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Larangan Perkawinan dalam Perjanjian Pela Darah antara Abio, Ahiolo, Walakone, dan Rumbelu Ditinjau dari UU. Nomor 39 Tahun 1999
No full textTradisi pela darah di Maluku merupakan perjanjian persaudaraan antar-negeri yang mengatur kewajiban sosial dan larangan perkawinan antar-negeri se-Pela. Penelitian ini bertujuan menganalisis larangan perkawinan dalam pela darah dari perspektif hak asasi manusia (HAM) dan mekanisme penyelesaian pelanggaran adat yang diterapkan masyarakat. Jenis penelitian ini deskriptif kualitatif, dengan lokasi di Negeri Abio, Ahiolo, Walakone, dan Rumbelu, Kabupaten Seram Bagian Barat. Subjek penelitian meliputi tokoh adat, tokoh masyarakat, dan keluarga yang terikat tradisi pela darah. Data dikumpulkan melalui observasi dan wawancara mendalam, kemudian dianalisis secara deskriptif. Hasil penelitian menunjukkan bahwa pela darah lahir dari kesepakatan damai pascaperang antara suku Alune dan Wemale, dengan ketentuan utama berupa kewajiban saling tolong-menolong, menjamu tamu, dan larangan perkawinan antar-negeri se-Pela. Larangan perkawinan ini, meski berpotensi bertentangan dengan UU Nomor 39 Tahun 1999 tentang HAM, namun berfungsi menjaga perdamaian, identitas kolektif, dan stabilitas sosial. Penyelesaian pelanggaran dilakukan melalui musyawarah adat, ritual, dan sosialisasi kepada generasi muda. Penelitian ini menegaskan bahwa hukum adat seperti pela darah tidak bertentangan dengan prinsip HAM, melainkan dapat menjadi instrumen untuk memperkuat solidaritas sosial, menjaga keharmonisan antar-negeri, dan melestarikan tradisi budaya lokal
The Influence of Second-hand Clothing Product Quality on Consumer Satisfaction at Mardika Market, Ambon City
Get PDFThis study aims to analyze the impact of second-hand clothing quality on consumer satisfaction. Product quality was evaluated through performance, aesthetics, and durability indicators, assessed using questionnaires distributed to 50 respondents. The research employed a quantitative approach with simple linear regression analysis. The results indicated that second-hand clothing quality has a significant effect on consumer satisfaction, with a coefficient of determination of 30.3%. These findings suggest that consumers tend to be more satisfied when the quality of second-hand clothing meets or exceeds their expectations. This study emphasizes the importance of product quality in enhancing consumer satisfaction and provides recommendations for sellers to maintain quality standards and product transparency. The study also offers insights for businesses on sustainable marketing strategies in the second-hand clothing industr
The Role of Housewives in Improving the Family Economy in Waiheru Village RW 004
Get PDFThis study aims to analyze the role of housewives in improving the family economy in Waiheru Village, RW 004. Housewives play a crucial role in creating additional income sources through various economic activities, such as trading and running small businesses. Despite facing limitations in terms of capital and time, housewives in Waiheru have significantly contributed to enhancing family welfare. Based on interviews, housewives effectively manage their time between household duties and the businesses they run. Furthermore, support from husbands and other family members strengthens their role in the family's economy. Common challenges include physical fatigue; however, with high determination and innovation, housewives continue to fulfill both roles successfully. This study concludes that housewives possess substantial potential in family economic empowerment, yielding positive impacts on family welfare and strengthening the local economy
The Influence of Product Layout on Purchasing Decisions at Alfamidi Minimarket Depok Lima, Desa Poka, Teluk Ambon District
Get PDFThis study aims to analyze the effect of product layout on purchasing decisions at Alfamidi Minimarket in Desa Poka. In this research, product layout is examined through three main indicators: room space allocation, placement of tables and chairs, and product positioning. Meanwhile, purchasing decisions are measured through several stages, including problem recognition, information search, alternative evaluation, purchase decision, and post-purchase behavior. The method used in this research is a quantitative approach utilizing simple linear regression to assess the relationship between the independent variable (layout) and the dependent variable (purchasing decisions). The results show that product layout has a positive and significant influence on purchasing decisions, contributing 34.3%. This finding indicates that a well-organized product layout can enhance shopping convenience, encourage impulse buying, and ultimately, increase customer satisfactio
The Influence of Marketing Mix on Consumer Purchasing Decisions at Nita Mandiri Clothing Store, Ambon City
