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PENGARUH UPAH TERHADAP KINERJA KARYAWAN LEPAS PADA PT. MILION LIMBAH AMBON DI NEGERI HUTUMURI KECAMATAN LEITIMUR SELATAN KOTA AMBON
Full text linkPenelitian ini bertujuan untuk menginvestigasi pengaruh upah terhadap kinerja karyawan di PT.Milion Limbah Ambon, yang berlokasi di Negeri Hutumuri, Kecamatan Leitimur Selatan, Kota Ambon. Penelitian ini menggunakan kuesioner sebagai instrumen untuk mengumpulkan data. Metode analisis data yang diterapkan meliputi uji instrumen, uji hipotesis, dan analisis regresi linear sederhana untuk menguji pengaruh variabel independen terhadap variabel dependen. Hasil pengujian instrumen penelitian menunjukkan bahwa semua item pernyataan untuk variabel upah dan kinerja karyawan adalah valid berdasarkan uji validitas. Uji reliabilitas juga menunjukkan bahwa variabel upah dan kinerja karyawan memiliki nilai Cronbach's Alpha > 0,60, sehingga dinyatakan reliabel. Analisis data yang dilakukan menggunakan regresi linear sederhana juga menunjukkan bahwa upah berpengaruh positif dan signifikan terhadap kinerja karyawan, Penelitian ini melibatkan seluruh karyawan lepas sebagai populasi, dengan sampel penelitian sebanyak 70 responden untuk menganalisis hubungan antara upah dan kinerja karyawan
ANALYSIS OF SMOKING AND COVID-19 MATHEMATICAL MODEL
Full text linkSmoking and COVID-19 have similar effects in the body system, i.e. damaging the airways and lung function. In this work, a mathematical model to study smoking and COVID-19 transmission was studied. The model was proven to have feasible region and it is well-posed mathematically and epidemiologically, the model was further proven to have positive solutions. The basic reproduction number was computed using the next generation method and sensitivity analysis was carried out. The results show that the disease-free equilibrium is locally and globally stable, the most sensitive parameter is the contact rate. The simulation shows that, curtailing rate of contact between exposed, infected individuals and susceptible human population will reduce the spread of the diseases, also giving attention to recovery strategies and controls will reduce to minimum the disease transmission. Therefore, it is recommended that stakeholders should give attention in controlling smoking habits, and prevention and treatment of COVID-19 infected individuals
ENHANCING LQ45 STOCK PRICE FORECASTING USING LSTM MODEL
Full text linkStocks listed in the LQ45 index represent companies with high liquidity, large market capitalization, and strong fundamentals, making them pivotal to the movements of the Indonesian capital market. This study selects eight LQ45-listed stocks from the energy and mining sectors, as well as the banking sector. Historical data spanning a 10-year period from February 28, 2015, to February 28, 2025. This research aims to mitigate the impact of stock market dynamics, a significant challenge for investor decision-making. The Long Short-Term Memory (LSTM) method was employed to forecast stock prices using four variables: opening, highest, lowest, and closing prices. The LSTM architecture was chosen because its gated memory cells can effectively capture long‑term dependencies and nonlinear patterns in financial time series, thereby aligning with the research objective of minimizing forecasting error under volatile market conditions. Evaluation results using the Mean Absolute Percentage Error (MAPE) showed prediction errors below 2.5%, indicating relatively low forecasting error. Root Mean Squared Error (RMSE) values varied depending on stock price volatility. Companies exhibiting higher stock prices, such as Indo Tambangraya Megah Tbk (ITMG), demonstrate larger RMSE values. For opening prices, predictive accuracy was notably strong, with MAPE values consistently below 1.26%. This suggests that opening prices, influenced by pre-market sentiment and historical data, are more stable and easier to predict compared to other price variables
Tanggung Jawab Marketplace Terhadap Penjualan Barang Secara Online
