queue, identification of vehicles’ origins and destinations, among others. Recently, the advent of deep learning has paved to way to efficient methods for extracting some of the aforementioned features. However, the problem of identifying vehicles and their origins and destinations within an intersection has not been fully addressed in the literature, even though such information has shown to play a role in RL-based traffic signal control. Building against this background, in this work we propose a deep learning pipeline for extracting relevant features from intersections based on traffic scenes. Our pipeline comprises three main steps: (i) a YOLO-based object detector fine-tuned using the UAVDT dataset, (ii) a tracking algorithm to keep track of vehicles along their trajectories, and (iii) an origin-destination identification algorithm. Using this pipeline, it is possible to identify vehicles as well as their origins and destinations within a given intersection. In order to assess our pipeline, we evaluated each of its modules separately as well as the pipeline as a whole. The object detector model obtained 98.2% recall and 79.5% precision, on average. The tracking algorithm obtained a MOTA of 72.6% and a MOTP of 74.4%. Finally, the complete pipeline obtained an average error rate of 3.065% in terms of origin and destination counts.
Ask me how I am, not only how much it hurts: Narratives of injured recreational runners
Authors: Festersen Michael Krag , Mose Caroline Broberg , Kloosterman Anne Michelle , Sivesgaard Heidi , Ramskov Daniel , Schmidt Jannie Tygesen 
Published: July 2023

BACKGROUND: Running-related injuries (RRI) are common among recreational runners, but research exploring lived experiences of a RRI is limited. OBJECTIVE: This study aimed to explore the psychosocial aspects experienced by recreational runners hindered in usual running because of RRI. METHODS: Individual semi-structured interviews based on a qualitative phenomenological methodology explored injured recreational runners experiences, reactions, thoughts, and feelings. Systematic text condensation was used as the analysis method. RESULTS: Three main codes were identified: Reasons for running: ‘ Calm for me is a feeling of my body just relaxing. It may sound a bit weird because you run, but it is kind of a feeling of just being able to unplug‘, Daily life during an injury - besides running: ‘ When I couldn’t run at all, it was super annoying. Several months it was completely empty. It was like there was a hole. There seemed to be missing something because I usually ran‘, Running while injured: ‘ Do I feel pain? Or is it something else? And should I navigate regarding the length of the route and where I run, how fast I run, and with whom I run? ‘. CONCLUSION: The recreational runners experiences explored in this study support the importance of bio-psycho-social awareness when physiotherapists meet runners hindered in usual running because of RRI.
Application and testing of RFID Software-Based Shielding in real fashion retail stores
Authors: Mezzogori Davide , Rizzi Antonio , Romagnoli Giovanni , Rosa Mirco 
Published: July 2023

PURPOSE: The present paper investigates the real performances of Software-Based Shielding (SBS) in two different stores of fashion retailers located in Northern Italy. DESIGN/METHODOLOGY/APPROACH: The study is based on a double case study analysis. Six different factors have been chosen, with two levels each. Namely, we investigated two different (i) stores; (ii) reader models; (iii) power levels; (iv) classification methods; (v) training data sets and (vi) settings of reference tags. The results have been evaluated in terms of overall and specific accuracies, and in percentage of false front (i.e., tags wrongly located in the sales floor area). FINDINGS: SBS proves to be a sound method for classifying tags’ location during normal operations in real-life stores, with overall accuracy up to 0.95. Of the two readers, reader A shows better results in terms of both overall and front accuracy, whereas reader B performs better in terms of rear accuracy and percentage of false front. With respect to the classification method, the combination of Method 2 with reads from reader A provides the best results. With respect to the training data, the use of front and back reads for training performs mostly better than the training with sole front data. ORIGINALITY: We are not aware of any other study that performed and reported results of SBS testing under normal operations in real stores. To the best of our knowledge, this study is the first one to report such results. RESEARCH LIMITATIONS: Main limitations of our research are the limited set of factors and levels, and the specific classification methods that we used, labelled as Method 1 and Method 2. Also, we did not consider tags disposition and density in our study. PRACTICAL IMPLICATIONS: We prove that SBS is a feasible option that could replace physical shielding in retail stores. We call to action for further research on this topic, and for retailers to test it in different store locations.
A computational approach for analysis of intratumoral heterogeneity and standardized uptake value in PET/CT images
Authors: Alshamrani Khalaf , Alshamrani Hassan A. 
Published: July 2023

BACKGROUND: By providing both functional and anatomical information from a single scan, digital imaging technologies like PET/CT and PET/MRI hybrids are gaining popularity in medical imaging industry. In clinical practice, the median value (SUVmed) receives less attention owing to disagreements surrounding what defines a lesion, but the SUVmax value, which is a semi-quantitative statistic used to analyse PET and PET/CT images, is commonly used to evaluate lesions. OBJECTIVE: This study aims to build an image processing technique with the purpose of automatically detecting and isolating lesions in PET/CT images, as well as measuring and assessing the SUVmed. METHODS: The pictures are separated into their respective lesions using mathematical morphology and the crescent region, which are both part of the image processing method. In this research, a total of 18 different pictures of lesions were evaluated. RESULTS: The findings of the study reveal that the threshold is satisfied by both the SUVmax and the SUVmed for most of the lesion types. However, in six instances, the SUVmax and SUVmed values are found to be in different courts. CONCLUSION: The new information revealed by this study needs to be further investigated to determine if it has any practical value in diagnosing and monitoring lesions. However, results of this study suggest that SUVmed should receive more attention in the evaluation of lesions in PET and CT images.
Pendeteksi Mobil Berdasarkan Merek dan Tipe Menggunakan Algoritma YOLO
Authors: Riansyah Al , Mirza A Haidar 
Published: July 2023

Sistem pemeritah di suatu wilayah atau kota memiliki peraturan dalam mengatur aktivitas penduduknya, terutama yang berkaitan berkendara di jalan raya. Pelanggaran lalulintas kerap terjadi di jalan perkotaan maupun jalan raya. Hal ini dapat memicu kecelakaan akibat melanggar peraturan lalulintas. Hal tersebut mendorong pemerintah untuk mengambil tidak tegas bagi para pengendara yang melanggar peraturan. Maka dari itu diperlukan sebuah sistem yang mampu membantu memantau kondisi lalu lintas. Sehingga penelitian ini bertujuan untuk membuat sistem yang mampu mendeteksi kendaraan mobil berdasarkan merek dan tipenya dengan tingkat akurasi pendeteksian yang tinggi, sehingga dapat mepermudah dalam mengenali objek mobil yang ada di sekitar. Sistem pendeteksi akan dikembangkan menggunakan Algoritma YOLO (You Only Look Once), karena YOLO adalah salah satu metode paling cepat dan akurat dalam pendeteksian objek bahkan mampu melebihi hingga 2 kali kemampuan algoritma lain. Algoritma YOLO (You Only Look Once) merupakan arsitektur dari deep learning dan sebuah algoritma yang dikembangkan untuk mendeteksi sebuah objek secara real-time. Pendeteksian dilakukan pada gambar, dan ketika akses webcam laptop yang didalamnya terdapat objek mobil menggunakan model dari dataset yang telah di training menggunakan framework Darknet. Objek mobil yang terdeteksi akan terdapat bounding box di area objek tersebut, dan terdapat keterangan nama mobil dan tipe serta tahun produksinya pada area bounding box tersebut. Berdasarkan pengujian kinerja klasifikasi dari data yang telah dilakukan training menunjukkan bahwa nilai akurasi mencapai 92% sehingga dapat disimpulkan bahwa sistem dapat bekerja dengan baik.