Get PDFThis study aims to analyze the effect of the marketing mix (product, price, promotion, and place) on consumer purchasing decisions at Nita Mandiri Clothing Store in Ambon City. This research uses a quantitative approach with the Simple Random Sampling technique, involving 97 respondents. Data were collected through questionnaires designed on a Likert scale and analyzed using SPSS 25 for validity, reliability, multiple linear regression, as well as t-test and F-test. The results show that price and place variables have a positive and significant effect on purchasing decisions, while product and promotion variables do not have a significant effect. Simultaneously, the four independent variables (product, price, promotion, and place) significantly influence consumer purchasing decisions. Therefore, optimizing competitive pricing strategies and strategic locations is essential to enhance purchasing decisions at Nita Mandiri Clothing Store. This study provides recommendations for store owners to improve promotion strategies and product innovation to attract more consumer
STRUCTURAL EQUATION MODELING ANALYSIS ON POVERTY IN WEST KALIMANTAN WITH FINITE MIXTURE IN PARTIAL LEAST SQUARE APPROACH
Get PDFPoverty occurs when individuals or groups lack the necessary resources to fulfill their basic needs. In Indonesia, including West Kalimantan, poverty remains a significant issue influenced by various socio-economic factors. This study aims to identify valid and reliable indicators of poverty and classify regencies/cities in West Kalimantan using the 2023 data from the Central Statistics Agency of West Kalimantan and Indonesia. The analysis applies the Structural Equation Modeling approach with Finite Mixture in Partial Least Squares (FIMIX-PLS). From 19 observed indicators, only 12 were found valid and reliable based on measurement and structural model evaluation. The structural model reveals three significant relationships: the Economy significantly influences Poverty, Health influences Education, and Education influences the Economy. Based on the FIMIX-PLS results, the regencies/cities are segmented into four groups with distinct structural characteristics. Segment 1 reflects the influence of Health on Education, Segment 2 reflects the influence of Health on the Economy, Segment 3 highlights the influence of Economy on Poverty, and Segment 4 captures the influence of Education on the Economy. Detailed interpretations of each segment and their policy implications are presented in the conclusion. The results support the importance of tailored poverty alleviation strategies based on latent regional characteristics and validated model findings
MODELING AND SEGMENTATION OF FACTORS AFFECTING HUMAN DEVELOPMENT IN ISLANDS OF JAVA USING FIMIX PLS METHOD WITH MEDIATION EFFECT
Get PDFHuman development is a key indicator used to assess the quality of a country's human resources. Although Indonesia's HDI has experienced a significant increase of 75.02 in 2024, inequality is still a pressing issue, especially in terms of gender representation in the workforce. This study aims to identify the influence of poverty, economic, health, employment and education factors on human development in Java Island by considering gender equality as a mediating variable. The data used in the study is limited to 119 districts/cities in Java Island and sourced from BPS publications, the Health Office and the Education Office. The novelty of this study lies in the use of the Finite Mixture Partial Least Square (FIMIX-PLS) approach with mediation effects which is rarely applied in human development research in Indonesia, as well as allowing the identification of latent population heterogeneity and region-based segmentation. The results of this method reveal two distinct district/city segments in Java, with Segment 1 dominated by the variables in this study that have significant direct and indirect effects through the mediation of gender equality on human development, while Segment 2 has characteristics that emphasize the effect of gender equality. Given these differences in characteristics, it is important that contextual and regional segmentation-based development policies are designed by local and central governments. Statistical segmentation approaches such as FIMIX-PLS make a significant contribution to more targeted policy making. By changing the type of intervention according to specific problems, the government can allocate resources more effectively. This supports the achievement of SDG-10 in reducing inequality
CLUSTER ANALYSIS OF MULTIVARIATE PANEL DATA ON DATA CONTAINING OUTLIERS
