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Classification of Money Market Mutual Fund Products in Indonesia By Using Mahalanobis Distance and Manhattan Distance Indrawan; Azka, Muhammad; Kamila, Isti; Rauf, Nurul Maqfirah; Santoso, Eka Krisna
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.6143

This study aims to classify money market fund products listed and supervised by the Financial Services Authority (OJK) with minimal classification error. Mahalanobis distance and Manhattan distance were employed to classify these products. Data was sourced from the Indo Premier Online Technology (IPOT) application. Variables utilized in this research include percentage return, Sharpe ratio, unit growth, and Asset Under Management (AUM) . Additionally, Principal Component Analysis (PCA) was employed to reduce data dimensionality by linearly combining correlated original variables into new variables (principal components). PCA was used to visualize data with more than three dimensions. Based on the principal component analysis, the first two principal components captured 74.43% of the original data information, while the first three principal components captured 98.94%. Classification results using three principal components and standardized data showed the same error rates: 13.33% for Mahalanobis distance and 6.67% for Manhattan distance. For the two principal components, both Mahalanobis and Manhattan distances resulted in an error rate of 13.33%. Therefore, Manhattan distance is the most effective method for classification. Forecasting results indicate that mutual fund A is a good investment choice, while mutual fund B is a poor one. Keywords: Mahalanobis distance; Manhattan distance; Principal Component Analysis

Training on Strategies to Pass CPNS Test for CPNS Applicants Through the Giat Belajar Abadi Platform Santoso, Eka Krisna; Azka, Muhammad; Kamila, Isti; Indrawan; Rauf, Nurul Maqfirah; Bahar, Nur Qadri
Jurnal Pengabdian Masyarakat Inovatif Vol. 2 No. 2 (2024): JPMI (Jurnal Pengabdian Masyarakat Inovatif)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/jpmi.v2i2.142

The acceptance of Civil Servant Candidates (CPNS) is an opportunity highly anticipated by the community to build a career in the government sector. However, tight competition and complex selection stages are often the main challenges for applicants. Many applicants fail due to a lack of understanding of the selection process, ineffective learning strategies, and minimal information about the success criteria. The partner of this Community Service activity is Giat Belajar Abadi. Giat Belajar Abadi (GBA) is a lifelong learning platform designed to help people improve their skills and expand their knowledge. This platform offers a variety of classes and learning programs related to business, self-development, and more. However, Giat Belajar Abadi has not yet opened a class for training strategies to pass the Civil Servant Candidate (CPNS) test. Therefore, a community service program is needed for Giat Belajar Abadi partners by opening a training class on CPNS test strategies. This class will help CPNS applicants to be better prepared for the selection, both technically and mentally, increasing their chances of success. The purpose of this Community Service activity is to increase understanding of CPNS selection strategies through Giat Belajar Abadi partners. Therefore, the target audience of this activity is CPNS applicants. The outcome of this Community Service program is an increased understanding of CPNS selection strategies. Through this program, it is hoped that the success rate of participants in the CPNS selection will increase, while creating more competent human resources ready to contribute to the government sector. This program also has a long-term impact on improving the quality of CPNS applicants’ preparation in the future.

Training on Strategies to Pass CPNS Test for CPNS Applicants Through the Giat Belajar Abadi Platform Santoso, Eka Krisna; Azka, Muhammad; Kamila, Isti; Indrawan; Rauf, Nurul Maqfirah; Bahar, Nur Qadri
Jurnal Pengabdian Masyarakat Inovatif Vol. 2 No. 2 (2024): JPMI (Jurnal Pengabdian Masyarakat Inovatif)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/jpmi.v2i2.142

