OJS UNPATTI Publication Center (Universitas Pattimura)
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Perlindungan Hukum Terhadap Pekerja Disabilitas: Tinjauan Undang – Undang Cipta Kerja
Get PDFLegal protection for workers with disabilities in Indonesia is a crucial issue in achieving equality and inclusion in the workplace. Law Number 8 of 2016 on Persons with Disabilities and Law Number 11 of 2020 on Job Creation mandate companies to employ persons with disabilities. Private companies are required to employ at least 1% of workers with disabilities, while government institutions must employ a minimum of 2%. This obligation is not merely about fulfilling quotas but must also be accompanied by the provision of an accessible work environment, such as disability-friendly infrastructure, assistive work tools, and policies that support their career development. This study aims to analyze the legal protection for workers with disabilities based on the Job Creation Law. The research method used is normative legal research with a statute approach. This study examines how regulations guarantee the rights of workers with disabilities, including equal wages, protection from discrimination, and reasonable workplace accommodations. The findings indicate that the Job Creation Law strengthens the rights of workers with disabilities by ensuring equal pay with other workers who have similar responsibilities. Furthermore, regulatory oversight and law enforcement mechanisms are established, including administrative sanctions for companies that fail to comply. As an incentive, the government provides tax relief and facility assistance for companies that actively employ persons with disabilities. This study concludes that although regulations are in place, their effectiveness still needs to be improved through strict supervision and broader education for the business sector
MODELING HOUSE SELLING PRICES IN JAKARTA AND SOUTH TANGERANG USING MACHINE LEARNING PREDICTION ANALYSIS
Get PDFThe increasing demand for housing in urban agglomerations, particularly in areas like Jakarta, has made homeownership a significant challenge for many, especially first-time buyers and the lower-middle class. Post-pandemic shifts have further influenced housing preferences, driving interest towards suburban areas with green spaces. Despite government efforts through mortgage subsidy programs, affordability remains a concern, particularly in peripheral regions. This study aims to analyze housing prices in various Jakarta regions using machine learning models, including Multiple Linear Regression (MLR), Support Vector Regression (SVR), Light Gradient Boosting Machine (LGBM), and Random Forest. A dataset of 554 house prices from West Jakarta, South Jakarta, Central Jakarta, and South Tangerang was used. The analysis focused on key predictors like land area, building area, bedrooms, and carports, with R² and Mean Squared Error (MSE) metrics evaluating model performance. Results showed that LGBM and Random Forest outperformed others with 0.8 R2 and low MSE, with building and land area as the most significant factors influencing prices. The study concludes that property size is a primary determinant of house prices, and there is a need for policy interventions to make housing more affordable. Additionally, apartment rentals offer a viable alternative, especially in central urban areas, where proximity to economic activities and facilities is crucial. The findings suggest that enhancing marketplace features with predictive tools could further assist buyers in making informed decisions
COMPARING FORECASTS OF AGRICULTURAL SECTOR EXPORT VALUES USING SARIMA AND LONG SHORT-TERM MEMORY MODELS
Get PDFIndonesia's agricultural sector plays a crucial role in the national economy, with significant export potential and supporting the livelihoods of the majority of the population. As part of the government's vision to make Indonesia the world's food barn by 2045, increasing the volume and value of agricultural product exports is a primary focus, making export value forecasting essential for supporting strategic decision-making. Sequential data analysis is an important approach in analyzing data collected over a specific period. This study aims to compare two popular methods in forecasting the export value of the agricultural sector, namely the Seasonal AutoRegressive Integrated Moving Average (SARIMA) model and the Long Short-Term Memory (LSTM) model. Monthly agricultural export data from West Java Province from January 2013 to February 2024 were used as the dataset. The best SARIMA model generated was (1,1,1)(0,1,1)12, while the optimal parameters for the LSTM model were neuron: 50, dropout rate: 0.3, number of layers: 2, activation function: relu, epochs: 500, batch size: 64, optimizer: Adam, and learning rate: 0.01. Evaluation was performed using the Root Mean Squared Error (RMSE) method to measure the accuracy of both models in forecasting the export value of the agricultural sector. The results showed that the LSTM model outperformed the SARIMA model, with a lower RMSE value (SARIMA: 4182.133 and LSTM: 1939.02). This research provides valuable insights for decision-makers in planning agricultural sector export strategies in the future. With this comparison, it is expected to provide better guidance in selecting forecasting methods suitable for the characteristics of the data
