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Eksplorasi Asosiasi Antara Fitur Sosial dan Ekonomi dalam Keputusan Pembelian di Platform E-Commerce Menggunakan Algoritma Apriori
Get PDFDigital transformation in the e-commerce sector has driven significant changes in consumer behavior, increasingly shaped by social and economic factors. This study aims to explore the associations between socio-economic features and purchasing decisions on e-commerce platforms by employing the Apriori algorithm, one of the most widely used data mining techniques for discovering product co-occurrence patterns. Utilizing a wholesale transaction dataset consisting of 38,765 entries, the research involved a series of data preprocessing steps, application of association rule mining, and visualization of product relationships using a graph-based network diagram. The analysis revealed that products such as whole milk, other vegetables, and rolls/buns appeared most frequently in transactions. Additionally, several product combinations with high lift and confidence values were identified, indicating strong potential for bundling and cross-selling strategies. The business implications of these findings include the development of association-based product recommendation systems to enhance promotional effectiveness and optimize product layout in online stores. Overall, this study underscores that leveraging the Apriori algorithm not only deepens the understanding of consumer behavior but also opens new opportunities for data-driven marketing innovation
ANALISIS MACTOR PADA HUBUNGAN ANTAR-AKTOR DALAM PENGELOLAAN KAWASAN KONSERVASI DI PERAIRAN PULAU AY DAN PULAU RHUN PROVINSI MALUKU
Get PDFThe management of the Marine Protected Areas around Ay Island and Rhun Island requires a robust multi-stakeholder governance approach to ensure ecological sustainability while supporting local community well-being. The purpose of this study is to analyze the relationship between actors and their orientation towards the strategic objectives of conservation area management on Ay Island and Rhun Island. This study applies the MACTOR method to analyze actor influence and dependence, goal preferences, levels of competitiveness, potential conflicts, collaboration opportunities, and actor–objective interactions within the governance system. The data was obtained through questionnaires distributed to 40 stakeholders from provincial government agencies, local governments, and NGOs, other relevant institutions. The results indicate that the key actors with the highest influence include the Maluku Provincial Marine and Fisheries Office, the Marine and Fisheries Branch Office of Island Cluster VI, the CTC, the EcoNusa Foundation, Pokmaswas-Ay, Pokmaswas-Rhun, and MCC. These actors hold strategic roles as decision-makers, technical support providers, and facilitators of cross-institutional coordination. Goal preferences emphasize enhanced community involvement as the top priority, followed by sustainable resource management and strengthened governance. Highly competitive actors exhibit strong legitimacy, capacity, and working networks, while others face limitations in authority and resources. Actor relationships are generally harmonious, with strong potential for collaboration, particularly among the provincial DKP, the Island Cluster VI Branch Office, CTC, EcoNusa, MCC, and Banda Naira University. Actor–objective interactions show strong alignment, indicating opportunities for policy integration, improved coordination, and reinforced multi-stakeholder collaboration to advance more effective and sustainable conservation management.
ABSTRAK
Pengelolaan Kawasan Konservasi Perairan Pulau Ay dan Pulau Rhun membutuhkan pendekatan tata kelola multi-stakeholder yang kuat untuk memastikan keberlanjutan ekosistem sekaligus mendukung kesejahteraan masyarakat lokal. Tujuan penelitian ini adalah menganalisis hubungan antaraktor dan orientasi terhadap tujuan strategis pengelolaan kawasan konservasi Pulau Ay dan Pulau Rhun. Penelitian ini menggunakan metode MACTOR (Matrix of Alliances and Conflicts: Tactics, Objectives, and Recommendations) untuk menganalisis pengaruh dan ketergantungan antar-aktor, preferensi tujuan, tingkat daya saing, potensi konflik, peluang kolaborasi, serta interaksi aktor dengan tujuan dalam pengelolaan kawasan. Data diperoleh melalui kuesioner yang dibagikan kepada 40 stakeholder yang berasal dari instansi pemerintah provinsi, pemerintah lokal, LSM, lembaga terkait lainnya. Hasil menunjukkan bahwa aktor kunci dengan pengaruh tertinggi mencakup Dinas Kelautan dan Perikanan Provinsi Maluku, Cabang Dinas Kelautan dan Perikanan Gugus Pulau VI, Yayasan CTC, Yayasan EcoNusa, Pokmaswas-Ay, Pokmaswas-Rhun, dan MCC. Aktor-aktor ini memiliki peran strategis sebagai pengambil keputusan, penyedia dukungan teknis, dan fasilitator koordinasi lintas lembaga. Preferensi tujuan menempatkan peningkatan keterlibatan masyarakat sebagai prioritas utama, diikuti pengelolaan sumberdaya berkelanjutan dan penguatan tata kelola. Aktor dengan daya saing tinggi memiliki legitimasi, kapasitas, dan jejaring kerja yang kuat, sementara aktor lainnya menghadapi keterbatasan kewenangan dan sumberdaya. Hubungan antar-aktor bersifat harmonis dengan potensi kolaborasi tinggi, terutama di antara DKP Provinsi Maluku, Cabang Dinas Gugus Pulau VI, CTC, EcoNusa, MCC, dan Universitas Banda Naira. Interaksi aktor dengan tujuan strategis menunjukkan kedekatan kuat yang membuka peluang integrasi kebijakan, peningkatan koordinasi, dan penguatan kolaborasi multi-stakeholder menuju pengelolaan konservasi yang lebih efektif dan berkelanjutan.
