This activity is the second stage of the meeting of the Assistance Activity for the Preparation of Evidence-Based Policy Instruments in the District of Rembang.

Twenty-six officials in charge of planning in the Government Work Unit (SKPD) throughout the district of Rembang participated in the agenda. They come from the offices such as Bappeda, Regional Secretariat, The Department of Population and Civil Registration, the Department of Transportation Communication and Information, the Department of Industry Trade and Cooperatives - Micro Small Medium Enterprises, the Regional Disaster Management Agency (BPBD), Inspectorate, Regional Employment Agency (BKD), the Regional Revenues and Regional Asset Management (DPPKAD), the Department of Social, Manpower, and Transmigration, Administrative Section of the Regional Secretariat, Legislative Secretariat, the Civil Service Police,  The Department of Agriculture and Forestry, Public Relations Secretariat, Regional Secretariat Welfare Section, Regional Secretariat General Affairs, Regional Secretariat Legal Section, Financial Administration Section,  Regional Secretariat Organization and Staffing Section, Integrated One-Stop Service Center for Investment Licensing (KPPT), Department of National Unity and Political Development, Regional Hospitals, Department of Education, Tourism, and Sport, Department of Food Resilience, Outreach, Agriculture, Fishery, and Forestry (BKP & P4K), Department of Energy and Mineral Resources, and the Center for Data and Archive Office.

The main objective of the second meeting was to acknowledge data needed per the Government Work Units (SKPD) based on the draft instrument previously sent.

THE SEQUENCE AND DESCRIPTION OF THE EVENT

The series of activities consisted of an Opening and Introduction by Drs. Drupodo MM, the Secretary of BAPPEDA of the district of Rembang, the Morning Exposure and Discussion Session, and the Afternoon Presentation and Discussion.

Drupodo, in his opening remarks, repeatedly reminded the attendees from the respective work unit (SKPD) to commit to participating in the event until concluded this afternoon. Since the agenda was also to explore collective agreement on the instrument to be used and inquired for input discussions on the data needed in the future based on the strategic plan and indicators in the particular National Medium-Term Development Plan (RPJMD). We expect the synchronization of data until the evaluation of the RPJMD and Strategic Plan, the programs and activities listed in the Activity Plan Budget (RKA) and the Document Implementation Budget (DPA) of each SKPD would lead to the overall objective of the vision and mission of the district of Rembang. We could tabulate and collaborate for the next RPJMD because we demand harmonization, structure, and integration in the RPJMD. Every Head of sub-division in each SKPD could be the pioneer of the aspiration.

Exposure and Discussion in the Morning Session

The exposure and discussion in the morning session regarding the four aspects of the data were administered by Dani Alfah and Roni Hermoko. Dani commenced by reflecting on the results of the previous meeting based on the answers of the SKPD participants to four questions to identify problems with data needs, data problems, and future challenges. Those are first, the data specifications desired by respective SKPDs vary in accordance with their main duties, second, almost all data owned exists and available but problematics, third, the main issues in data are centered on human resources, fourth, the need for data and information is adjusted to the needs of each SKPD.

Furthermore, Dani explores the four data issues prior to utilizing them in the policy formulation programs, namely from the data source, collection, quality, and analysis. The aspect of data source consists of primary and secondary data. The primary data is data obtained directly (first hand) by researchers, for example, through questionnaires, focus group discussions, and panels, or also data from in-depth interviews with resource persons. Meanwhile, secondary data is acquired by researchers from existing sources, for example, government records or documentation in the form of salaries, published financial reports, government reports, and the central bureau of statistics (BPS) data.

There are two straightforward things to do in developing instruments, first, if we do not create our own questionnaires however based on the existing ones and already know the concept, second, self-composed the instrument according to the theory is necessary to delve for the consensus matched to the desired concept. The conceptual grasp is pivotal in conducting data analysis, for example, whether the concept of work definition adopted by the BPS is in accordance with the respective SKPD desires.

Meanwhile, the data collection aspect relates to the technique of collecting data (surveys) in the field in the type of implementing observations, sending questionnaires, and conducting interviews. Prior to collecting survey data/field research, there are five stages of preparation; first, discussion of the instrument (determining indicators, population, sample, and initial design of the instrument); second, the pilot-test survey (to see the reliability in the field whether the flow of the instrument is applicable and easily understood by the respondents or not, determine the time of the study and the possibility of instrument revision); third, pre-tests were carried out following up on the pilot results, to determine the reliability and final instrument; fourth, design data entry (debugging to elicit the final computerize data entry program); fifth is training the human resources (preparing guidebook arrangement; deciding learning and teaching patterns).

The data quality aspects have to meet the six flows of the data quality assurance processes both in the field and in the office until carrying out the analysis phase. They include observation, inspection, verification, consistency check, run missing, and look-up. Observation is conducted during data collection, while the inspection is when the questionnaire already exists and is re-checked for the possibility of missing data. Verification is done directly by revisiting some samples on the spot, while a consistency check is a programmatic effort designed to detect or examine whether the inter-related variables are correct, accurate, valid, and adequate. Run missing is a process applied programmatically installed to ensure all raw data is correct and comprehensive while a look-up stage is held by several trained officers who review the possibility of errors and recommend if data is no change, suggest to change, or changed by providing a note why it happened that way.