Get PDFOne clustering method for panel data is K-Means Longitudinal (KML), which considers only a single trajectory per subject over time. To address this limitation, KML was extended into K-Means Longitudinal 3D (KML3D), which enables clustering of joint or multivariate longitudinal data by considering multiple trajectories measured simultaneously for each subject. Both KML and KML3D provide new insights into clustering panel data using a non-hierarchical K-means approach. Hereinafter, this method is referred to as KML3D K-Means. KML3D K-Means implements the K-Means algorithm, specifically designed to cluster trajectories in panel data, and uses the mean as the clustering centroid. In practice, the K-Means algorithm is less effective in clustering data with outliers. This issue can be overcome by KML3D K-Medoids, a method based on KML3D that uses the median as the centroid. This study aims to determine cluster analysis for multivariate panel data on data containing outliers with KML3D K-Means and KML3D K-Medoids. Both methods are applied to panel data of social and welfare statistical data from 34 provinces observed for 8 years (2016 – 2023). The comparison of methods is based on the Calinski–Harabasz index. The results of the study show that KML3D K-Medoids has a Calinski-Harabasz index that is higher than KML3D K-Means in clustering multivariate panel data with outliers. The analysis identified three optimal clusters (k = 3) based on the Calinski–Harabasz (CH) index, which can be categorized as the “more prosperous”, “moderately prosperous”, and “less prosperous” groups. The growth rate analysis reveals disparities in development trajectories across clusters, with cluster 3 showing the most consistent improvements, cluster 1 moderate progress, and cluster 2 lagging in key social and welfare indicators
CHAOS CONTROL IN PERMANENT MAGNET SYNCHRONOUS MOTOR BY SLIDING MODEL CONTROLLER WITH LYAPUNOV OBSERVER UNDER UNKNOWN INPUTS
Get PDFThe control of chaotic and hyper-chaotic systems represents a crucial area of research in the field of nonlinear dynamic systems. In this study, we focus on applying chaos control techniques to a permanent magnet synchronous motor (PMSM), a system known to exhibit chaotic behavior under certain conditions. To achieve this, a sliding mode control (SMC) strategy integrated with a Lyapunov-based observer is proposed. The core concept involves designing a candidate Lyapunov function that governs the application of the control law, ensuring system stability while effectively suppressing chaotic dynamics. Through numerical simulations, the proposed sliding mode controller demonstrates its effectiveness in rapidly eliminating chaotic behavior and stabilizing the PMSM system toward a predefined reference trajectory. Notably, the system achieves error convergence within approximately 0.7 seconds under full control (four channels). When control channels are reduced to two, the system still maintains stability, showing flexibility and cost efficiency. In a further simulation, the chaotic PMSM is subjected to two unknown external disturbances, and the proposed controller continues to maintain stability with only a slight increase in convergence time. These quantitative results affirm the robustness, accuracy, and practicality of the proposed control method. This research confirms that integrating sliding mode control with a Lyapunov observer is an effective approach for chaos suppression in PMSMs, offering promising insights for the development of advanced control strategies in nonlinear electromechanical systems
COMPARISON OF ARIMA, EXPONENTIAL SMOOTHING, AND CHEN-SINGH FUZZY MODELS FOR INFLATION FORECASTING IN ASEAN COUNTRIES
Get PDFThis study aims to (i) develop predictive models using statistical and fuzzy approaches, and (ii) evaluate their forecasting performance. The data were obtained from www.investing.com for the period 1961 to 2017 and focus on five ASEAN countries: Indonesia, Malaysia, the Philippines, Singapore, and Thailand. The statistical models used are Autoregressive Integrated Moving Average (ARIMA) and Exponential Smoothing, while the fuzzy approaches include Chen and Singh fuzzy time series models. The dataset was divided into training and test sets in a 75%-25% proportion. ARIMA models capture trends and autocorrelations in time series data, while Exponential Smoothing uses exponentially weighted averages. Fuzzy models are designed to handle uncertainty and linguistic patterns in data. The results show that Singh’s fuzzy model yields the lowest error for Indonesia, while exponential smoothing and Chen fuzzy time series model demonstrate the same lowest error for Malaysia. For the Philippines, exponential smoothing is most accurate, whereas ARIMA and Singh fuzzy time series achieve the smallest error for Singapore. For Thailand, exponential smoothing and ARIMA perform equally well. However, the robustness of the forecasting model cannot be determined from either statistical or fuzzy methods, highlighting the challenge in determining the most robust model for inflation in the ASEAN region. The 75%-25% data split may also limit the generalizability of the findings. This study contributes a rare cross-country comparison of statistical and fuzzy forecasting methods in the ASEAN context. It highlights the importance of model selection based on country-specific inflation behavior and provides insights for improving forecasting strategies in macroeconomic applications