Kata Kunci: Kawasan konservasi perairan, MACTOR, tata kelola multi-stakeholder, Pulau Ay, Pulau Rhu
COMPARATIVE STUDY OF LSTM-BASED MODELS WITH HYPERPARAMETER OPTIMIZATION FOR SHORT-TERM ELECTRICITY LOAD FORECASTING
Get PDFThis research is focused on the development and comparison of time series models for short-term electrical load forecasting, utilizing several variants of Long Short-Term Memory (LSTM) networks. The specific LSTM variants employed in this study include Vanilla LSTM, Stacked LSTM, Bidirectional LSTM, and Convolutional Neural Network LSTM (CNN-LSTM). We used five years (2016-2020) of daily electricity load data from the Central Java-DIY system, provided by PT PLN (Persero). The primary objective is to ascertain the accuracy and evaluate the performance of these LSTM variants in the context of short-term load forecasting. This is achieved quantitatively through the computation of various error metrics, namely Mean Square Error (MSE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and R-squared. The results of the study reveal that the CNN-LSTM method outperforms the other variants in terms of the calculated metrics. Specifically, the CNN-LSTM method achieved the lowest values for all metrics: an MSE of 0.007 for training and 0.0010 for testing, an MAE of 0.0050 for training and 0.0062 for testing, and an RMSE of 0.083 for training and 0.099 for testing. Among the evaluated models, CNN-LSTM demonstrates the best trade-off between predictive accuracy and training efficiency, making it the most recommended for short-term electricity load forecasting. While BiLSTM achieves higher accuracy, particularly in terms of MAE, it requires a longer training time. In contrast, Stacked LSTM converges faster with slightly lower accuracy, making it a strong alternative when computational efficiency is prioritized.
SPATIAL ASSESSMENT OF PEAT-LAND FIRES UTILIZING BINARY LOGISTICS REGRESSION IN WEST KALIMANTAN
Get PDFThis study contributes to the understanding of forest fire susceptibility by applying a binary logistic regression model combined with a Geographic Information Systems (GIS) to map hotspot vulnerability in West Kalimantan, Indonesia, an approach not extensively explored in previous research. Forest fire is one of the environmental problems. In West Kalimantan, land fires are a routine disaster that is experienced almost every year. In this paper, a binary logistic regression model was used to identify land fire in west Kalimantan. In addition, mapping of confidence of hotspot susceptibility was carried out in West Kalimantan. The data used were 72 hotspots spread across in seven districts of West Kalimantan in 2020. The independent variables used were land cover, slope, topography, distance of hotspots to rivers, distance of hotspots to roads and distance of hotspots to settlements. While the dependent variable was the point which was classified into hotspots and non-hotspots. Results showed that the method identified that the variables significantly influencing land fires include the distance of the points to the river and the distance of the points to the road. The Binary Logistic Regression model of the land fire in West Kalimantan has a classification accuracy rate is 84.03%. From the results of weighting and visualization using GIS shown that the area that has a very high level of vulnerability is the city of Pontianak (42.97%). Meanwhile, areas that have a moderate level of vulnerability include Kayong Utara, Kubu Raya, Mempawah, Sambas, Sanggau, Sekadau and Sintang districs. Kubu Raya and Kayong Utara districts in the medium vulnerability level have the largest forest fire districts (43.70% and 41.25%). Meanwhile, districts that are in the very low vulnerability level are Bengkayang, Singkawang, Landak and Melawi districts
LOSS INSURANCE MODEL OF RISK FOR AGRICULTURAL COMMODITY BASED ON MAXIMUM DAILY RAINFALL INDEX CONSIDERATION
Get PDFAgricultural commodities in rainfed areas face significant risks of yield loss and crop failure due to uncertain rainfall patterns and intensities. Index-based crop insurance has been introduced as an adaptive strategy to simplify loss assessment using climate indicators. However, most existing schemes cover only a single peril, such as drought. This study aims to develop a loss model of risk for agricultural commodity using maximum daily rainfall index that accounts for both drought and flood risks. The model consists of two components: rainfall modelling and insurance modelling. Rainfall modelling identifies the appropriate probability distribution to define rainfall index parameters—trigger