SISTEM INFORMASI PASAR MODAL DALAM ANALISIS FAKTOR YANG MEMPENGARUHI VOLATILITY IHSG DI BURSA EFEK INDONESIA (BEI) PERIODE 2015-2021

Penelitian ini bertujuan untuk memanfaatkan sistem informasi pasar modal dalam menganalisis pergerakan (volatility) Indeks Harga Saham Gabungan (IHSG) dan faktor-faktor yang mempengaruhinya. Faktor yang mempengaruhi IHSG yag digunakan dalam penelitian ini adalah nilai tukar Rupiah terhadap Dollar Amerika, SBI (Suku Bunga Sertifikat Bank Indonesia), inflasi dan Produk Domestik Bruto (PDB). Data yang digunakan adalah data sekunder berupa data time series yang diambil pada rentang tahun 2015-2021 yang diperoleh dari Badan Pusat Statistik, Bank Indonesia, dan data dari www.investing.com. Analisis data dilakukan dengan menggunakan pertama, uji stasioner data, kedua uji kointegrasi dan ketiga Error Correction Model (ECM). Hasil penelitian menunjukkan bahwa hanya SBI (Suku Bunga Sertifikat Bank Indonesia) yang mempunyai pengaruh terhadap Indeks Harga Saham Gabungan di Bursa Efek Indonesia, sedangkan nilai tukar Kurs Rupiah, inflasi dan Produk Domestik Bruto tidak mempunyai pengaruh terhadap Indeks Harga Saham Gabungan di Bursa Efek Indonesia tahun 2015 – 2021. Berdasarkan hal tersebut diatas, informasi yang dikeluarkan pasar modal akan dapat menarik minat investor untuk dapat menanamkan modalnya di pasar modal. Jika informasi yang dikeluarkan positif, maka pertumbuhan pasar modal juga akan positif, namun jika yang terjadi sebaliknya maka pertumbuhan pasar modal juga akan sebaliknya. Melalui sistem informasi yang ada, maka investor dapat membaca secara langsung mengenai pasar modal dan fluktuatifnya harga saham yang ada

Dampak Ekonomi Makro Terhadap Yield Surat Berharga Negara: Studi Empiris Di Indonesia

The increasing integration of the world economy and the large share of foreign ownership of the Government Securities (SBN), then changes in economic policies in developed countries affect the pressure on financial markets in emerging market countries. This study analyzes the effect of macroeconomic factors on 10-year tenor Government's yields issued by the Government of Indonesia for the period 2012-2017. Using the Vector Error Correction Model (VECM) results in long-term USD/IDR, Oil Price, Credit Default Swap (CDS) are negatively significant, while Brazilian State Bonds (ON Brazil) have a significant positive effect on SBN yield. Based on the analysis of Impulse Response Function (IRF), the shock of yield on ON Brazil, CDS, JIBOR, USD / IDR and US Treasury (UST) responded positively by the yield SBN in each period, but the shock by Oil Price responded negatively by the yield of SBN. The result of Forecast Error Variance Decomposition (FEVD) analysis shows that UST variable is the biggest variable contribution influence to Indonesia SBN yield, followed by CDS and ON Brazil

Pemberdayaan Kaum Perempuan dalam Pengembangan Model Bisnis Berbasis Ekonomi Biru

