MétaCan
Menu
Back to cohort
Record W3174471512 · doi:10.37535/104001120216

Perencanaan Model Bisnis pada UMKM dalam Mengembangkan Oleh-oleh Khas Bekasi

2021· article· id· W3174471512 on OpenAlexaff
Jati Paras Ayu

Bibliographic record

VenueJournal of Research on Business and Tourism · 2021
Typearticle
Languageid
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesBusiness administrationBusinessBusiness Model CanvasMarketingBusiness modelArt

Abstract

fetched live from OpenAlex

Penelitian ini bertujuan untuk mengidentifikasi model bisnis yang digunakan oleh bisnis kuliner Bekasi Salaku dengan menggunakan business model canvas. Identifikasi dilakukan dalam 9 elemen dalam business model canvas yaitu customer segments, value proposition, channels, customer relationship, revenue streams, key resources, key activities, key partnership, dan cost structure. Penelitian ini menggunakan pendekatan kualitatif dan metode penelitian ini adalah studi kasus. Pengumpulan data primer pada penelitian ini dilakukan yaitu dengan menggunakan wawancara. Hasil penelitian yang ditemukan ialah belum adanya perencanaan Business Model Canvas yang memenuhi 9 elemen model bisnis, oleh karena itu peneliti membantu membuatkan atau merencanakan usaha kuliner khas Bekasi Salaku ke dalam 9 elemen model bisnis. Setelah merancang dari 9 elemen model bisnis Salaku miliki maka hasil simpulan dan saran yang dapat diberikan yaitu, Salaku perlu membuat strategi marketing yang lebih gencar dan menarik untuk memasarkan produk yang spesifik kepada pasar yang potensial. Strategi marketing yang lebih gencar seperti membuat suatu jadwal posting Sosial Media dalam satu timetable lalu bekerja sama dengan banyak Lembaga terkait seperti Dinas Pariwisata daerah, lalu memasarkan produk yang menarik yaitu membuat design postingan sosial media yang lebih atraktif dari warna dan angle foto lalu mengemas produk yang sesuai pada tren saat ini.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.091
GPT teacher head0.371
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Research on Business and TourismSame topicSMEs Development and Digital MarketingFrench-language works237,207