and exit—which represent thresholds for yield reduction and total crop failure, respectively. These parameters are derived through numerical integration and can be approximated using percentiles when crop-specific water requirement data are unavailable. Insurance modelling determines a benefit claim model based on rainfall probability and parameters of rainfall index, with three possible benefit claim conditions: full, partial, and none. A case study using maximum daily rainfall data (September–December, 1984–2014) for paddy in Dramaga, Bogor, indicates that the Burr Type XII distribution fits the data better than the GEV distribution. The estimated premium ranges from IDR 300000 to 300822.9 per hectare. In high-rainfall areas like Dramaga, premiums are primarily influenced by the probability of excess rainfall, while drought risk is negligible. Analysis over a 10-year actual maximum daily rainfall data (September–December, 2015–2024) shows that lower insured percentiles result in lower premiums. To improve accuracy, trigger and exit should ideally be determined based on the specific crop's water requirements. Despite data limitations, this model provides a conceptual model for developing more representative and actuarially fair loss model for agricultural commodity risk
MODIFIED STATISTICAL-BASED VALUE AT RISK FOR MULTI-OBJECTIVE OPTIMAL-BASED PORTFOLIO ANALYSIS OF INDONESIAN STOCK RETURN DISTRIBUTION
Get PDFBasically, all stock investments aim to obtain maximum profit with low risk. The formation of a stock investment portfolio is always accompanied by measuring returns and risks that show its performance. Portfolio risk measurement is often faced with the challenge that returns are not normally distributed, so that measurements using the normality assumption cannot be applied. This study proposes the development of a modification of stock portfolio risk measurement so that it is not limited to the normality assumption. The development is carried out by modifying the calculation of Value at Risk (VaR) to consider the skewness and kurtosis values (hereinafter referred to as modified VaR), so that the normal distribution assumption can be eliminated. As a method for compiling a stock portfolio, the Multi-Objective Optimization technique was chosen because it can modify risk averse so that the risk can be adjusted to the risk profile of each investor and is able to stabilize the mean return value. For its implementation, this paper uses real stock data which of course has returns that are not normally distributed, namely the four Indonesian stocks based on the largest capitalization recorded in January 2025 (blue chip), namely BREN, BBCA, BYAN, and BBRI obtained through finance.yahoo.com. The analysis method is divided into three steps, including multi-objective optimization completion, portfolio return calculation, and finally modified VaR estimation. The results of the study show that BBCA has the largest weight with a portion of more than 40% of the four stocks, so BBCA will be the priority stock for this portfolio. The portfolio formed using multi-objective optimization is proven to have a stable mean return because the portfolio mean return is between several of its constituent stocks (vice versa) which is around 0.01%, and the smallest estimated value of the portfolio modified VaR is 1.67%. Thus, a portfolio based on multi-objective optimization is not only able to create a portfolio that provides a small risk in risk measurement without assuming a normal distribution, but at the same time multi-objective optimization is also able to provide competitive returns with its constituent stocks
STRATEGI PENDIDIKAN LINGKUNGAN UNTUK MENINGKATKAN KESADARAN KONSERVASI SATWA LIAR PADA GENERASI MUDA DI DESA LEAHARI, PULAU AMBON
Get PDFThis community service activity was conducted in Leahari Village, Ambon Island, to raise awareness of wildlife conservation among the younger generation through environmental education based on local wisdom. The activity methods included outreach, participatory discussions, mangrove planting, and coastal cleanup, involving 50 participants consisting of students, youth, and community leaders. Evaluation was conducted through pre- and post-tests to measure improvements in knowledge, attitudes, and conservative behavior. Results showed an increase in knowledge from 55% to 90%, attitudes from 60% to 88%, and behavior from 58% to 86%. This activity demonstrated that the integration of local values such as sasi laut and pela gandong is effective in strengthening the ecological awareness of the younger generation.