Pengabdian masyarakat ini bertujuan untuk mengoptimalkan peran kaum perempuan kelompok bank sampah pratama, pura bojonggede melalui pengembangan model bisnis produk olahan sampah daur ulang. Kegiatan ini memiliki dua tujuan khusus yaitu; meningkatkan pendapatan ibu – ibu desa tajurhalang, pura bojonggede dari diversifikasi produk olahan bank sampah yang ada. Selain itu bertujuan untuk membangun usaha yang berkelanjutan dan ramah lingkungan. Metode yang digunakan dalam kegiatan ini mencakup lima tahapan antara lain; kegiatan identifikasi potensi sampah yang dapat didaur ulang; membuat prototype produk; merancang model bisnis berbasis ekonomi biru; memberikan pelatihan dan pendampingan terkait model bisnis berbasis ekonomi biru; mengevaluasi kelayakan model bisnis. Rintisan usaha diyakini akan mampu berdampak pada peningkatan pendapatan ibu – ibu yang tergabung dalam kelompok bank sampah Pratama. Kata kunci— Bank sampah, Ekonomi biru, Model bisnis, Pemberdayaan perempuan Abstract This community service aims to optimize the role of women in the pratama waste bank group, Pura Bojonggede through the development of a business model for processed waste products. This activity has two specific objectives, namely; increase the income of women in the village of Tajurhalang, Pura Bojonggede from the diversification of existing waste bank processed products. In addition, it aims to build a sustainable and environmentally friendly business. The method used in this activity includes five stages, including; identification of potential waste that can be recycled; make product prototypes; designing a blue economy-based business model; provide training and assistance related to blue economy-based business models; evaluate the feasibility of the business model. It is believed that the business startup will be able to have an impact on increasing the income of mothers who are members of the Primary waste bank group. Keywords— Garbage bank, Blue economy, Business model, Women's empowermentPengabdian masyarakat ini bertujuan untuk mengoptimalkan peran kaum perempuan kelompok bank sampah pratama, pura bojonggede melalui pengembangan model bisnis produk olahan sampah daur ulang. Kegiatan ini memiliki dua tujuan khusus yaitu; meningkatkan pendapatan ibu – ibu desa tajurhalang, pura bojonggede dari diversifikasi produk olahan bank sampah yang ada. Selain itu bertujuan untuk membangun usaha yang berkelanjutan dan ramah lingkungan. Metode yang digunakan dalam kegiatan ini mencakup lima tahapan antara lain; kegiatan identifikasi potensi sampah yang dapat didaur ulang; membuat prototype produk; merancang model bisnis berbasis ekonomi biru; memberikan pelatihan dan pendampingan terkait model bisnis berbasis ekonomi biru; mengevaluasi kelayakan model bisnis. Rintisan usaha diyakini akan mampu berdampak pada peningkatan pendapatan ibu – ibu yang tergabung dalam kelompok bank sampah Pratama. Kata kunci— Bank sampah, Ekonomi biru, Model bisnis, Pemberdayaan perempuan Abstract This community service aims to optimize the role of women in the pratama waste bank group, Pura Bojonggede through the development of a business model for processed waste products. This activity has two specific objectives, namely; increase the income of women in the village of Tajurhalang, Pura Bojonggede from the diversification of existing waste bank processed products. In addition, it aims to build a sustainable and environmentally friendly business. The method used in this activity includes five stages, including; identification of potential waste that can be recycled; make product prototypes; designing a blue economy-based business model; provide training and assistance related to blue economy-based business models; evaluate the feasibility of the business model. It is believed that the business startup will be able to have an impact on increasing the income of mothers who are members of the Primary waste bank group. Keywords— Garbage bank, Blue economy, Business model, Women's empowermen

Dampak Ekonomi Makro Terhadap Yield Surat Berharga Negara: Studi Empiris Di Indonesia

The increasing integration of the world economy and the large share of foreign ownership of the Government Securities (SBN), then changes in economic policies in developed countries affect the pressure on financial markets in emerging market countries. This study analyzes the effect of macroeconomic factors on 10-year tenor Government’s yields issued by the Government of Indonesia for the period 2012-2017. Using the Vector Error Correction Model (VECM) results in long-term USD/IDR, Oil Price, Credit Default Swap (CDS) are negatively significant, while Brazilian State Bonds (ON Brazil) have a significant positive effect on SBN yield. Based on the analysis of Impulse Response Function (IRF), the shock of yield on ON Brazil, CDS, JIBOR, USD / IDR and US Treasury (UST) responded positively by the yield SBN in each period, but the shock by Oil Price responded negatively by the yield of SBN. The result of Forecast Error Variance Decomposition (FEVD) analysis shows that UST variable is the biggest variable contribution influence to Indonesia SBN yield, followed by CDS and ON Brazil

UAV- and Random-Forest-AdaBoost (RFA)-Based Estimation of Rice Plant Traits

Rapid, accurate and inexpensive methods are required to analyze plant traits throughout all crop growth stages for plant phenotyping. Few studies have comprehensively evaluated plant traits from multispectral cameras onboard UAV platforms. Additionally, machine learning algorithms tend to over- or underfit data and limited attention has been paid to optimizing their performance through an ensemble learning approach. This study aims to (1) comprehensively evaluate twelve rice plant traits estimated from aerial unmanned vehicle (UAV)-based multispectral images and (2) introduce Random Forest AdaBoost (RFA) algorithms as an optimization approach for estimating plant traits. The approach was tested based on a farmer’s field in Terengganu, Malaysia, for the off-season from February to June 2018, involving five rice cultivars and three nitrogen (N) rates. Four bands, thirteen indices and Random Forest-AdaBoost (RFA) regression models were evaluated against the twelve plant traits according to the growth stages. Among the plant traits, plant height, green leaf and storage organ biomass, and foliar nitrogen (N) content were estimated well, with a coefficient of determination (R2) above 0.80. In comparing the bands and indices, red, Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), Red-Edge Wide Dynamic Range Vegetation Index (REWDRVI) and Red-Edge Soil Adjusted Vegetation Index (RESAVI) were remarkable in estimating all plant traits at tillering, booting and milking stages with R2 values ranging from 0.80–0.99 and root mean square error (RMSE) values ranging from 0.04–0.22. Milking was found to be the best growth stage to conduct estimations of plant traits. In summary, our findings demonstrate that an ensemble learning approach can improve the accuracy as well as reduce under/overfitting in plant phenotyping algorithms