KomDesa: Inovasi Digital Partisipatif untuk Perencanaan Pembangunan Desa Cerdas
Bibliographic record
Abstract
Abstract. The development of digital technology opens up strategic opportunities to bridge the communication gap between village communities and academics in the context of smart village development. This research aims to design and develop a prototype of the KomDesa application, an interactive platform that connects village communities with experts from academic institutions as an effort to encourage community involvement in smart village development planning. The method used is the Waterfall model software engineering approach, including needs analysis, design, implementation, testing, and maintenance. Data was collected through literature studies, user observations, and interviews with community representatives and academics. The results show that KomDesa has succeeded in providing five main features, namely Explore Community Problems, Find Experts, Community, Consulting, and Explore UNISBA Research and Service which are considered relevant and easy to use by early users. These findings show that KomDesa has the potential as a participatory digital solution that strengthens cross-sector collaboration, encourages local knowledge-based planning, and supports the development of an inclusive and sustainable smart village ecosystem. In the future, this application can be optimized to strengthen the role of villages as active subjects in inclusive, collaborative, and knowledge-based social transformation development planning. Abstrak. Perkembangan teknologi digital membuka peluang strategis untuk menjembatani kesenjangan komunikasi antara komunitas desa dan kalangan akademisi dalam konteks pembangunan desa cerdas (smart village). Penelitian ini bertujuan merancang dan mengembangkan prototipe aplikasi KomDesa, sebuah platform interaktif yang menghubungkan masyarakat desa dengan pakar dari institusi akademik sebagai upaya mendorong keterlibatan masyarakat dalam perencanaan pembangunan desa cerdas. Metode yang digunakan adalah pendekatan rekayasa perangkat lunak model Waterfall, meliputi analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Data dikumpulkan melalui studi literatur, observasi pengguna, dan wawancara dengan perwakilan komunitas dan akademisi. Hasil menunjukkan bahwa KomDesa berhasil menyediakan lima fitur utama, yaitu Jelajah Masalah Komunitas, Cari Pakar, Komunitas, Konsultasi, serta Jelajah Penelitian dan Pengabdian UNISBA yang dinilai relevan dan mudah digunakan oleh pengguna awal. Temuan ini menunjukkan bahwa KomDesa memiliki potensi sebagai solusi digital partisipatif yang memperkuat kolaborasi lintas sektor, mendorong perencanaan berbasis pengetahuan lokal, dan mendukung pengembangan ekosistem desa cerdas yang inklusif dan berkelanjutan. Ke depan, aplikasi ini dapat dioptimalkan untuk memperkuat peran desa sebagai subjek aktif dalam perencanaan pembangunan yang inklusif, kolaboratif, dan berorientasi pada transformasi sosial berbasis pengetahuan.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".