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All Journal JOIV : International Journal on Informatics Visualization RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Adi Widya : Jurnal Pengabdian Masyarakat JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Information Systems and Informatics Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) International Journal of Business, Law, and Education Wasana Nyata WASANA NYATA
Yusuf Sutanto
STIE-AUB Surakarta
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Neuroscience Social Sciences Veterinary Other

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Micro, Small, and Medium Enterprises Eligibility and Financial Institutions Selection for Provision Capital Sutanto, Yusuf; Purnama, Bambang Eka; Rapiyanta , Paulus Tofan
International Journal of Business, Law, and Education Vol. 6 No. 2 (2025): International Journal of Business, Law, and Education (On Progress July-Desembe
Publisher : IJBLE Scientific Publications Community Inc.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56442/ijble.v6i2.1171

Abstract

Some of the obstacles to Micro, Small, and Medium Enterprises (MSMEs) existence include difficulty in obtaining additional capital from banking institutions due to lack of employee knowledge and unfulfilled requirements. This research purpose is to determine MSMEs feasibility and  selection of appropriate financial institutions to apply for additional capital using a decision support system. There are 25 MSMEs samples in Karanganyar City to be used as research material. Decision tree algorithm is used to calculate initial decisions in specify MSMEs suitability to be given capital. AHP method is used as final decision to decide an appropriate financial institution to carry out additional capital. Accuracy level testing decision tree algorithm implementation to determine MSMEs feasibility resulted in 86.67%. Accuracy level of testing AHP method to decide financial institutions suitability resulted in 76.91%. From the test results, it can be concluded that  developed system is good or accurate.
Pelatihan dan Pendampingan Peningkatan Strategi Pemasaran Produk Kue Klepon sebagai Ikon Jajan Pasar di Kota Surakarta Wardhana, Galih Wisnu; Nugroho, Anggoro Panji; Sutanto, Yusuf
WASANA NYATA Vol 9, No 1 (2025)
Publisher : STIE AUB Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36587/wasananyata.v9i1.1986

Abstract

Kue klepon merupakan salah satu jajanan tradisional yang memiliki potensi besar untuk dikembangkan sebagai ikon kuliner daerah. Namun, pelaku usaha masih menghadapi kendala seperti strategi pemasaran konvensional, kemasan produk kurang menarik, dan minimnya pemanfaatan media digital. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan keterampilan pemasaran digital, memperbaiki desain kemasan, serta memperluas jangkauan pasar produk kue klepon. Metode pelaksanaan meliputi pelatihan strategi pemasaran digital, pendampingan pembuatan konten promosi, dan perancangan desain kemasan yang modern dan higienis. Kegiatan dilaksanakan selama tiga hari, diikuti 20 pelaku UMKM kue klepon di wilayah binaan Kota Surakarta.  Hasil kegiatan menunjukkan adanya peningkatan pengetahuan peserta dalam memanfaatkan media sosial untuk promosi, peningkatan kualitas desain kemasan, dan bertambahnya jumlah pesanan setelah promosi digital dilakukan. Kegiatan ini berkontribusi positif pada peningkatan daya saing UMKM dan pelestarian kuliner tradisional.
Extreme Learning Machine Method Application to Forecasting Coffee Beverage Sales Sutanto, Yusuf; Setyadi, Heribertus Ary; Nugroho, Wawan; Al Amin, Budi
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10465

Abstract

Sales estimates can be used to set product prices and increase expected profits. Flyover coffee shop Karanganyar does not have a methodical forecasting method to estimate and predict their need/demand for coffee beverage products. Two previous research that used Extreme Learning Machine (ELM) method in other predictions stated that ELM method has high accuracy and fast compilation time. Another research predicted jeans sales using the ARIMA model and produced an accuracy of 17.05% based on the MAPE (Mean Absolute Percentage Error) method. Menstrual cycle prediction using the Long Short-Term Memory (LSTM) method produces a MAPE value of 7.5%. Two advantages of ELM method from two previous research were used as the basis for selecting ELM method used in our study. To help predict sales of coffee beverage menus, this research utilized an artificial neural network method using ELM algorithm. ELM method consists of an input layer and an output layer connected through a hidden layer. Data used for the test was daily sales data for a month. Data used for this study consisted of 215 data samples. Daily sales data at the Flyover coffee shop were collected from June to December 2024. Based on the results and analysis of error values using MAPE method, an average error value was 8.274%. From comparison of original data results and prediction data, an average MAPE error value the best number of features and hidden neurons is 5.65%.
Co-Authors Al Amin, Budi Aris Tri Haryanto Bambang Eka Purnama Budi Al Amin Endang Saryanti Galih Setiawan Nurohim Haryanti Haryanti Heribertus Ary Setyadi Nani Irma Susanti Nugroho, Anggoro Panji Nugroho, Wawan Pudji Widodo Rapiyanta , Paulus Tofan Rina Ani Sapariyah Siti Fatonah Sumaryanto Sumaryanto, Sumaryanto Supriyanta Supriyanta Susanti, Nani Susanti, Nani Irma Wahyuningsih, Hartati Dyah wardhana, galih wisnu