THE NON-COPRIME GRAPHS OF UPPER UNITRIANGULAR MATRIX GROUPS OVER THE RING OF INTEGER MODULO WITH PRIME ORDER AND THEIR TOPOLOGICAL INDICES
Get PDFIn its application graph theory is widely applied in various fields of science, including scheduling, transportation, industry, and structural chemistry, such as topological indexes. The study of graph theory is also widely applied as a form of representation of algebraic structures, including groups. One form of graph representation that has been studied is non-coprime graphs. The upper unitriangular matrix group is a form of group that can be represented in graph form. This group consists of upper unitriangular matrices, which are a special form of upper triangular matrix with entries in a ring R and all main diagonal entries have a value of one. In this research, we look for the form of a non-coprime graph from the upper unitriangular matrix group over a ring of prime modulo integers and several topological indexes, namely the Harmonic index, Wiener index, Harary index, and First Zagreb index. The findings of this research indicate that the structure of the graph and the general formula for the Harmonic index, Wiener index, Harary index, and First Zagreb index were successfully obtained
3D MODELING COMPUTATION TO EVALUATE GROYNE STRUCTURE PERFORMANCE: CASE STUDY OF PASSO COASTAL AREA
Get PDFGroyne is very important to protect the coastline with the concept of maintaining the balance of sediment transport. Groyne building in theory can work well if worked in groups or more than one. In this study, the Passo beach location was chosen because there is an existing groyne building that, if seen on Google Earth, has been damaged by the scattering of the constituent rocks. If the groyne cannot work to balance the sediment transport, it may occur that mass destruction to the infrastructure behind the groyne itself, such as regional roads, may occur. To find out the level of damage, an in-depth study needs to be carried out. In this paper, Delft-3D mathematical modeling was carried out to investigate groyne damage by looking at the performance of groyne in maintaining the balance of sediment transport in the Passo beach area. Hydrodynamic and coastal sediment modeling analyses were carried out in wet and dry season conditions. Modeling was carried out over one month with a morphology factor of 12 to obtain sediment transport for one year. In the existing dry season conditions, it shows that at the observation point, there is erosion of 2 meters, and in the wet season sediment transport is balanced. It is implied that the groyne structure must be replaced for being surpass the structure lifetime
Chemical Constituent and Antioxidant Activity of Clove (Syzygium aromaticum) Bud and Leaf Essential Oils from Bali
Get PDFBali is one of clove (Syzygium aromaticum) producers in Indonesia. Clove essential oil is mainly produced from the leaves and flowers. Eugenol is the main component in the essential oil of clove. The objective of this research is to determine constituents and antioxidant activity of clove’s bud and leaf essential oils from Bali. The essential oils were isolated from clove’s bud and leaf samples by steam distillation with the yield of 12.90 and 2.63%. The constituents of the clove essential oils were analyzed by using gas chromatography-mass spectrometry (GC-MS). Thirty-six and twenty-nine constituents were identified based on GC-MS from the clove bud and leaf essential oils, respectively. Major classes of compounds are sesquiterpenes, phenyl propanoids, oxygenated sesquiterpenes, and esters. Different compositions in major constituents were found between both essential oils. Clove bud essential oil (CBEO) contained eugenol (65.29 %), trans-caryophyllene (20.06 %), and α-humulene (3.38 %). While, in clove’s leaf essential oil (CLEO), the composition was eugenol (64.47 %), trans-caryophyllene (27.19 %), and α-humulene (3.62 %). The clove essential oil and its main component show strong antioxidant activity. The antioxidant activity of CBEO, CLEO, and eugenol is 22.58, 29.19, and 17.53 μg/mL, respectively
Efektivitas Model Pembelajaran PBL (problem based learning) Pada Materi Larutan Elektrolit dan Non Elektrolit Terhadap Hasil Belajar Siswa Kelas X SMA Negeri 3 Ambon
Get PDFTujuan dalam penelitian ini adalah untuk mengetahui efektivitas model pembelajaran PBL (problem based learning) pada materi larutan elektrolit dan non elektrolit terhadap hasil belajar siswa kelas X SMAN 3 Ambon. Penelitian ini adalah penelitian eksperimen dengan jenis desain eksperimen murni (true experiment design). Model eksperimen yang digunakan adalah pretest-posttest control group design dengan satu macam perlakuan. Sampel dalam penelitian ini adalah siswa kelas X SMAN 3 Ambon dimana kelas X IPA³ sebagai kelas eksperimen dan kelas X IPA4 sebagai kelas kontrol. Teknik pengumpulan data dalam penelitian ini adalah tes dan non tes. Hasil penelitian diperoleh hasil belajar siswa untuk kelas eksperimen dengan rata-rata nilai sebesar 80,06, sedangkan untuk kelas kontrol memperoleh rata-rata nilai sebesar 67,46, dengan demikian terdapat perbedaan antara model PBL dan model pembelajaran konvensional yang signifikan, yang dibuktikan dengan hasil uji-t sig 0,000 < 0,05. Hal ini menunjukan bahwa model pembelajaran PBL (Problem Based Learning) yang diterapkan efektif terhadap hasil belajar kimia siswa
