Judul: Dampak Volatilitas Nilai Tukar Terhadap Kinerja Ekspor Lada Indonesia
Abstrak: Since the breakdown of Bretton Woods system in 1973, topic on the impact of exchange rate volatility on trade has been drawn attention of many researchers. However, discussion on the topic remains ambiguous and becomes an empirical issue. Indonesia is an emerging country that heavily depends on agricultural export as one of its national income sources. As Indonesia’s agricultural trade has become largely integrated with global trade, it inevitably involves other currencies on its transactions. Pepper (Piper nigrum) is one of the most exported spices in Indonesia followed by cinnamon, cloves, and vanilla. Due to its strong dependency on international trade, Indonesian pepper exports are suspected to be prone to exchange rate volatility risks. This paper aims to analyze the exchange rate volatility and examine the relationship between bilateral exchange rate volatility from 2005 to 2019 using the gravity model and GARCH(1,1) model as the proxy of exchange rate volatility. The results of bilateral exchange rate volatility analysis versus Indonesia’s pepper trading partners indicate that the highest volatility for all of the currencies occurred between 2008 and 2009 due to the recent financial crisis or GFC. Amidst the shock, Indonesia was reported to have resilient growth. The results of the gravity model reveal that during the observation period, Indonesian pepper exports are not affected significantly by the exchange rate volatility. This is because Indonesia has been in the position as a net exporter of pepper where a majority of its production is consumed abroad. Moreover, pepper only costs a small percentage of the total cost of food productions. Since pepper is included as necessity goods, pepper demand is relatively not responsive to the price changes (inelastic). Therefore, the effects are not large enough to affect Indonesian pepper exports. Pepper has a good opportunity for export expansion since the results suggest that it is resistant to exchange rate volatility risks. To support this, the efforts that can be used are to maintain the currency stability, support on providing hedging facilities, and optimize the application of warehouse receipt system (WRS) for the better competitiveness. For future research, it is recommended to use more data in the analysis and try to use other variables that may be related to this topic. Finally, it is also recommended to compare the results with other volatility measurements.
Keyword: Gravity model, exchange rate volatility, GARCH(1,1), Indonesian spice, Indonesian pepper trade

Judul: Analysis of Factors Affecting Exports and Development of Indonesian Pepper (Piper nigrum L.) Exports to Major Export Destinations
Abstrak: Indonesia merupakan salah satu eksportir lada terbesar, namun dihadapkan tidak stabilnya produksi yang berdampak pada perubahan jumlah maupun nilai ekspor lada Indonesia. Penelitian ini bertujuan untuk: (1) menganalisis faktor-faktor yang mempengaruhi volume ekspor lada Indonesia ke negara tujuan, (2) menganalisis perkembangan trend dan proyeksi jumlah volume ekspor lada Indonesia ke negara tujuan periode 2020-2024. Penelitian ini menggunakan analisis regresi linier berganda untuk mengetahui variabel penduga yang berpengaruh terhadap jumlah ekspor lada Indonesia ke tiga negara tujuan dan trend analysis untuk untuk mengetahui perkembangan trend dan proyeksi jumlah ekspor lada Indonesia periode 2020-2024. Hasil regresi menunjukkan bahwa PDB perkapita negara Vietnam, India, dan Amerika Serikat berpengaruh signifikan terhadap volume ekspor lada Indonesia ke tiga negara tersebut. Kurs riil rupiah terhadap dollar Amerika berpengaruh signifikan terhadap volume ekspor lada Indonesia ke Vietnam dan Amerika Serikat. Trend proyeksi volume ekspor lada Indonesia ke Vietnam tahun 2020-2024 diramalkan akan meningkat, ke India cenderung stabil, dan ke Amerika Serikat akan menurun., Indonesia is one of the largest pepper exporters, but faced with unsteady production which has an impact on changes in the quantity and value of Indonesian pepper exports. This study aims to: (1) analyze the factors that affect the volume of Indonesian pepper exports to destination countries (2) analyze the development trend and projected volume of Indonesian pepper exports to destination countries for the 2020-2024 period. This research uses multiple linear regression analysis to find out the estimating variables that affect the total of Indonesian pepper exports to the three export destination countries and trend analysis to find out the trend development and projected number of Indonesian pepper exports the 2020-2024 period. The regression indicate that the GDP percapita of Vietnam, India, and the United States has a significant effect on the volume of Indonesian pepper exports to these three countries. The real exchange rate of the rupiah against the US dollar has a significant effect on the volume of Indonesian pepper exports to Vietnam and the United States. The projected trend of Indonesian pepper exports to Vietnam will increase, to India tends to be steady, and to the United States it will decrease.
Keyword: Exporters, Export real price, Forecasting, Importers, Multiple linear regression

Judul: Quantum Convolutional Neural Network (QCNN) for Classification Brain Tumor MRI Image
Abstrak: Penelitian ini bertujuan untuk mengembangkan model deteksi tumor otak menggunakan citra MRI dengan metode Quantum Convolutional Neural Network. Data yang digunakan adalah citra MRI otak yang terdiri dari citra tumor otak glioma, meningioma, hipofisis, dan negatif tumor yang dibagi kedalam data latih dan uji dengan rasio 80:20. Selanjutnya data latih dilakukan penyeimbangan dengan teknik oversampling. Dilakukan pengembangan model untuk mendeteksi tumor otak (biner), dan juga model untuk mengklasifikasikan jenis tumor otak (multiclass). Parameter yang digunakan dalam pengembangan model adalah jumlah ukuran filer = 2 dan kedalaman = 4, dengan qubit 4, dan dilatih dengan jumlah epoch sebanyak 10. Data akan diproses dengan metode Quantum Convolutional Neural Network yang terdiri dari lapisan quantum convolution, lapisan flatten, dan lapisan dense. Model multiclass mendapatkan akurasi 52%, setelah data latih diseimbangkan akurasi model meningkat menjadi 62%, sedangkan model biner mendapatkan akurasi 88%, setelah data latih diseimbangkan akurasi model meningkat menjadi 89%.
Keyword: Citra MRI, Klasifikasi Citra, QCNN, Tumor Otak