Full text linkCurrently, there is a lot of use of the internet for commerce among the public which is a means of online buying and selling. It is regulated in the Civil Code, Law Number 8 of 1999 concerning Consumer Protection, Law Number 19 of 2016 concerning amendments to Law Number 11 of 2008 concerning Information and Electronic Transactions, Government Regulation Number 8 of 2019 concerning Trading Through Electronic Systems. However, there are still many violations that are committed to the detriment of buyers and sellers. Based on this research, online marketplaces allow sellers and buyers to interact and carry out transactions online, facilitating the buying and selling process and increasing sales capabilities, but the parties involved in buying and selling on the marketplace do not comply with statutory regulations so it can be concluded that the actions that have been taken carried out by each party can cause losses to each party intentionally or unintentionally. The responsibility of the marketplace is to provide compensation and compensation for goods received that do not comply with the agreement
Pendampingan Guru Madrasah dalam Pengembangan Konten Pembelajaran Digital Berbasis Nilai Keislaman dan Literasi Global
Full text linkThis community service program was conducted to enhance madrasah teachers’ competence in integrating Islamic values and global literacy into digital learning content. The background arises from teachers’ limited ability to utilize technology meaningfully and contextually in Islamic-based education. The objective is to strengthen teachers’ capacity to design, produce, and implement value-oriented digital instructional media. The method applied was Participatory Action Research through training, mentoring, classroom supervision, and the establishment of an Islamic digital teacher community. Results show significant improvements in technological mastery (+70.8%), Islamic value integration (+65.4%), and global literacy (+77.3%), along with a positive shift in teaching culture. This activity demonstrates that value-based mentoring and community collaboration effectively foster creative, reflective, and adaptive madrasah teachers in the digital era. The model implies practical policy relevance for enhancing Islamic teachers’ professionalism and can be replicated nationally
Peran Pemerintah Daerah Seram Bagian Barat dalam Mengoptimalkan Pasar Kairatu
Full text linkTujuan penelitian ini adalah untuk mengetahui peran pemerintah daerah dalam mengoptimalkan Pasar Kairatu dan menilai dampak pasar jika tidak dioptimalkan. Perekonomian masyarakat Kairatu sangat bergantung pada pasar, terutama bagi masyarakat kelas menengah ke bawah, yang memanfaatkannya untuk kegiatan jual beli guna memenuhi kebutuhan pokok sehari-hari. Penelitian kualitatif deskriptif ini dilakukan di Seram Bagian Barat dengan menggunakan teknik pengumpulan data berupa observasi, wawancara, dan dokumentasi, dengan melibatkan perangkat desa (kepala desa) dan 10 pedagang di Pasar Kairatu sebagai subjek penelitian. Hasil penelitian menunjukkan bahwa peran pemerintah daerah Seram Bagian Barat dalam mengoptimalkan Pasar Kairatu sangat krusial bagi para pedagang di wilayah tersebut. Para pedagang di Pasar Kairatu telah beroperasi selama 9 bulan dan memilih lokasi ini karena mereka merasa nyaman berjualan di sana, meskipun saat ini jumlah pengunjungnya masih rendah. Pemerintah desa telah menjalin komunikasi dengan masyarakat Kairatu melalui pertemuan langsung di balai desa untuk mendorong transaksi jual beli di Pasar Kairatu. Namun, warga cenderung berbelanja di pasar lain, sehingga aktivitas pasar menjadi kurang optimal. Pasar Kairatu memiliki potensi untuk ditingkatkan guna meningkatkan peluang tawar-menawar dan fungsionalitas secara keseluruhan
ANALYSIS OF APRIORI AND K-NEAREST NEIGHBOR (KNN) ALGORITHM IN RECOMMENDING APPROPRIATE LEARNING METHOD
Full text linkThe study investigates the utilization of data mining techniques, especially the Apriori algorithm and K-Nearest Neighbor (KNN) classification, in recommending appropriate learning methods based on student data. The purpose of this research is to analyze patterns and groupings in students’ behavior, preferences, and academic performance to support more informed and personalized educational strategies. The Apriori algorithm is used to identify frequent associations among learning related attributes, while KNN classification helps group students with similar learning characteristics. The analysis revealed that the digital learning method is the most preferred by students, with a percentage of 84.29%, followed by the traditional lecture method at 15.70%. These results reflect a notable trend toward technology-driven, flexible learning environments, although conventional approaches continue to hold relevance for a portion of learners. The research concludes that the integration of the Apriori algorithm and KNN clustering proves to be an effective analytical framework for facilitating adaptive learning. This approach allows educators and institutions to make data-driven decisions in tailoring instructional methods that align with the diverse needs and preferences of students