Ekstraksi Fitur Objek Tutupan Lahan Menggunakan Citra Satelit Resolusi Tinggi (Studi Kasus : Daerah Desa Argomulyo, Yogyakarta)
Get PDFCitra beresolusi tinggi merupakan generasi terbaru dalam teknologi penginderaan jauh yang menawarkan daya tarik lebih besar, memberikan peluang baru, dan memungkinkan pemetaan serta estimasi area tutupan lahan dengan tingkat akurasi yang lebih tinggi dibandingkan citra beresolusi menengah maupun rendah. Klasifikasi citra adalah sebuah proses yang digunakan untuk menghasilkan model peta tematik berdasarkan data citra satelit. Tema yang dihasilkan dapat mencakup berbagai kategori, seperti: lahan, vegetasi, dan air permukaan untuk gambaran umum wilayah pedesaan, hingga klasifikasi yang lebih spesifik. Ekstraksi fitur adalah suatu teknik yang digunakan untuk memperoleh atribut atau karakteristik spesifik dari sebuah objek, di mana hasil dari proses ini akan dianalisis lebih lanjut pada tahap selanjutnya. Kajian ini memusatkan perhatian pada proses ekstraksi fitur dari dataset citra, yang kemudian dimanfaatkan untuk mengklasifikasikan objek berdasarkan jenis tutupan lahannya. Kajian ekstraksi fitur dilakukan dengan menggunakan data citra satelit Pleiades. Interpretasi visual dilakukan dengan menggunakan komposit band merah, band hijau, band biru serta band NIR yang dipadukan dengan band pankromatik. Nilai piksel menjadi data input dalam proses interpretasinya. Hasilnya dapat disimpulkan bahwa metode ekstraksi fitur efektif untuk mengklasifikasi tutupan lahan sesuai dengan kelas yang telah ditentukan
Dampak Faktor Sosial Ekonomi terhadap Perubahan Tutupan Lahan di Daerah Aliran Sungai Waerupa, Negeri Hukurila, Kota Ambon
Get PDFPerubahan tutupan lahan merupakan fenomena yang signifikan dalam dinamika ekosistem daerah aliran sungai. Perubahan ini dipengaruhi oleh berbagai faktor, termasuk aspek sosial ekonomi masyarakat yang menghuni kawasan tersebut. Penelitian ini bertujuan untuk menganalisis dampak faktor sosial ekonomi, yang meliputi umur, pendidikan, pekerjaan, pendapatan, dan jumlah tanggungan keluarga, terhadap perubahan tutupan lahan (hutan, lahan pertanian, permukiman), perkembangan aksesibilitas, dan pertumbuhan penduduk. Metode penelitian menggunakan pendekatan kuantitatif dengan analisis regresi linear berganda untuk menguji hubungan antara variabel sosial ekonomi dan perubahan tutupan lahan. Uji statistik meliputi uji asumsi klasik (multikolinearitas, heteroskedastisitas, dan autokorelasi), uji regresi, dan uji parameter individu untuk menguji pengaruh variabel independen terhadap variabel dependen. Hasil penelitian menunjukkan bahwa variabel pekerjaan dan pendapatan memiliki pengaruh signifikan terhadap perubahan tutupan hutan, lahan pertanian, dan permukiman. Jumlah tanggungan keluarga juga ditemukan signifikan dalam memengaruhi perkembangan aksesibilitas. Sementara itu, variabel pendidikan menunjukkan pengaruh yang tidak signifikan terhadap semua kategori perubahan tutupan lahan. Uji koefisien determinasi (adjusted R²) mengungkapkan bahwa variabel sosial ekonomi secara keseluruhan mampu menjelaskan perubahan tutupan lahan pada hutan sebesar 96%, lahan pertanian 94,8%, permukiman 98,4%, aksesibilitas 90,1%, dan pertumbuhan penduduk 91,8%. Berdasarkan hasil tersebut, penelitian ini merekomendasikan pengembangan kebijakan berbasis sosial ekonomi untuk mendukung pengelolaan lahan yang berkelanjutan di DAS Waerupa. Pemerintah daerah diharapkan memberikan perhatian khusus pada peningkatan pendidikan masyarakat, diversifikasi pekerjaan, dan pengelolaan pendapatan yang lebih baik untuk mengurangi tekanan pada sumber daya lahan. Penguatan aksesibilitas infrastruktur juga perlu diimbangi dengan perlindungan kawasan hutan dan pertanian untuk menjaga keseimbangan ekosistem di wilayah tersebut
Toward a Smart City Pontianak: A Study of Digital Governance Effectiveness as a Moderator of the Relationship Between Work Culture, HR Management, and Public Satisfaction
Get PDFThis study examines the impact of implementing a digital government system as a strengthening factor in the relationship between organizational work culture and human resource management on public satisfaction levels in Pontianak City. The research aims to understand the effectiveness of digital governance in supporting government organizational performance to achieve a more optimal smart city concept. The research method used is quantitative research with an explanatory survey approach, involving 378 respondents selected through a proportional stratified random sampling method. Data collection was conducted using a structured questionnaire, and data analysis was carried out using Structural Equation Modeling (SEM) techniques processed with the SmartPLS version 4.0 application. The study results show that the successful implementation of a digital government system significantly strengthens the influence of work culture on public satisfaction levels. The findings also indicate that the synergy between digital government systems, organizational work culture, and human resource management can increase the public satisfaction index by up to 42.3% compared to traditional methods. This research contributes to the development of social humanities sciences, particularly in understanding the role of digital governance as a reinforcement in the relationship between human resource management and public satisfaction in urban contexts moving towards smart cities