24 research outputs found
Pengukuran Kualitas Produk, Rating Produk Online dan Ulasan Produk Online Terhadap Keputusan Pembelian Pada Toko Online Shopee,
Penelitian ini bertujuan untuk mengetahui mengukur seberapa besar
pengaruh kualitas produk, rating produk Online dan ulasan produk Online
berpengaruh secara bersama–sama terhadap keputusan pembelian Mahasiswa
Prodi Manajemen Fakultas Ekonomi dan Bisnis Angkatan 2017 Universitas
Bhayangkara Jakarta Raya pada toko Online shopee. Metode yang digunakan
adalah metode kuantitatif. Populasi yang digunakan dalam penelitian ini adalah
mahasiswa Fakultas Ekonomi dan Bisnis Universitas Bhayangkara Jakarta Raya
Angkatan 2017 yang pernah menggunakan aplikasi Shopee untuk berbelanja.
Teknik yang digunakan adalah non-probability sampling dengan Teknik sampling
jenuh dengan penyebaran kuesioner melalui google kuesioner. Teknik analisis
data pada penelitian ini yaitu uji kualitas data, uji asumsi klasik, uji hepotesis uji
analisis regresi linear berganda, koefisien determinasi.
Hasil penelitian menunjukkan bahwa variabel Kualitas Produk, Rating
Produk Online dan Ulasan Produk Online secara simultan berpengaruh signifikan
terhadap keputusan pembelian. Yang berarti kemampuan variabel independen
(Kualitas Produk, Rating Produk Online dan Ulasan Produk Online) dalam
menerangkan perubahan variabel dependen (Keputusan Pembelian) sebesar 64,6%
sisanya 35,4% dijelaskan oleh variabel lain yang berada diluar dari penelitian in
Penerapan Analytical Hierarchy Process (AHP) Untuk Decission Support System Pemilihan Vendor IT
Pemilihan Vendor terbaik oleh Decission Maker dalam menentukan keputusan untuk pengerjaan project harus dilakukan dengan sangat cermat. Berbagai macam kriteria yang kompleks membuat penentu keputusan mengalami kesusahan dalam menentukan pilihan yang sesuai. Analytical Hierarchy Process (AHP) dapat digunakan untuk membantu dalam menentukan keputusan (deciccion Support System) terutama dalam pemilihan vendor IT untuk project yang dilakukan. Dari hasil perangkingan mnggunakan AHP peringkat pertama diduduki oleh GA dengan total nilai 44,18%, CMC di posisi kedua sebesar 31% , Posisi ke tiga oleh PSW sebesar 15,70% dan ESS diposisi ke empat dengan nilai 9,12%. The selection of the best vendor by Decission Maker in determining the decision to work on the project must be done very carefully. Various kinds of complex criteria make the decision makers experience difficulties in determining the appropriate choice. Analytical Hierarchy Process (AHP) can be used to assist in determining decisions Support System, especially in the selection of IT vendors for the project being carried out. From the ranking using the first rank AHP was occupied by GA with a total value of 44.18%, CMC in the second position by 31%, the third position by PSW was 15.70% and ESS was placed fourth with a value of 9.12%
Crosslingual Generalization through Multitask Finetuning
Multitask prompted finetuning (MTF) has been shown to help large language
models generalize to new tasks in a zero-shot setting, but so far explorations
of MTF have focused on English data and models. We apply MTF to the pretrained
multilingual BLOOM and mT5 model families to produce finetuned variants called
BLOOMZ and mT0. We find finetuning large multilingual language models on
English tasks with English prompts allows for task generalization to
non-English languages that appear only in the pretraining corpus. Finetuning on
multilingual tasks with English prompts further improves performance on English
and non-English tasks leading to various state-of-the-art zero-shot results. We
also investigate finetuning on multilingual tasks with prompts that have been
machine-translated from English to match the language of each dataset. We find
training on these machine-translated prompts leads to better performance on
human-written prompts in the respective languages. Surprisingly, we find models
are capable of zero-shot generalization to tasks in languages they have never
intentionally seen. We conjecture that the models are learning higher-level
capabilities that are both task- and language-agnostic. In addition, we
introduce xP3, a composite of supervised datasets in 46 languages with English
and machine-translated prompts. Our code, datasets and models are freely
available at https://github.com/bigscience-workshop/xmtf.Comment: 9 main pages (119 with appendix), 16 figures and 11 table
Bounding the pseudogap with a line of phase transitions in YBCO cuprate superconductors