FORECASTING INDONESIA COMPOSITE INDEX USING HYBRID AUTOREGRESSIVE INTEGRATED MOVING AVERAGE-DOUBLE RANDOM FOREST MODEL
Full text linkModeling time series data using autoregressive integrated moving average (ARIMA) has been widely discussed. However, this has limitations in that it can only handle linear data. Machine learning is one of the alternative approaches that can solve this limitation since this method can handle nonlinear cases. Double random forest (DRF) is considered a supervised learning method that can solve regression problems. This research provides a novel hybrid forecasting framework combining ARIMA and DRF, designed to model both linear and nonlinear behaviors, and provide more accurate predictions for volatile financial data like the Indonesia Composite Index (ICI). Previous studies have not examined the performance of the hybrid ARIMA-DRF model. In this study, the performance of ARIMA, DRF, and the hybrid ARIMA-DRF models is compared using ICI data obtained from Bank Indonesia’s website. ICI has nonstationary and nonlinear characteristics. This made the ICI data suitable to be modeled using the hybrid ARIMA-DRF model. The comparison results indicate that the hybrid ARIMA-DRF model outperforms the independent ARIMA and DRF models, with a value of its mean absolute percentage error is 4.17%. Therefore, forecasting the future value of ICI data was done by using a hybrid ARIMA-DRF model with forecasting periods from October 2023 to September 2024. The forecasting results show that ICI values fluctuate over the forecasting periods, hence the authority might use the pattern to predict the ICI behaviors and take further decisions. While the forecasting results offer valuable insights for decision-making, this study has limitations as it does not incorporate external macroeconomic variables that may influence ICI behavior
ESTIMATING MODULARITY BOUNDS FOR HOMOPHILIC SCALE-FREE NETWORKS
Full text linkThe problem of estimating the modularity boundaries for networks that are both homophilic and scale-free is considered. The key property of homophilic networks is the tendency of nodes to link with similar nodes, i.e., belonging to the same community. Thus, homophily is a natural mechanism for community formation, i.e., network structuring. One of the measures of network structuring is modularity. In homophilic networks, not only can the distribution of node degrees be scale-free, but also the distribution of community sizes. In this case, communities can differ significantly in size, which leads to narrowing the achievable modularity boundaries. Estimates of the modularity boundaries of networks of the considered class are obtained. Mathematically strict estimates contain non-elementary functions, which complicates the practical application of such estimates. Approximate estimates with high (0.005) accuracy for the most characteristic values of network parameters are obtained
Beyond the Ice: Value Chains and Strengthening the Competitiveness of Ambon Frozen Fish
Full text linkThe frozen fish industry in Ambon Island plays a vital role in sustaining coastal economies while integrating into Indonesia’s global seafood trade network. This study examines the structure and governance of the frozen fish value chain to understand value distribution, institutional roles, and competitiveness challenges faced by local industries. Data were collected through field observations, stakeholder interviews, and value chain mapping. The findings reveal that buyers and exporters in Surabaya hold dominant control over pricing and quality standards, while fishermen and local processors remain in weak bargaining positions due to limited capital and logistics infrastructure. The regional government, through the Regional Inflation Control Team (TPID), acts as a balancing mechanism between export demands and domestic supply, although its effectiveness is constrained by institutional coordination. Two major structural issues were identified: high logistics costs and dependence on a single buyer. To enhance competitiveness, an integrated strategy is required, combining supply chain efficiency, market diversification, cold-chain infrastructure strengthening, and the adoption of traceability and digital value chain systems to support the development of geographical branding for Ambon’s fishery products. The study highlights the necessity of a structural shift toward a value-based, sustainable, and inclusive fisheries economy