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All Journal Jurnal Studi Manajemen Organisasi Jurnal Nosel Among Makarti Fon: Jurnal Pendidikan Bahasa dan Sastra Indonesia JURNAL MEDIA INFORMATIKA BUDIDARMA Barometer Building of Informatics, Technology and Science Prosiding Temu Profesi Tahunan PERHAPI International Journal of Economics Development Research (IJEDR) JURNAL ILMIAH AGRINECA Journal of Applied Data Sciences Jurnal Budaya Etnika Jurnal Bingkai Ekonomi (JBE) Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan Jurnal Ilmiah Ilmu Manajemen (JUIIM) CEMERLANG :Jurnal Manajemen dan Ekonomi Bisnis Jurnal Bangun Abdimas Optimal: Jurnal Ekonomi dan Manajemen Journal of Economics and Management Scienties
Kusmanto Kusmanto
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Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

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Clusterisasi Tingkat Pengangguran Terbuka Menurut Provinsi di Indonesia Menggunakan Algoritma K-Medoids Karim, Abdul; Esabella, Shinta; Kusmanto, Kusmanto; Suryadi, Sudi; Mardinata, Erwin
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6198

Abstract

The Open Unemployment Rate (OER) in Indonesia decreased in February 2024 to 4.82%, showing an improvement compared to February 2023. Despite the decline in TPT, there are still regions with TPT reaching 7.02%, which could potentially lead to negative consequences such as increased crime. Efforts to address TPT include increasing economic growth, developing the quality of education and training. This research utilises clustering in data mining. The number of clusters formed was 3 clusters with a DBI value of -1.685. This study uses K-Medoids clustering to group 38 provinces based on TPT. Of the 38 data, there is incomplete data so preprocessing is done using the "filter example" operator in rapidminer to eliminate incomplete data so that there are 34 data that will be used in this study (after preprocessing). The results show 4 provinces with the highest TPT (Riau Islands, DKI Jakarta, West Java, and Banten) with a percentage of 11.76%.
Enhancing Customer Loyalty in the Digital Economy: The Role of Service Quality and Satisfaction in Livin' by Mandiri Mobile Banking Kusmanto, Kusmanto; Islami, Mutiara
International Journal of Economics Development Research (IJEDR) Vol. 6 No. 1 (2025): International Journal of Economics Development Research (IJEDR)
Publisher : Yayasan Riset dan Pengembangan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/ijedr.v6i1.6958

Abstract

This research aims to determine the influence of Service Quality and Customer Satisfaction on Customer Loyalty of Mobile Bangking Livin by Mandiri KCP Tangerang STPI Curug jointly and individually and to determine the variables that have a dominant influence on Customer Satisfaction. The research method used is a causal quantitative approach. The population in this research was 336 customers. The sampling technique used purposive sampling with a total sample of 77 customers obtained using the Slovin formula. Based on the research results, it is proven that service quality has an influence of 54.3% on customer satisfaction, while the remaining 45.7% is influenced by other factors not examined in this research. The results of the F test in this study show that the calculated f value is 43.894 > f table 3.96847 and the sig. F 0.000 < 0.05, which means that Service Quality and Customer Satisfaction together have a positive and significant influence on Customer Loyalty. Based on the results of the T Test, it can be seen that the Service Quality variable partially has a positive and significant influence on Customer Loyalty. Meanwhile, the Customer Satisfaction variable does not have a positive and significant influence on Customer Loyalty. And the largest standard value of the coefficient of determination is the value of the Service Quality variable, namely 0.530, which means that the Service Quality variable has the most dominant influence on Customer Loyalty.
Pengembangan Sistem Informasi Untuk Pengelolaan Data Penduduk Karim, Abdul; Kusmanto, Kusmanto; Bobbi Kurniawan Nasution, Muhammad
Jurnal Bangun Abdimas Vol 4 No 1: Mei 2025
Publisher : PT. Bangun Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56854/ba.v4i1.520

Abstract

Teknologi informasi dan teknologi komputer yang canggih telah memberikan dampak yang signifikan terhadap berbagai aspek kehidupan manusia di setiap lapisan masyarakat. Organisasi harus memiliki sistem informasi yang dapat memenuhi kebutuhannya dalam mencapai efisiensi dan efektifitas kerja. Diharapkan pengolahan data akan menjadi lebih mudah dengan adanya sistem informasi data kependudukan. Kantor Kelurahan Karang Baru masih menggunakan pengelolaan data secara manual menggunakan Microsoft Word dan Microsoft Excel. Dengan adanya sistem informasi pengelolaan data penduduk berbasis web ini, diharapkan pegawai akan lebih mudah menyelesaikan tugas mereka dan penduduk akan mendapatkan pelayanan yang lebih cepat dan lebih baik.
Pelatihan Sistem Informasi Untuk Manajemen Sekolah Kusmanto, Kusmanto; Febriani, Budi; Dewi Siregar, Usmala
Jurnal Bangun Abdimas Vol 4 No 1: Mei 2025
Publisher : PT. Bangun Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56854/ba.v4i1.521