Close to optimal doping, the copper oxide superconductors show 'strange
metal' behavior, suggestive of strong fluctuations associated with a quantum
critical point. Such a critical point requires a line of classical phase
transitions terminating at zero temperature near optimal doping inside the
superconducting 'dome'. The underdoped region of the temperature-doping phase
diagram from which superconductivity emerges is referred to as the 'pseudogap'
because evidence exists for partial gapping of the conduction electrons, but so
far there is no compelling thermodynamic evidence as to whether the pseudogap
is a distinct phase or a continuous evolution of physical properties on
cooling. Here we report that the pseudogap in YBCO cuprate superconductors is a
distinct phase, bounded by a line of phase transitions. The doping dependence
of this line is such that it terminates at zero temperature inside the
superconducting dome. From this we conclude that quantum criticality drives the
strange metallic behavior and therefore superconductivity in the cuprates
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Large language models (LLMs) have been shown to be able to perform new tasks
based on a few demonstrations or natural language instructions. While these
capabilities have led to widespread adoption, most LLMs are developed by
resource-rich organizations and are frequently kept from the public. As a step
towards democratizing this powerful technology, we present BLOOM, a
176B-parameter open-access language model designed and built thanks to a
collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer
language model that was trained on the ROOTS corpus, a dataset comprising
hundreds of sources in 46 natural and 13 programming languages (59 in total).
We find that BLOOM achieves competitive performance on a wide variety of
benchmarks, with stronger results after undergoing multitask prompted
finetuning. To facilitate future research and applications using LLMs, we
publicly release our models and code under the Responsible AI License
The SANAD II study of the effectiveness and cost-effectiveness of levetiracetam, zonisamide, or lamotrigine for newly diagnosed focal epilepsy: an open-label, non-inferiority, multicentre, phase 4, randomised controlled trial
Background:
Levetiracetam and zonisamide are licensed as monotherapy for patients with focal epilepsy, but there is uncertainty as to whether they should be recommended as first-line treatments because of insufficient evidence of clinical effectiveness and cost-effectiveness. We aimed to assess the long-term clinical effectiveness and cost-effectiveness of levetiracetam and zonisamide compared with lamotrigine in people with newly diagnosed focal epilepsy.
Methods:
This randomised, open-label, controlled trial compared levetiracetam and zonisamide with lamotrigine as first-line treatment for patients with newly diagnosed focal epilepsy. Adult and paediatric neurology services across the UK recruited participants aged 5 years or older (with no upper age limit) with two or more unprovoked focal seizures. Participants were randomly allocated (1:1:1) using a minimisation programme with a random element utilising factor to receive lamotrigine, levetiracetam, or zonisamide. Participants and investigators were not masked and were aware of treatment allocation. SANAD II was designed to assess non-inferiority of both levetiracetam and zonisamide to lamotrigine for the primary outcome of time to 12-month remission. Anti-seizure medications were taken orally and for participants aged 12 years or older the initial advised maintenance doses were lamotrigine 50 mg (morning) and 100 mg (evening), levetiracetam 500 mg twice per day, and zonisamide 100 mg twice per day. For children aged between 5 and 12 years the initial daily maintenance doses advised were lamotrigine 1·5 mg/kg twice per day, levetiracetam 20 mg/kg twice per day, and zonisamide 2·5 mg/kg twice per day. All participants were included in the intention-to-treat (ITT) analysis. The per-protocol (PP) analysis excluded participants with major protocol deviations and those who were subsequently diagnosed as not having epilepsy. Safety analysis included all participants who received one dose of any study drug. The non-inferiority limit was a hazard ratio (HR) of 1·329, which equates to an absolute difference of 10%. A HR greater than 1 indicated that an event was more likely on lamotrigine. The trial is registered with the ISRCTN registry, 30294119 (EudraCt number: 2012-001884-64).
