Judul: Performance Determinant on Fintech Peer-to-Peer Lending in Indonesia
Abstrak: Fintech globally continues to experience an increase in 2020 which the fintech investment reaching USD 48,8 billion, and in 2021 the third quarter will double to USD 94,7 billion. The problem faced by P2P companies is that during the pandemic, the value of Non-Performing Loans (NPL) for P2P touched the highest in 2020, reaching 8,8%. In 2021, even though the NPL is in good condition, there is a fluctuating pattern. In the profitability aspect, after the pandemic, P2PL profitability increased dramatically from -7,36% in early 2021 to the highest recorded at 10.85%. This high level of profitability has had a very significant effect on fintech growth from 2018 to 2021. The dynamics and developments in the P2PL fintech industry are interesting for deeper analysis. In this study, the aims were to map the P2PL fintech industry, find out the determinants of ROE, and determine the determinants of NPL. In this study, the data used came from surveys to each of the P2PL fintech companies to obtain independent variable data. The analytical method used is the ordinal logistic regression method to determine the relationship between variables. The data collected is from 2019 to 2021. From the results of the hierarchical clustering mapping, there are three companies in cluster 1 where this company has the best performance, namely the highest disbursement and low NPL. In cluster two, there are 77 companies with disbursement below the total disbursement average and NPL below the total NPL average. While in cluster 3, there are 14 companies with high NPL values and low disbursement. Based on the results of ordinal logistic regression analysis, there are 11 independent variables that affect ROE, monthly active user, Operational Costs on Operational Revenues ratio (BOO), the use of biometrics, the use of robotic process automation, the use of SLA, integrated platform, distribution time, delivery of accurate information, the use of social media, the use of features chat on the application, and the type of credit scoring used. Based on the results of ordinal logistic regression analysis for NPL, there are 4 independent variables that influence NPL, the use of biometrics in lending, the use of digital marketing in promotions, the use of digital signatures in lending, and the use of social media. From the results of this study, there are several policy implications. The performance mapping dominated only some companies with high disbursement and good NPL value. These results show that the P2P lending industry needs to be more mature. The results of this study can be used as a reference for the government to maintain the fintech lending ecosystem. The ease of obtaining credit insurance, the vacation of licensing, and encouraging investment to increase technological innovation must be carried out so that the business climate for fintech lending remains good. The government's role as a supervisor is also very instrumental in determining the success of the fintech lending business line.
Keyword: Determinant, Fintech P2PL, NPL, Performance, ROE

Judul: Determinants of Investment Decisions in P2P
Lending in the JABODETABEK Region.
Abstrak: Kemajuan di bidang teknologi yang terus meningkat juga mempengaruhi perubahan perilaku masyarakat dimana masyarakat menjadi menginginkan sesuatu yang mudah dan cepat. Kemajuan teknologi ini juga terjadi di pasar keuangan seperti adanya financial technologi (fintech) salah satunya adalah platform peer-topeer lending. Tujuan dari penelitian ini untuk mengidentifikasi karakteristik para lender atau pemberi pinjaman di wilayah JABODETABEK dan mengetahui faktor apa saja yang mempengaruhi pemberi pinjaman untuk memutuskan berinvestasi di P2P lending. Metode analisis yang digunakan adalah analisis regresi logistik biner dan analisis deskriptif dengan menggunakan data primer yang diambil dari 132 responden melalui kuesioner online yang tersebar di wilayah JABODETABEK. Hasil penelitian ini menunjukkan bahwa karakteristik dari responden yang berbeda secara signifikan adalah responden yang berdomisili Jakarta dan Tangerang cenderung untuk memilih berinvestasi di P2P lending, lalu responden yang sudah menikah, berumur lebih tua, responden yang mengenyam waktu pendidikan lebih lama serta responden dengan pendapatan >Rp20.000.000 dan mempunyai pengalaman berinvestasi sebelumnya juga cenderung mempunyai willingness to lend di P2P lending. Sedangkan, responden yang mempunyai pendapatan <Rp5.000.000 cenderung tidak menginvestasikan modalnya di platform P2P lending. Selanjutnya, hasil dari penelitian ini menemukan bahwa biaya transaksi, layanan, keamanan, suku bunga dan risiko dapat mempengaruhi willingness to lend pemberi pinjaman atau lender. Hasil logit menunjukkan bahwa biaya transaksi, layanan, kemanan serta suku bunga dapat mempengaruhi secara positif sebaliknya faktor risiko berpengaruh secara negatif. Platform P2P lending dapat mengurangi faktor risiko seperti dengan adanya asuransi serta peningkatan dari segi layanan dan keamanan., Advances in technology that continue to increase also affect changes in people's behavior where people want something easy and fast. This technological advancement also occurs in the financial market, such as the existence of financial technology (fintech), one of them is a peer-to-peer lending platform. The purpose of this study is to identify the characteristics of lenders in the JABODETABEK area and to find out what factors influence lenders to decide to invest in P2P lending. The analytical method used is binary logistic regression analysis and descriptive analysis using primary data taken from 132 respondents through online questionnaires scattered in the JABODETABEK area. The results of this study indicate that the characteristics of the respondents who are significantly different are respondents who live in Jakarta and Tangerang tend to choose to invest in P2P lending, then respondents who are married, older, respondents who have a longer education time and respondents with income > Rp 20.000.000 and have previous investment experience also tend to have a willingness to lend in P2P lending. Meanwhile, respondents who have income <Rp 5.000.000 tend not to invest their capital in P2P lending platforms. Furthermore, the results of this study found that transaction costs, services, security, interest rates and risk can affect the willingness to lend of lenders or lenders. Logit results show that transaction fees, services, security and interest rates can have a positive effect, while risk factors have a negative effect. P2P lending platforms can reduce risk factors such as insurance and improve service and security.
Keyword: Investasi, P2P lending, willingness to lend

Judul: Ornithonyssus Bursa (Berlese, 1888) Famili Macronyssidae yang Menyerang Unggas Dan Penaggulangannnya
Abstrak: Ornithonyssus bursa adalah tungau penghisap darah pada unggas di daerah tropis dan subtropis. Tungau ini relatif kecil, dengan panjang tubuh antara 700-1000 mikron dan lebarnya 250-490 mikron. Tubuhnya bulat berwarna coklat kekuningan sebelum menghisap darh dan berwarna merah setelah menghisap darah dari induk semangnya.
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