Judul: Analysis of Consumer Attitudes Attributes  of Perhutani Honey Product in Bandung
Abstrak: Produksi madu yang meningkat selama beberapa tahun terakhir menyebabkan usaha madu mengalami perkembangan dan persaingan diantara industri madu semakin ketat. Produsen madu perlu memahami sikap konsumen serta atribut yang dianggap penting oleh konsumen. Penelitian ini bertujuan untuk menganalisis karakteristik konsumen, menganalisis sikap konsumen terhadap atribut produk madu Perhutani. Jumlah responden dalam penelitian ini adalah 100 orang. Metode analisis yang digunakan adalah analisis deskriptif dan analisis multiatribut Fishbein. Mayoritas responden merupakan laki-laki berusia 46-55 tahun, memiliki Pendidikan terakhir S1, bekerja sebagai pegawai swasta, dengan pendapatan Rp5.000.000-Rp6.999.999. Hasil penelitian menunjukan bahwa sikap konsumen terhadap atribut madu Perhutani termasuk kategori sangat positif dan kinerja atribut madu Perhutani terbagi menjadi empat kuadran dengan atribut keterjangkauan, The increase in honey production over the past few years has led to the development of the honey business, and competition in the honey industry has intensified. Honey producers need to understand consumer attitudes and attributes that are considered important by consumers. The purpose of this study is to analyze consumer characteristics and consumer attitudes of Perhutani honey product attributes in Bandung City. The number of respondents in this research were 100. The analysis methods used are descriptive analysis and Fishbein multiattribute analysis. The majority of respondents were men aged 46–55 years, had the last education of S1, worked as private employees, and had an income of Rp5,000,000–Rp6,999,999. The results of this research show that consumer attitudes towards Perhutani honey attributes are included in the very positive category and the performance of Perhutani honey attribute is divided into four quadrants, with the attributes of price, affordability, and ease of obtaining being the top priorities for improvement.
Keyword: consumer attitudes, honey, multiattributes fishbein, consumer

Judul: Kepuasan Konsumen dan Analisis Sensitivitas Harga Produk Madu Pramuka di PT. Madu Pramuka
Abstrak: The success of PT. Madu Pramuka in its modern honeybee farming business has encouraged the emergence of many varieties of similar products, thus it leads to more competitive market conditions. The purposes of the study were to analyze the importance level and attribute performance of the product, to analyze the level of customer satisfaction, and also to analyze the price sensitivity of the Pramuka Honey Product. The research methods that used were Importance Performance Analysis (IPA), Customer Satisfaction Index (CSI), and Van Westendorp method approach method. Based on the Importance Performance Analysis, attributes included in the first quadrant, wich are the first priority attributes that its performance should be fixed and improved, were the ease of obtaining product and the information on the packaging. Attributes included in Quadrant II, which are attributes that its quality should be mantained, were the flavors, the benefits and the authenticity of the product. From the analysis of Customer Satisfaction Index, a value of 78.63 was obtained indicating that consumers of Pramuka Honey were satisfied with the product. Based on the analysis of price sensitivity, the price of super Pramuka honey in size 650 ml which is Rp110 000, was in acceptable price range, that is bound on the lower end by Rp105 000 and on the upper end by Rp115 000.
Keyword: IPA, CSI, Price Sensitivity, Satisfaction, Pramuka Honey

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