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"[ABSTRAKPersaingan perusahaan pembiayaan yang begitu ketat serta peluang izin usahayang diperluas oleh pihak OJK, mendorong perusahaan menggunakan teknologi informasi untuk menciptakan keunggulan kompetitif. Namun, keterbatasan bujet dan sumber daya yang ada memaksa perusahaan untuk lebih selektif dengan memprioritaskan kebutuhan bisnis melalui aplikasi. Setiap perusahaan memiliki interpretasi yang berbeda-beda tentang aplikasi, sehingga perlu dirumuskan model yang generik dalam pengklasifikasian aplikasi. Tujuan dari penelitian ini adalah memetakan aplikasi pada perusahaan pembiayaan berdasarkan karakteristik masing-masing kuadran strategic grid. Karakteristik masing-masing kuadran dirangkum dari berbagai teori dan praktik. Dari analisis teori dan praktik tentang strategic grid, terdapat 6 karakteristik untuk kuadran key operational, 7 karakteristik untuk kuadran support, 7 karakteristik untuk kuadran strategic, dan 4 karakteristik untuk kuadran high potential. Karakteristik tersebut dituangkan ke dalam pertanyaan kuesioner. Wawancara dan observasi lapangan dilakukan untuk mengkonfirmasi jawaban atas pertanyan yang diberikan. Dari hasil pemetaan 15aplikasi berdasarkan karakteristik tersebut, diperoleh sebanyak 8 aplikasi dikuadran support, 3 aplikasi di kuadran strategic, 4 aplikasi di kuadran keyoperational, dan 0 aplikasi di kuadran high potential. Berdasarkan hasil pemetaan bahwa perusahaan pembiayaan di Indonesia sudah tergolong ke dalam era Business Intelligence dimana sistem data warehouse sudah dibangun, alat pendukung untuk kebutuhan analisis data sudah tersedia, dan perusahaan tidak lagi bergantung pada TI untuk menyediakan informasi kepada level eksekutif untuk keperluan strategis.

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ABSTRACTThe competition is so tight in financing companies and the opportunities ofextended business licenses by the OJK, encourage companies to use information technology to create competitive advantage. However, the limitations of budget and resource is forcing companies to be more selective in prioritizing business needs through the application. Each company has different interpretation ofapplications, so it is necessary to formulate a generic model in the classification application. The aim of this research is to map the finance company application based on the characteristics of each quadrant on the strategic grid. Thecharacteristics of each quadrant summarized from various theories and practices. From the analysis of the theory and practice of strategic grid, there are 6 characteristics for key operational quadrant, 7 characteristics for support quadrant, 7 characteristics for strategic quadrant and 4 characteristics for high potential quadrant. These characteristics poured into question questionnaire. Interviews and field observations conducted to confirm the answer of questions. From the mapping of 15 applications based on these characteristics, obtained as many as 8 applications in support quadrant, 3 applications in strategic quadrants, 4 applications in key operational quadrant, and 0 applications in high potentialquadrant. Based on the results of application mapping that the finance company in Indonesia has been classified into a Business Intelligence era where the data warehouse system was built, a supporting tool for requirements analysis of the data is available, and the company is no longer depend on IT to provide information to the executive level for strategic purposes. , The competition is so tight in financing companies and the opportunities ofextended business licenses by the OJK, encourage companies to use informationtechnology to create competitive advantage. However, the limitations of budgetand resource is forcing companies to be more selective in prioritizing businessneeds through the application. Each company has different interpretation ofapplications, so it is necessary to formulate a generic model in the classificationapplication. The aim of this research is to map the finance company applicationbased on the characteristics of each quadrant on the strategic grid. Thecharacteristics of each quadrant summarized from various theories and practices.From the analysis of the theory and practice of strategic grid, there are 6characteristics for key operational quadrant, 7 characteristics for support quadrant,7 characteristics for strategic quadrant and 4 characteristics for high potentialquadrant. These characteristics poured into question questionnaire. Interviews andfield observations conducted to confirm the answer of questions. From themapping of 15 applications based on these characteristics, obtained as many as 8applications in support quadrant, 3 applications in strategic quadrants, 4applications in key operational quadrant, and 0 applications in high potentialquadrant. Based on the results of application mapping that the finance company inIndonesia has been classified into a Business Intelligence era where the datawarehouse system was built, a supporting tool for requirements analysis of thedata is available, and the company is no longer depend on IT to provide information to the executive level for strategic purposes. ]"

