IMPLEMENTASI KEBIJAKAN SISTEM INFORMASI PEMERINTAHDAERAH (SIPD) PADA BADAN PERENCANAAN PEMBANGUNAN,RISET DAN INOVASI DAERAH KOTA BANDAR LAMPUNG
Bibliographic record
Abstract
Sistem Informasi Pemerintah Daerah (SIPD) merupakan salah satu kebijakan yang menjadi bagian dari sistem informasi, dengan tujuan menerapkan teknologi informasi dalam proses penginputan data dan informasi perencanaan pembangunan. Penelitian ini bertujuan untuk mengetahui sejauh mana implementasi kebijakan SIPD ini dalam membantu Bapperida Kota Bandar Lampung sebagai admin pelaksana untuk mengkooordinasi pemerintah daerah dalam pengimplementasian SIPD. Penelitian ini menggunakan pendekatan kualitatif dengan analisis data menggunakan teori implementasi kebijakan Thomas B Smith yaitu kebijakan yang diidealkan, kelompok sasaran, organisasi pelaksana dan faktor lingkungan. Data penelitian berasal dari hasil wawancara, dokumentasi dan observasi. Pemanfaatan SIPD dapat menjadi pemecah masalah dengan mempermudah perencanaan pembangunan, karena dengan adanya SIPD data-data dapat di masukkan dengan mudah ke dalam sistem tersebut juga membantu dan mempermudah Bapperida serta OPD lainnya dalam memilih usulan-usulan prioritas. Hasil penelitian ini menemukan bahwa Bapperida sudah menjalankan tugasnya dengan baik agar implementasi SIPD ini berjalan sesuai dengan kebijakan yang telah dibuat, tetapi masih terdapat kendala pada sumber daya manusia yang ditunjuk untuk mengimplementasikan SIPD tersebut. Kata Kunci : Implementasi Kebijakan, Sistem Informasi Pemerintah Daerah, Perencanaan Pembangunan, Koordinasi Antar Pihak The Regional Government Information System (SIPD) is one of the policies that is part of the information system, with the aim of implementing information technology in the process of inputting data and development planning information. This study aims to determine the extent to which the implementation of this SIPD policy is in assisting Bapperida of Bandar Lampung City as the implementing admin to coordinate the local government in implementing SIPD. This study uses a qualitative approach with data analysis using Thomas B Smith's policy implementation theory, namely idealized policies, target groups, implementing organizations and environmental factors. Research data comes from interviews, documentation and observations. The use of SIPD can be a problem solver by facilitating development planning, because with SIPD data can be easily entered into the system and also helps and facilitates Bapperida and other OPDs in selecting priority proposals. The results of this study found that Bapperida has carried out its duties well so that the implementation of SIPD runs in accordance with the policies that have been made, but there are still obstacles in the human resources appointed to implement SIPD. Key Words : Policy Implementation, Regional Government Information Systems, Development Planning, Coordination Between Parties
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.020 |
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".