Judul: Analisis Pembayaran Jasa Lingkungan Air Bersih Di Hulu DAS Latuppa Kota Palopo Provinsi Sulawesi Selatan
Abstrak: The increasing number of population and economic growth lead to the increasing of water demand. Furthermore, it will also affect the availability of fresh water to meet the needs of human activities. UNEP (2002) reported that the total of water consumption in the world reach 12.500-14.00 km3 per year. This number is believed will continuously increase as the increasing needs of a better life. The rise of watershed degradation (DAS) in supporting human activities leads to the increasing of people awareness to keep it sustainable. One way is to conduct an environmental policy that can control the use of resources (water resource) in a watershed area. One of watershed area in Sulawesi that serve fresh water for many people is Latuppa watershed in Palopo City. The watershed has big potential to support human life, such as a source of fresh water for water supply corporation (PDAM) of Palopo and for agriculture irrigation. But, the Latuppa watershed is now facing a serious problem, characterized by its biophysical changes due to the continuous unsustainable use by the community, either timber exploitation and firewood, housing, as well as the agricultural activities. As a consequence, flood is happened in rainy season and drought in dry season occurred in the last decade. Those problems faced by the upstream and downstream Latuppa watershed user including PDAM Palopo City, which is the water form Latuppa watershed is a source of intake for their corporation. Fluctuation of water volume in Latuppa river lead to disruption of the distribution of fresh water distribution to consumers of PDAM due to over capacity of water in rainy season with high contaminated and scarcity in dry season that could not fulfill the intake capacity of water production in PDAM Palopo. Therefore, the protection of water use system in the watershed area (DAS) of Latuppa upstream using payment mechanism for ecosystem services was initiated to minimize degradation of water catchment area that was purposed to maintain the continuity of fresh water produced by PDAM. The general objective of this study is to estimate the amount (price) of compensation for the upstream community keep the watershed sustain and provided appropriate organization to handle payment of environmental service to fresh water in Latuppa upstream area. The specific purposes of this study are: (1) to study local community’ perceptions and behavior for rehabilitating land and water in the upstream of Latuppa watershed, (2) to estimate the contribution of the economic value of raw water for the PDAM of Palopo, (3) to assess the ability of PDAM to pay for keeping the water catchment area in the upstream in order to remain sustainable supply of raw water, (4) analyze the institutional mechanisms for the implementation of payment for ecosystem services of fresh water in Latuppa watersheds. This research was conducted in two sub-districs, Mungkajang and Sendana, as two major areas located in Latuppa upstream of water stream area (DAS) Palopo. The data used were primary and secondary data. This research used Spearmen analysis (Likert scale), The mean score to identify population’s perceptions and attitudes towards conservation in water stream
Keyword: Water Catchment area, Payment for ecosystem Services, Residual Imputation Approach

Judul: Penifaian Jasa Lingkungan Air Minum dan Penentuen Prioriias Bantuan Perbaikan Lingkungan (Studi Kasus DAS Citarum, Jawa Barat)
Abstrak: Willingness of community at Citarum watershed to partidpate in improving environmental quality as an effort to reduce impact of dimate change was assessed based on their willingness to pay to environmentd sewices provided by upper watershed communities. Identification of activities that would reduce the involvement of upstream communities to do deforestation and assessment, of vulnerability of downstream communities to climate change was carried out through survey to. household. The illingness to pay was analyzed using Contingent Valuation Methd (CVM) and priority pwmm was analyzed using Analytical Hierarki Process (AHP). Based on CVM analysis it was indicated that the level of willingness of downstream communities to pay the compensation for the environmental sewices (0.g. drinking water) provided by upstream communities depended on their perception and understanding about the important of maintaining forest cover at the upper Citafum watershed and availability of drinking water. If the downstream communities living in the uhan areas often exposed to clean water scarcity problem during dry-season, their willingness to pay for the compensation tended to inmase. Further analysis found that the main factors that motivate mmuniiy to do deforestation at Upper Cirum watershed were to seek new land for agricutture activities and to increase their income. Majority of communities wanted to stop destructing the forest if they have alternative jobs for income generation.
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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