Findings:
990 participants were recruited between May 2, 2013, and June 20, 2017, and followed up for a further 2 years. Patients were randomly assigned to receive lamotrigine (n=330), levetiracetam (n=332), or zonisamide (n=328). The ITT analysis included all participants and the PP analysis included 324 participants randomly assigned to lamotrigine, 320 participants randomly assigned to levetiracetam, and 315 participants randomly assigned to zonisamide. Levetiracetam did not meet the criteria for non-inferiority in the ITT analysis of time to 12-month remission versus lamotrigine (HR 1·18; 97·5% CI 0·95–1·47) but zonisamide did meet the criteria for non-inferiority in the ITT analysis versus lamotrigine (1·03; 0·83–1·28). The PP analysis showed that 12-month remission was superior with lamotrigine than both levetiracetam (HR 1·32 [97·5% CI 1·05 to 1·66]) and zonisamide (HR 1·37 [1·08–1·73]). There were 37 deaths during the trial. Adverse reactions were reported by 108 (33%) participants who started lamotrigine, 144 (44%) participants who started levetiracetam, and 146 (45%) participants who started zonisamide. Lamotrigine was superior in the cost-utility analysis, with a higher net health benefit of 1·403 QALYs (97·5% central range 1·319–1·458) compared with 1·222 (1·110–1·283) for levetiracetam and 1·232 (1·112, 1·307) for zonisamide at a cost-effectiveness threshold of £20 000 per QALY. Cost-effectiveness was based on differences between treatment groups in costs and QALYs.
Interpretation:
These findings do not support the use of levetiracetam or zonisamide as first-line treatments for patients with focal epilepsy. Lamotrigine should remain a first-line treatment for patients with focal epilepsy and should be the standard treatment in future trials.
Funding:
National Institute for Health Research Health Technology Assessment programme
The SANAD II study of the effectiveness and cost-effectiveness of valproate versus levetiracetam for newly diagnosed generalised and unclassifiable epilepsy: an open-label, non-inferiority, multicentre, phase 4, randomised controlled trial
Background:
Valproate is a first-line treatment for patients with newly diagnosed idiopathic generalised or difficult to classify epilepsy, but not for women of child-bearing potential because of teratogenicity. Levetiracetam is increasingly prescribed for these patient populations despite scarcity of evidence of clinical effectiveness or cost-effectiveness. We aimed to compare the long-term clinical effectiveness and cost-effectiveness of levetiracetam compared with valproate in participants with newly diagnosed generalised or unclassifiable epilepsy.
Methods:
We did an open-label, randomised controlled trial to compare levetiracetam with valproate as first-line treatment for patients with generalised or unclassified epilepsy. Adult and paediatric neurology services (69 centres overall) across the UK recruited participants aged 5 years or older (with no upper age limit) with two or more unprovoked generalised or unclassifiable seizures. Participants were randomly allocated (1:1) to receive either levetiracetam or valproate, using a minimisation programme with a random element utilising factors. Participants and investigators were aware of treatment allocation. For participants aged 12 years or older, the initial advised maintenance doses were 500 mg twice per day for levetiracetam and valproate, and for children aged 5–12 years, the initial daily maintenance doses advised were 25 mg/kg for valproate and 40 mg/kg for levetiracetam. All drugs were administered orally. SANAD II was designed to assess the non-inferiority of levetiracetam compared with valproate for the primary outcome time to 12-month remission. The non-inferiority limit was a hazard ratio (HR) of 1·314, which equates to an absolute difference of 10%. A HR greater than 1 indicated that an event was more likely on valproate. All participants were included in the intention-to-treat (ITT) analysis. Per-protocol (PP) analyses excluded participants with major protocol deviations and those who were subsequently diagnosed as not having epilepsy. Safety analyses included all participants who received one dose of any study drug. This trial is registered with the ISRCTN registry, 30294119 (EudraCt number: 2012-001884-64).
