OJS UNPATTI Publication Center (Universitas Pattimura)
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Analysis of Public Service Innovation "Sama Thukel" by the Regional Revenue Agency of Maluku Province
Get PDFThis research aims to analyze the public service innovation "Sama Thukel" implemented by the Regional Revenue Agency of Maluku Province. Public service innovation is a critical element for improving the quality of governance and enhancing the public's trust in government institutions. "Sama Thukel" is a digital-based public service innovation designed to facilitate taxpayers' access to regional tax services, ensuring efficient and transparent processes. Through qualitative methods, including interviews and document analysis, the study explores the design, implementation, challenges, and impact of this innovation on taxpayers and the agency itself. The findings reveal that the "Sama Thukel" program has significantly improved taxpayer compliance, reduced bureaucratic inefficiencies, and created a more transparent and accountable system. However, challenges remain in terms of digital literacy and the need for continuous system upgrades. This research highlights the importance of adapting public service innovations to local contexts and the role of technology in enhancing governance. The study concludes by offering recommendations for optimizing the "Sama Thukel" program and ensuring its sustainability
Strategi Pengembangan Usaha Budidaya Rumput Laut di Desa Warialau Kecamatan Aru Utara Kabupaten Kepulauan Aru
Get PDFThe aim of this research is to determine the strategy for developing seaweed cultivation businesses in Warialau village, North Aru sub-district, Aru Islands district. To evaluate the sustainability status of seaweed, it is necessary to review the ecological, economic, technological, social and institutional dimensions. This research uses two types of data collection methods, namely primary and secondary data. The results of the ecological dimension analysis show that the physical and chemical water data is in the normal range, the economic dimension shows that the average income of the community is not proportional to the expenditure from seaweed cultivation activities, namely IDR 1,825,000 from capital of IDR 2,800,000. The technology used is relatively simple, both for the seeds used and post-harvest handling. Measurement of the social dimension shows that the majority of the community is at senior high school level 57.1%, followed by junior high school 22.9%, elementary school 14.3% and undergraduate 5.7%. The cultivation system is carried out individually because there is no official institution regarding seaweed development in the future. SWOT and AHP Rapfish were used to test the sustainability of seaweed cultivation businesses in Warialau Village. The Rapfish test results show a 60.5% chance of sustaining cultivation in a good direction, the biggest threat is 40% from pests and diseases. The SWOT test results show total strengths of 1.13 and weaknesses of 11.35
Forgiveness and Emotional Well-Being: A Study of Parents of Children with Autism Spectrum Disorders
Get PDFThis study investigates the relationship between forgiveness and subjective well-being among parents of children with autism spectrum disorders (ASD). Using a quantitative correlational approach, the research aims to determine whether forgiveness significantly impacts the subjective well-being of these parents. The study involved 43 participants from SLBN 1 Palangka Raya, who completed questionnaires measuring forgiveness (Heartland Forgiveness Scale) and subjective well-being (SAPAN and SWLS scales). Descriptive statistics revealed high levels of forgiveness and subjective well-being among participants. However, Pearson correlation analysis indicated no significant relationship between the two variables. This suggests that while parents exhibit high forgiveness, it does not necessarily translate to increased life satisfaction or emotional balance. Subjective well-being is influenced by multiple factors, including gratitude, personality, self-esteem, spirituality, and social support. The study highlights the need for further research to explore these additional factors and address limitations such as incomplete samples and participant confusion during data collection. These insights are crucial for supporting the psychological well-being of parents with children who have special needs
Nomophobia and Self-Esteem: A Study of Migrant Students' Psychological Well-Being