 
Pemanfaatan Metode Universal Soil Loss Equation untuk Penentuan Kawasan Konservasi Lahan di Sub Daerah Aliran Sungai Cihaur
Get PDFErosi tanah merupakan salah satu permasalahan utama dalam pengelolaan daerah aliran sungai (DAS), khususnya pada wilayah dengan topografi curam dan intensitas hujan tinggi seperti DAS Citarum. Penelitian ini bertujuan untuk memprediksi laju erosi dengan metode Universal Soil Loss Equation (USLE) serta menentukan zonasi kawasan konservasi lahan di Sub DAS Cihaur. Data yang digunakan meliputi faktor erosivitas hujan (R), erodibilitas tanah (K), panjang dan kemiringan lereng (LS), penutup lahan (C), serta tindakan konservasi (P), yang dianalisis secara spasial menggunakan Sistem Informasi Geografis (SIG). Hasil analisis menunjukkan bahwa Sub DAS Cihaur memiliki variasi Tingkat Bahaya Erosi (TBE) dari sangat ringan hingga sangat berat. Sebagian besar wilayah termasuk kategori sangat ringan hingga ringan (±69,4%), sedangkan wilayah dengan kategori berat hingga sangat berat mencakup ±21,5% dari total area, yang umumnya berada di lereng curam dengan penggunaan lahan pertanian terbuka. Zonasi konservasi yang dihasilkan merekomendasikan perlindungan vegetasi alami dan pengendalian alih fungsi lahan pada TBE sangat ringan–ringan, konservasi vegetatif intensif seperti agroforestri, cover crops, dan rotasi tanaman pada TBE sedang, serta konservasi mekanik sederhana, revegetasi prioritas, dan penanaman strip rumput pada TBE berat–sangat berat. Penelitian ini memberikan kontribusi berupa novelty pada penerapan USLE dalam konteks Sub DAS Cihaur yang belum banyak dikaji sebelumnya. Hasil penelitian tidak hanya menghasilkan prediksi kuantitatif erosi, tetapi juga memberikan dasar aplikatif bagi penentuan kawasan konservasi lahan, sehingga dapat mendukung strategi pengelolaan DAS Citarum Hulu yang berkelanjutan
Jurisdiksi International Criminal Court (ICC) Terhadap Presiden Rusia Vladimir Putin Berdasarkan Ketentuan Hukum Humaniter Internasional
Get PDFThe International Criminal Court (ICC) is important in enforcing international law, especially against serious crimes. In March 2023 the ICC issued an arrest warrant for President Vladimir Putin regarding his crimes against humanity and war crimes, even though Russia is not a member country of the ICC. The issues in this writing include, whether Russian President Vladimir Putin can be arrested by the International ICC under the provisions of International Humanitarian Law and whether Russian President Vladimir Putin can be held accountable to the ICC under the provisions of International Humanitarian Law. The research method applied is normative legal research by studying legal library materials through statutory, case, and conceptual approaches and using quanlitative analysis. Research results show that the ICC has limited jurisdiction and cannot outperform national courts, it does not have the power to enforce arrest and accountability without Russia's cooperation. Russia also has veto rights at the UN, so Russia can use its veto rights to protect its national interests. Even though it is difficult for the ICC to arrest and hold Putin accountable, the arrest warrant affects Russia's political and diplomatic relations. The research aims to serve as input for legal science, especially in International Law related to the Arrest and Accountability of Russian President Vladimir Putin to the ICC Based on the Provisions of International Humanitarian Law
Implementasi Putusan Mahkamah Arbitrase Internasional Dan Akibat Hukumnya: Konflik Antara China dan Filipina Atas Laut China Selatan
Get PDFThe South China Sea dispute stems from China's historical "nine-dash line" claim to almost the entire area, which the Philippines rejects. In 2013, the Philippines brought the dispute to the Permanent Court of Arbitration (PCA). The PCA's July 12, 2016 ruling affirmed that China's claim had no legal basis under UNCLOS 1982 and rejected the validity of the "nine-dash line", while designating areas such as Scarborough Shoal as part of the Philippines' Exclusive Economic Zone (EEZ). China's stance in rejecting the arbitral award has also been criticized by surrounding countries and the international community, who consider such actions to threaten regional security and raise concerns about the potential for armed conflict in the strategic region. The author uses normative juridical research. In general, normative legal research is research that focuses on legal issues in a particular jurisdiction. Normative legal research focuses on the statutory approach, which leads to the idea that normative research is research on laws and regulations. The analysis focuses on the provisions of UNCLOS 1982, international dispute resolution mechanisms, and the implementation of arbitral awards in global legal practice. The implementation of the Permanent Court of Arbitration (PCA) award faces significant political challenges due to China's rejection, so the legal consequences are more political and economic than formal juridical. The Philippines respects and seeks to implement the award, while China expressly rejects it. This rejection has led to various legal consequences, including the application of enforcement mechanisms that include economic sanctions, membership sanctions in international organizations, and unilateral sanctions from certain countries. Although the PCA ruling has the binding force of international law, China's non-compliance with the ruling shows the limitations of international law enforcement mechanisms in maritime disputes involving major powers. Therefore, resolving South China Sea disputes requires a more comprehensive approach, combining legal, political and diplomatic aspects to achieve sustainable regional stability. The role of the international community and relevant countries is crucial in encouraging compliance with international law and preventing conflict escalation that can have far-reaching regional and global impacts