Abstract

Majelis Pendidikan Dasar dan Menengah Muhammadiyah Kota Medan merupakan lembaga atau organisasi yang kegiatannya terkait tentang keagamaan. Salah satu kegiatan dari Majelis Pendidikan Dasar dan Menengah Muhammadiyah Kota Medan ini yaitu mengawasi pelaporan dan melakukan Monitoring dan Evaluasi (Monev) laporan keuangan dari sekolah- sekolah muhammadiyah yang tergabung di dalam majelis tersebut agar masalah keuangan di sekolah-sekolah tersebut menjadi transparan. Berdasarkan analisis situasi khalayak sasaran yang telah dikemukakan di atas, permasalahan yang dihadapi selama ini terjadi dalam dua arah, dimana pihak majelis dan pihak sekolah sama-sama memiliki masalah dalam kegiatan monitoring dan evaluasi terhadap laporan keuangan tersebut, sehingga diperlukan solusi yang tepat untuk menyelesaikan kedua masalah tersebut. Solusi untuk masalah-masalah yang ada yaitu dengan membangun Aplikasi Sistem Informasi Keuangan Sekolah Muhammadiyah (SIKeSMu) dan memberikan pelatihan untuk penggunaan aplikasi tersebut sehingga dapat mempermudah pelaporan dan mempermudah kegiatan monitoring laporan keuangan di Sekolah-sekolah yang tergabung di Majelis Pendidikan Dasar dan Menengah Muhammadiyah Kota Medan.
Determinants Of Stock Returns and Their Implications for Dividend Policy of Mining Sector Companies on The Indonesian Stock Exchange Kusmanto, Kusmanto
Journal of Economics and Management Scienties Volume 7 No. 4, September 2025
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jems.v7i4.179

Abstract

This study analyzes the influence of fundamental microeconomic and macroeconomic factors on stock returns and their implications for the dividend policy of mining sector companies listed on the Indonesia Stock Exchange during 2019–2024. Microeconomic variables include operational cash flow, working capital, and net income, while macroeconomic variables comprise the interest rate (BI Rate) and the rupiah exchange rate (KURS). This research uses a quantitative approach with an associative method. The results show that working capital, net income, interest rates, and exchange rates significantly and positively affect stock returns, while operational cash flow has no significant effect. This indicates that investors prioritize profitability and capital efficiency over short-term cash flow. Regarding dividend policy, working capital, net income, interest rates, exchange rates, and stock returns significantly and positively influence dividend payouts. Operational cash flow, however, shows no significant impact, suggesting companies base dividend decisions more on profitability and macroeconomic conditions. Simultaneously, all studied micro and macro variables significantly affect stock returns and dividend policy. These findings emphasize that internal financial performance and external economic indicators are key considerations in investment decisions and dividend formulation. The study implies that companies should focus on profitability and efficient working capital management while accounting for macroeconomic trends to develop sustainable dividend policies. For investors, understanding both internal company performance and broader economic factors is crucial for rational investment choices.
A Hybrid LSTM–Stacking–SMOTE Model for Weather-Aware Palm Oil Price Prediction Addressing Data Imbalance and Forecast Accuracy Kusmanto, Kusmanto; Subagio, S; Manja, Erni
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.922

Abstract

Accurate forecasting of palm oil prices is crucial for agribusiness decision-making due to high market volatility influenced by dynamic weather conditions. This study proposes a novel hybrid deep learning model combining Long Short-Term Memory (LSTM), Stacking Ensemble, and Synthetic Minority Over-sampling Technique (SMOTE) to improve predictive accuracy and handle class imbalance in price trend classification. The model was trained using a multivariate time-series dataset sourced from Kaggle, consisting of daily records of temperature, humidity, rainfall, and palm oil prices. A binary classification scheme was applied by labeling instances as either price increase (class 1) or price stable/decrease (class 0), based on a 0% price change threshold. Four experimental configurations were evaluated: standard LSTM, LSTM + SMOTE, LSTM + Stacking, and the proposed LSTM + SMOTE + Stacking. The proposed model outperformed all baselines, achieving the highest accuracy of 83.12%, an F1-score of 0.8466, MAE of 0.1688, RMSE of 0.4109, and a perfect recall of 1.0000, indicating excellent sensitivity to minority class trends. In contrast, the standard LSTM achieved only 77.32% accuracy and an F1-score of 0.7224, showing limited ability in handling imbalanced data. Visualization of loss curves and confusion matrices confirmed the model’s learning stability and classification effectiveness. This study contributes a novel integration of ensemble learning and oversampling in time-series commodity forecasting and demonstrates the effectiveness of this approach in capturing weather-driven price patterns, offering a robust framework for predictive analytics in agriculture.
Co-Authors Abdul Karim Aditya, Galuh AF Aziez AF Aziez Ahmad Fauzi Fauzi AJI, BAYU Asep Jejen Jaelani, Asep Jejen Bobbi Kurniawan Nasution, Muhammad Dadang Redantan, Dadang Dalimunthe, Abdul Hakim Dewi Siregar, Usmala Eko Setia Budi Fahrezi, Moch Agung Febriani, Budi Guidio Leonarde Ginting Hardi Utomo Hariska, Elvia Hidayatullah, Muhammad Ibnu Rasyid Munthe Imam Setyobudi Joko Sampurno Manja, Erni Mardinata, Erwin Mita Widi Astuti Muhammad Syaifullah Mutiara Islami, Mutiara Nasution, Mhd Bobbi Kurniawan Purba, Elvitrianim Rahmad Aditiya Rahmawati, Putri Rahmawati Ristanto, Hesti Rizki Febriana Ronal Watrianthos Rubiyati Rubiyati, Rubiyati Samsir Samsir, Samsir Shinta Esabella Simanjorang, Elida F. S. Sri Muryanti Subagio, S Suryadi, Sudi Sutrisno, Sutrisno Tyas Soemarah KD Tyas Soemarah KD Vera Methalina Afma, Vera Methalina Wibowo, Gembong S Yuningsih, Yuyun