Findings:
520 participants were recruited between April 30, 2013, and Aug 2, 2016, and followed up for a further 2 years. 260 participants were randomly allocated to receive levetiracetam and 260 participants to receive valproate. The ITT analysis included all participants and the PP analysis included 255 participants randomly allocated to valproate and 254 randomly allocated to levetiracetam. Median age of participants was 13·9 years (range 5·0–94·4), 65% were male and 35% were female, 397 participants had generalised epilepsy, and 123 unclassified epilepsy. Levetiracetam did not meet the criteria for non-inferiority in the ITT analysis of time to 12-month remission (HR 1·19 [95% CI 0·96–1·47]); non-inferiority margin 1·314. The PP analysis showed that the 12-month remission was superior with valproate than with levetiracetam. There were two deaths, one in each group, that were unrelated to trial treatments. Adverse reactions were reported by 96 (37%) participants randomly assigned to valproate and 107 (42%) participants randomly assigned to levetiracetam. Levetiracetam was dominated by valproate in the cost-utility analysis, with a negative incremental net health benefit of −0·040 (95% central range −0·175 to 0·037) and a probability of 0·17 of being cost-effectiveness at a threshold of £20 000 per quality-adjusted life-year. Cost-effectiveness was based on differences between treatment groups in costs and quality-adjusted life-years.
Interpretation:
Compared with valproate, levetiracetam was found to be neither clinically effective nor cost-effective. For girls and women of child-bearing potential, these results inform discussions about benefit and harm of avoiding valproate.
Funding:
National Institute for Health Research Health Technology Assessment Programme
Penerapan Analytical Hierarchy Process (AHP) Untuk Decission Support System Pemilihan Vendor IT
Pemilihan Vendor terbaik oleh Decission Maker dalam menentukan keputusan untuk pengerjaan project harus dilakukan dengan sangat cermat. Berbagai macam kriteria yang kompleks membuat penentu keputusan mengalami kesusahan dalam menentukan pilihan yang sesuai. Analytical Hierarchy Process (AHP) dapat digunakan untuk membantu dalam menentukan keputusan (deciccion Support System) terutama dalam pemilihan vendor IT untuk project yang dilakukan. Dari hasil perangkingan mnggunakan AHP peringkat pertama diduduki oleh GA dengan total nilai 44,18%, CMC di posisi kedua sebesar 31% , Posisi ke tiga oleh PSW sebesar 15,70% dan ESS diposisi ke empat dengan nilai 9,12%. The selection of the best vendor by Decission Maker in determining the decision to work on the project must be done very carefully. Various kinds of complex criteria make the decision makers experience difficulties in determining the appropriate choice. Analytical Hierarchy Process (AHP) can be used to assist in determining decisions Support System, especially in the selection of IT vendors for the project being carried out. From the ranking using the first rank AHP was occupied by GA with a total value of 44.18%, CMC in the second position by 31%, the third position by PSW was 15.70% and ESS was placed fourth with a value of 9.12%
Pelatihan Kelompok Sadar Wisata Kabupaten Landak
Landak Regency in the province of West Kalimantan is rich in beautiful natural tourist attractions. Limited human resources and lack of infrastructure affect the development needed to manage those places properly. However, Landak has 12 communities that support local tourism, known as Kelompok Sadar Wisata (Pokdarwis), in each subdistrict. They are to be good beginning pioneers to manage the local tourist attractions. Helping them, STKIP Pamane Talino in collaboration with Dinas Pemuda Olahraga dan Pariwisata Landak (Disporapar) provide them training on how to be a good tour guide as our community service. They are expected to have more skills and knowledge to recognize and develop any gift and potential in their village. They will be the leader of their Pokdarwis. The implementation of this community service has been done through several stages: taking surveys, interviewing residents and community leaders, training on Sapta Pesona and tour guide, and preparing the final report. This activity results in the growth of public awareness, especially among members of the Pokdarwis, in developing and maintaining local tourist attractions