During this discussion, a question arose from the participant (Hary Massahir from Bappeda): how to verify the length of damaged roads, the trend of which is increasing while on the other hand, the budget for repairs is also increasing. Is there a comparison verification model other than field verification?

Responding to the question, Dani Alfah said that if there is no initial data (database) on where and the extent of the previous road damage, the most likely thing to do is an estimate by looking at trends.

Data analysis aspects are also called data processing or data interpretation. It is a series of activities for reviewing, grouping, systematizing, interpreting, and verifying data until a phenomenon has social, academic, and scientific value. Its activities are grouping the database on variables and types of respondents, tabulating the database on variables and all respondents, presenting data for each variable studied, performing computation to answer the problem formulation, and performing arithmetic to test hypotheses.

Data analysis technically explores entry, cleaning, coding, output, and analysis stages. Those processes run from field data collection to office analysis, along with the data analysis may be applied to univariate, bivariate, or multivariate. Its program tools can use XLS, SPSS, or STATA, while the type of analysis may be implemented as descriptive or inferential.

Presentation and Discussion in the Afternoon Session

The presentation and discussion in the afternoon session on the Analytical Hierarchy Process (AHP) were introduced by Dani Alfah. He briefly presented the material straight to the point by explaining the things that are considered most important.

The Analytic Hierarchy Process (AHP) is a theory of measurement through pairwise comparisons and relies on the judgments of experts to derive priority scales. It is a decision-making method that involves a number of criteria and alternatives that are selected based on consideration of all related criteria. (Thomas L. Saaty, 2004).

The SurveyMETER Team provided a kind of post-question to the participants at the end of the event as an evaluation material to capture future input based on the two meetings already been held. Their answers were collected and written on a piece of manila paper. The four questions are as follows:

1. Do you feel the distinction of information in pre-or-post-the-two EVIDENCE-BASED POLICY INSTRUMENT DEVELOPMENT activities carries out?
2. What distinction do you feel?
3. What material (information) do you expect in the next activity?
4. Are you committed to escorting the ONE DATA idea in the district of Rembang?

In response to the four questions, there were only two of the nineteen government work units (SKPDs) attending the agenda till it concluded by answering NO or NOT YET to the first question. Both of them are SKPD representatives who have just attended the second stage of the meeting because at the first meeting were represented by others. However, to the fourth question, all SKPDs stated their commitment to follow, succeed, and escort the ONE DATA idea in the district of Rembang.

The responses of each SKDP to the second and third questions varied but tended to be similar. Regarding the second question, they generally mention new and more detailed knowledge and the importance of data for the formulation of policy programs. While for the third question, most of them conveyed the technical and practical data collection and analysis.

The details of the reasons for the differences (answers to the second question) perceived by each SKPD representative are as follows:

• A more detailed explanation
• The previous data collection method was inaccurate as well as the accuracy of the data used was doubtful
• Finding new thinking perspectives
• Generate data requires a planning process to verification to analysis
• The information obtained increases
• Adding alternative insights
• Having a little bit easier way to obtain data
• There is an option on a top priority scale to put forward
• Some participants confessed they previously didn't know the direction to achieve in preparing evidence-based policy instruments, but having attended the second meeting, they got the answers.
• The importance of data for a policymaking
• Method of collecting data
• By data collection followed by analysis, it turns out that it can form SKPD in the context of achieving the vision and mission
• If we look for data, be searchable from some source that is subsequently weighting provided
• Become more aware of how to find and collect data
• Increase knowledge about the importance of data for planning
• Data turns out to be very important to taking a stance/decision
• Become more knowledgeable about data collection methods according to the objectives to achieve. The importance of the database in determining the policies of the Rembang district in the future
• There is additional knowledge of statistics to measure the plan and success of a program

While the details of the material (information) that participants want to answer the third question are as follows:

• Types of data
• Acquiring good and accurate data collection methods as well as having instruments are used for better development of the Rembang district
• Materials related to simulation, data verification, and quality control data
• A more detailed explanation of the definitions described in the variables and instruments
• The material presented can be understood
• Carry out data/information collection as initial data for the technical guidance application
• More on theory and practice (direct implementation)
• Collecting data is straightforward
• We can provide input to the leadership after rechecking the actual conditions in the field then we could estimate budgets and prioritize human resources or infrastructure to use
• Material about AHP in making a policy
• Accurate data compilation/collection
• How to handle sampling error
• More complete modules/materials
• Making the right instrument and how to analyze the data
• Simpler delivery
• Material on how to make accurate/valid data
• More technical, not theoretical
• Making instruments in the preparation of databases, criteria/types of databases required by the local government
• Technical work on making data for the preparation of activity plans

(JF)