"Optimalisasi portofolio melalui Alokasi Aset Strategis penting dilakukan oleh Badan Pengelola Keuangan Haji (BPKH) untuk meningkatkan nilai manfaat dari investasi dana haji. Nilai manfaat merupakan sumber utama bagi subsidi ongkos naik haji yang diberikan kepada jamaah, dimana nominalnya terus mengalami peningkatan setiap tahun akibat belum terlaksananya rasionalisasi ongkos naik haji dan eksposur risiko dari depresiasi rupiah. Penelitian ini menggunakan pendekatan kuantitatif dan analisis deskriptif. Tujuan penelitian ini adalah untuk mendapatkan rekomendasi alokasi pada setiap kelas aset dalam portofolio dana haji. Periode penelitian akan dibagi menjadi dua, yaitu sebelum COVID-19 (2017-2019) dan selama COVID-19 (2020-2021) untuk menguji model alokasi aset yang digunakan dapat bekerja pada dua kondisi berbeda. Hasil penelitian menunjukkan bahwa alternatif portofolio dana haji dapat dihasilkan melalui model Black-Litterman (BLO), yaitu model yang dibentuk untuk mengeliminasi kekurang-kekurangan dalam model Mean-Variance Markowitz yang cenderung tidak aplikatif dan menghasilkan biaya transaksi yang besar akibat realokasi aset yang ekstrem. Menggunakan data pada periode tahun 2017 hingga 2021, portofolio terbaik ditunjukkan oleh portofolio konservatif yang terkonsentrasi pada aset pendapatan tetap pada rentang 76% hingga 100%. Portofolio ini dihasilkan dari asumsi penilaian pesimistik BPKH akibat kondisi ekonomi yang cenderung menurun selama pandemi. Pembentukan portofolio menggunakan BLO disarankan untuk menggunakan data pada periode Pre COVID-19, karena spesifik menggunakan periode COVID-19 sebagai dasar alokasi, dihasilkan portofolio yang berkinerja lebih rendah akibat ketidaksesuaian asumsi penilaian dengan kondisi aktual.

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Portfolio optimization through Strategic Asset Allocation is important to be carried out by the Hajj Financial Management Agency (BPKH) to increase the value of benefits from investment in hajj funds. The value of benefits is the main source of subsidies for the cost of the pilgrimage given to pilgrims, where the nominal continues to increase every year due to the risk of IDR depreciation and the rationalization of the cost of the pilgrimage has not been implemented. This study uses a quantitative approach and descriptive analysis. The purpose of this study was to obtain recommendations for the allocation of each asset class in the Hajj fund portfolio. The research period will be separated, before COVID-19 (2017-2019) and during COVID-19 (2020-2021) to test the asset allocation model used to work in two different extreme conditions. The results of the study show that alternative hajj fund portfolios can be generated through Black-Litterman model (BLO), a model that is formed to eliminate deficiencies in the Markowitz Mean-Variance model which tends to be inapplicable and generates large transaction costs due to extreme asset reallocation. Using data for the period 2017 to 2021, the most optimum portfolios are shown by the conservative portfolios that concentrated in fixed income assets in the range of 76% to 100%. These portfolios were mostly generated from BPKH's pessimistic view due to economic conditions that tend to decline during the pandemic. It is recommended to form the portfolios using Pre COVID-19 period data in BLO, because when specifically uses the COVID-19 period as the basis for allocation, the portfolios’ performance are lower due to the unaligned view with the actual conditions."

"Pemilihan portofolio adalah salah satu bidang penelitian yang menarik dan penting di bidang keuangan karena masa depan dan ketidak beraturan pasar keuangan yang tidak dapat diprediksi. Setiap investor berharap mendapatkan tingkat pengembalian yang tinggi untuk portofolio mereka dengan risiko sekecil mungkin dan hal ini sulit dicapai, sehingga investor mencoba menyeimbangkan kinerja dan risiko portofolio melalui diversifikasi. Tujuan penelitian ini adalah untuk menyelidiki strategi pemilihan portofolio melalui metode clustering dan Genetic Algorithm. Clustering digunakan untuk diversifikasi portofolio dengan membentuk sekelompok aset homogen berdasarkan karakteristik rasio keuangan mereka. Ada tujuh rasio keuangan yang akan digunakan, yaitu EPS, PER, PEG, ROE, DER, Current Ratio, dan Profit Margin. Dalam skripsi ini digunakan algoritma Density Based Clustering of Application with Noise sebagai metode clustering DBSCAN. Setelah fase clustering, Genetic Algorithm digunakan untuk membentuk portofolio optimum. Genetic Algorithm secara otomatis memilih portofolio dengan risiko dan pengembalian yang optimal berdasarkan hasil clustering dengan memutuskan aset dan bobot masing-masing yang akan dimasukkan dalam portofolio. Algoritma genetika didasarkan pada model Mean Variance Cardinality Constrained Portofolio Optimization MVCCPO dan disebut metode Genetic Algorithm dengan kendala. Metode ini berhasil memberikan tingkat pengembalian dan Sharpe ratio yang lebih tinggi 25,35 dan 17,20 dibandingkan dengan indeks S P 500 pada periode waktu yang sama dengan tingkat pengembalian dan Sharpe ratio masing-masing 12,34 dan 2,7.

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Portfolio selection is one of the interesting and important fields of research in finance because of the unpredictable future and randomness of the financial market. Every investor is hoping to get a high rate of return for their portfolio with as little risk as possible, which is hard to achieve, so investors try to balance the performance and risk of the portfolio through diversification. The motivation of this research is to investigate the portfolio selection strategies through clustering method and application of genetic algorithm. Clustering is used to diversify the portfolio by forming a homogenous cluster of assets with respect to their financial ratios characteristic. There are seven financial ratio characteristics that is used, they are EPS, PER, PEG, ROE, DER, Current Ratio and Profit Margin.

In this thesis, Density Based Clustering Algorithm with Application of Noise used as the clustering method DBSCAN. After the clustering phase, genetic algorithm used for portfolio selection. Genetic Algorithm automatically select the optimum risk and return portfolio based on the clustered asset by deciding which assets and their respective weights included in the portfolio. The genetic algorithm is based on the Mean Variance Cardinality Constrained Portofolio Optimization MVCCPO model and called a Constrained Genetic Algorithm. The method succesfully give a higher level of return 25,35 and Sharpe ratio 17,20 compared to S P 500 index in the same period of time 12.34 and 2.7 respectively."

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