Get PDFThe transition from high school to higher education represents a significant milestone for adolescents, often accompanied by migration to access better educational opportunities, known as "merantau." This phenomenon, prevalent among students aged 18-24, is associated with a high prevalence of nomophobia, characterized by anxiety and discomfort when separated from smartphones. This study aims to explore the relationship between self-esteem and nomophobia tendencies among migrant students, given the mixed findings in existing literature. Employing a correlational quantitative research design, data were collected from 153 migrant students using the Nomophobia Questionnaire (NMP-Q) and the State Self-Esteem Scale (SSES). Descriptive analysis revealed that 74.5% of students exhibited moderate nomophobia tendencies, while 62.7% had high self-esteem. Pearson's correlation analysis indicated a significant negative relationship between self-esteem and nomophobia tendencies (r = -0.222, p = 0.006), suggesting that higher self-esteem is associated with lower nomophobia tendencies. This finding underscores the importance of enhancing self-esteem to mitigate nomophobia, highlighting the role of positive self-perception and real-life social interactions. Despite limitations such as the online data collection method, this study provides valuable insights into the psychological dynamics between self-esteem and nomophobia among migrant students, advocating for targeted interventions to address these issues
Exploring the Impact of Conformity on Impulsive Buying: Implications for Counseling Practices
No full textGiven the increasing prevalence of impulsive buying behavior among football supporters, understanding the underlying social influences becomes crucial for effective intervention. This study examines the relationship between conformity and impulsive buying behavior among football supporters in Salatiga. Using a quantitative correlational design, data was collected from 106 participants via an online questionnaire distributed through social media. The findings reveal a significant positive relationship between conformity and impulsive buying, with 49.1% of participants exhibiting high conformity and 55.7% displaying high impulsive buying behavior. The effective contribution of conformity to impulsive buying was 82%, indicating that peer pressure and social dynamics significantly influence buying behavior. The study suggests that counselors should develop targeted interventions to help individuals manage conformity pressures, enhance self-awareness, and make more rational purchasing decisions. The research highlights the need for financial literacy education and supportive group counseling sessions to address the psychological and practical aspects of impulsive buying. However, the study's limitations include its focus on a specific demographic and potential biases in self-reported data, necessitating further research to generalize the findings
Rebuilding Harmony: Social Interactions After the Maluku Conflict
Get PDFThe purpose of this study was to determine the dynamics of social interactions that were passed down from previous generations in students of the BK Study Program after the Maluku conflict. The research method used a qualitative approach with in-depth interviews with students whose families experienced the conflict in Maluku directly in 1999-2002. Through coding analysis, the research identified thematic patterns and meanings that emerged from students' narratives. Based on the results of the study, it was found that the social interaction of post-conflict Counseling students both individually and in groups can be established with active communication between students of different religions with tolerance as an attitude to maintain harmony in social relations during the study period and emphasize the need for integration of social aspects reflected in the study program curriculum so that the unique experience of each post-conflict student passed down from generation to generation can adapt to the campus environment commonly dubbed the "campus of basudara people"
Ethnopharmacy and Traditional Knowledge Study with a Family Use Value Approach in Sumberbrantas Village, Bumiaji District, Batu City, East Java
No full textIndonesia is recognized as one of the world’s most biodiverse countries, with an estimated 17% of global plant and animal species found within its borders. This biodiversity supports a wealth of medicinal plants that have been traditionally utilized by local communities. However, rapid modernization has led to a decline in the transmission of ethnobotanical knowledge. This study investigates the ethnopharmacological practices in Sumberbrantas Village, Bumiaji District, Batu City, East Java, with a focus on the Family Use Value (FUV) approach to identify the most utilized plant families in traditional medicine. Data were collected through structured interviews with 70 respondents selected using purposive and snowball sampling techniques. The study analyzed the FUV and Fidelity Level (FL) of various plant species to determine their significance in traditional healing practices. Results indicate that the Zingiberaceae and Euphorbiaceae families have the highest FUV (0.45), highlighting their widespread use in treating various ailments. Conversely, the Oxalidaceae family exhibits the lowest FUV (0.01). The FL analysis shows that Allium cepa (shallot) has the highest fidelity level (75%), demonstrating its prominence in treating multiple conditions. This research provides critical insights into the preservation of ethnomedicinal knowledge and the sustainable use of medicinal plant resources. The findings serve as a valuable reference for conservation efforts and the development of community-based herbal medicine initiatives
