Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan JUSTIN (Jurnal Sistem dan Teknologi Informasi)
Agustono, Hendri
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
AN EXAMINATION OF THE GREEN STOCK PORTFOLIO IN CONNECTION WITH THE 2024 INDONESIAN REPUBLIC PRESIDENTIAL GENERAL ELECTION Sulistianingsih, Evy; Martha, Shantika; Andani, Wirda; Agustono, Hendri; Pebriyandi, Rifki; Gunawan, Risky; Maharani, Cinta Priscillia
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2543-2556

Abstract

The presidential election of the Republic of Indonesia occurs on a frequency of once every five years. The present work investigated the impact of the 2024 Presidential Election on the performance of the optimal stock portfolio constructed by K-Means Clustering during the first phase of stock selection. Subsequently, the portfolio will be evaluated using two distinct approaches, namely Mean Absolute Deviation (MAD) and Mean-Variance Efficient Portfolio (MVEP). Both techniques were employed to construct several portfolios throughout three time periods: before the Presidential Election (13 August 2023 to 13 February 2024) and after the Presidential Election (15 February to 15 April 2024 and 20 April 2024 to 20 May 2024). This was done by implementing a mechanism to manage the allocation of shares in order to optimize the portfolio. The analyzed data is historical data on daily green stock closing prices indexed on the SRI-KEHATI index. A portfolio was constructed and subsequently evaluated for its performance using the Sharpe Index. The findings of this study suggest that the upcoming 2024 general election for the presidency of the Republic of Indonesia had a favorable impact on the Indonesian capital market, particularly for stocks that are indexed by SRI-KEHATI. This criterion was proposed based on the observation that the average Sharpe ratio index for Period II and Period III exceeds the average Sharpe ratio index for Period I (prior to the election day). The most optimal portfolio examined in this study was the MVEP portfolio, mostly composed of assets in the primary consumer products industry, with a Sharpe ratio of 0.53586. Furthermore, the performance of portfolios in period III (after the election result release) was far superior to that of other portfolios examined in previous periods.
Pemetaan Kawasan Prioritas Pengelolaan Sampah Indonesia dengan Algoritma DBSCAN Agustono, Hendri; Gunawan, Risky
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 14, No 1 (2026)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v14i1.95328

Abstract

Indonesia sebagai negara dengan jumlah penduduk terbesar keempat menghadapi tantangan pengelolaan sampah yang masif dalam pencapaian SDG 12, ditambah dengan ketimpangan infrastruktur antar 38 provinsi. Penelitian ini bertujuan mengidentifikasi dan memetakan kawasan prioritas pengelolaan sampah di tingkat provinsi untuk mendukung alokasi sumber daya yang efisien. Penelitian ini mengintegrasikan Principal Component Analysis (PCA) untuk reduksi dimensi, uji Statistik Hopkins untuk validasi klasterabilitas, penentuan jumlah klaster terbaik dengan Indeks Davies Bouldin dan Silhouette Score, serta algoritma Density Based Spatial Clustering of Application with Noise (DBSCAN) untuk pengelompokkan 38 provinsi berdasarkan lima indikator produksi sampah dari Sistem Informasi Pengelolaan Sampah Nasional (SIPSN) tahun 2023. Kebaruan penelitian terletak pada integrasi PCA, uji Statistik Hopkins, dan DBSCAN pada data pengelolaan sampah nasional 38 provinsi di Indonesia. Hasil menunjukkan terbentuknya 2 klaster utama dan 1 klaster noise dengan parameter optimal Epsilon = 0,46 dan MinPts = 2 (Indeks Davies Bouldin = 0,3877 dan Silhouette Score = 0,6). Klaster 0 atau noise berisi DKI Jakarta, Bali, Jawa Barat, Jawa Tengah, dan Jawa Timur menunjukkan tingkat penanganan sampah yang tinggi. Klaster 2 berisi Banten, Sulawesi Selatan, dan Sumatera Utara menunjukkan tingkat penanganan sampah yang moderat. Sedangkan, klaster 1 dengan 30 provinsi lainnya tergolong dalam tingkat penanganan sampah yang rendah. Berdasarkan hasil klaster tersebut, dapat disimpulkan bahwa masih banyak provinsi-provinsi di Indonesia yang perlu diprioritaskan dalam pembangunan infrastruktur pengelolaan sampah seperti TPA terpadu, fasilitas daur ulang, dan pusat pengolahan terpadu.
Co-Authors Andani, Wirda Evy Sulistianingsih Gunawan, Risky Maharani, Cinta Priscillia Martha, Shantika Pebriyandi, Rifki