Phytoremediation of Lead (Pb) Particulate as a Nature-Based Solution for a Healthier Environment
No full textLead (Pb) particulates are a serious environmental issue due to their impact on health and ecosystems. These pollutants stem from emissions of vehicles, industries, and mining. This study aims to explore the potential of plants as phytoremediators of Pb used a literature review with data triangulation from scientific journals and institutional reports. Content analysis, tabulation, and exploratory descriptive analysis were conducted. Lead, with an atomic number of 82 and an atomic weight of 207.20, is a hazardous metal that can cause kidney damage, hypertension, anemia, nerve damage, reduced fertility, miscarriages, and lower IQ. Pb particulates can adhere or fall on leaf surfaces and are absorbed through stomata. This process occurs because the size of Pb particulates (0.2-4 µm) allows them to be absorbed through stomatal openings (2-10 µm) when they open to take in CO2, thus allowing Pb to enter and accumulate in plant tissues. Through this physiological mechanism, plants can be used as effective solutions for absorbing Pb. Some plants with high effectiveness include Polyaltia longifolia, Swietenia macrophylla, and Bougainvillea spectabilis. Planting these species in industrial zones and roads can improve air quality and provide ecosystem benefits, such as clean air, habitat space, thermal comfort, and aesthetic value
APPLICATION OF THE PRINCIPAL COMPONENT ANALYSIS-VECTOR AUTOREGRESSIVE INTEGRATED (PCA-VARI) MODEL TO FORECASTING ECONOMIC GROWTH IN INDONESIA
No full textIndonesia's economic growth has undergone significant fluctuations in recent years, driven by global shocks such as the 2020 COVID-19 pandemic, the 2013 taper tantrum, and the 2022 global energy crisis. These events underscore the urgent need for more accurate and robust forecasting models to support economic stability and policymaking. This study applies the Principal Component Analysis-Vector Autoregressive Integrated (PCA-VARI) model to forecast economic growth in Indonesia. PCA reduces seven economic variables into two principal components for ten years (2012-2022). The results show that the first component (PC1) shows the highest correlation with the variables of Money Supply, BI Rate, and Foreign Exchange Reserves, which reflect monetary policy and financial stability. Meanwhile, the second component (PC2) is highly correlated to the GDP Index, Exchange Rate, and Inflation variables, which reflect macroeconomic conditions. VARI, as a non-stationary multivariate time series model, is used to model the relationship between these components, with the third-order lag selected as the optimal lag based on the Akaike Information Criterion (AIC), Hannan-Quinn Criterion (HQ), and Final Prediction Error (FPE) values. The results show that the PCA-VARI(3) model is able to provide highly accurate forecasting with a MAPE of 1.21% for PC1 and 1.34% for PC2, and has met all the necessary model assumptions
HYBRID ARIMA–ANN MODEL FOR AIR QUALITY INDEX PREDICTION IN DKI JAKARTA
No full textAir pollution is a threat to all countries, including Indonesia. One area in Indonesia with poor air quality is DKI Jakarta. One step to minimize the decline in air quality in an area is to predict the air quality index in the future. In this study, a hybrid ARIMA-ANN analysis was conducted, combining the ARIMA method and Artificial Neural Networks to model air quality in DKI Jakarta. The time series data of the air quality index sourced from the DKI Jakarta Environmental Service during January 19-30, 2023, which was observed every hour with a total of 288 data. The results of the study showed that the SAE and RMSE of the ARIMA model were 94.135 and 1.157, respectively, while the SAE and RMSE values of the hybrid ARIMA-ANN model were 61.094 and 1.15. The results of the study showed that the hybrid ARIMA-ANN model had a higher accuracy value compared to the single ARIMA model in describing DKI Jakarta air quality data. This study has limitations in that determining the network architecture in the ANN model is still done by trial and error, so it takes a relatively longer time