The acceptance of Civil Servant Candidates (CPNS) is an opportunity highly anticipated by the community to build a career in the government sector. However, tight competition and complex selection stages are often the main challenges for applicants. Many applicants fail due to a lack of understanding of the selection process, ineffective learning strategies, and minimal information about the success criteria. The partner of this Community Service activity is Giat Belajar Abadi. Giat Belajar Abadi (GBA) is a lifelong learning platform designed to help people improve their skills and expand their knowledge. This platform offers a variety of classes and learning programs related to business, self-development, and more. However, Giat Belajar Abadi has not yet opened a class for training strategies to pass the Civil Servant Candidate (CPNS) test. Therefore, a community service program is needed for Giat Belajar Abadi partners by opening a training class on CPNS test strategies. This class will help CPNS applicants to be better prepared for the selection, both technically and mentally, increasing their chances of success. The purpose of this Community Service activity is to increase understanding of CPNS selection strategies through Giat Belajar Abadi partners. Therefore, the target audience of this activity is CPNS applicants. The outcome of this Community Service program is an increased understanding of CPNS selection strategies. Through this program, it is hoped that the success rate of participants in the CPNS selection will increase, while creating more competent human resources ready to contribute to the government sector. This program also has a long-term impact on improving the quality of CPNS applicants’ preparation in the future.

Uncovering the potential of mining stocks: Analysis of price prediction and fundamental performance using double exponential smoothing and discounted cash flow Kamila, Isti; Mushliha; Indrawan; Azka, Muhammad; Sembiring, Brema
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202528611

The purpose of this research was to forecast the stock prices of the mining sector using the Double Exponential Smoothing method and to determine the intrinsic value of stocks using the Discounted Cash Flow method as a recommendation for investment decisions in stocks. The data used was secondary data consisting of closing prices and financial reports from 2022 to 2024 for 10 mining stocks listed on the Main Board of the Energy sector on the IDX website. Based on the results of determining the intrinsic value of the stocks using the DCF method, seven mining stock issuers were categorized as undervalued, namely ABMM, BUMI, BYAN, DEWA, GEMS, HRUM, and INDY, while three other stock issuers were categorized as overvalued, namely ADRO, DSSA, and ITMG. Based on the forecasting results using the Double Exponential Smoothing method, from the seven issuers in the undervalued category, there were two issuers, BYAN and DEWA, that have the potential to experience a price increase. The results of the stock price forecasting evaluation using MAPE show that it was categorized as very accurate with a MAPE value range of 0.6% to 3.5%.

Forecasting Sharia Stock Prices Using Hybrid STL Decomposition–LSTM and SARIMA Models: A Case Study of PT Semen Indonesia (Persero) Tbk Indrawan Indrawan; Muhammad Azka; Putri Amalia
Journal of Mathematics, Computations and Statistics Vol. 9 No. 2 (2026): Volume 09 Issue 02 (June 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/2ane1252

Stock price forecasting is a challenging task due to the complex, nonlinear, and dynamic nature of financial time series data. This study aims to develop a hybrid forecasting model by integrating Seasonal and Trend Decomposition using Loess (STL) with Long Short-Term Memory (LSTM) and to compare its performance with the Seasonal Autoregressive Integrated Moving Average (SARIMA) model as a linear benchmark. The empirical analysis is conducted using daily closing price data of PT Semen Indonesia (Persero) Tbk (SMGR) over the period from March 2018 to March 2026. The proposed approach applies STL decomposition to separate the time series into trend, seasonal, and residual components, enabling the LSTM model to capture nonlinear patterns more effectively. Forecasting performance is evaluated using the Mean Absolute Scaled Error (MASE) on an out-of-sample testing dataset. The results show that the hybrid STL–LSTM model achieves superior accuracy, with a MASE value of 0.4738, significantly outperforming the SARIMA model, which yields a MASE value of 2.7073. In contrast, the SARIMA model produces overly smooth forecasts and fails to capture short-term fluctuations and nonlinear dynamics present in the data. These findings indicate that the integration of STL decomposition and LSTM provides a more effective and flexible framework for modeling complex financial time series. The proposed model not only improves forecasting accuracy but also produces stable and reliable predictions, making it suitable for practical applications in stock price forecasting.

Inovasi Olahan Ikan Lele dan Pembuatan Mesin Spinner untuk Mendukung Pemberdayaan Masyarakat Kampung Pelita Habibie, Fadeli Muhammad; Indrawan, Indrawan; Qurrohman, Taufik; Berlian, Pio Putra; Mampow, Vanessa Keysa Immanuela; Shofa, Ghina Zahira; Damayanti, Siska; Susilo, Budi; Ramadhani, Tyas Ayu; Hermawan, Aditiya
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 17, No 1 (2026): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v17i1.26674

Kampung Pelita Sumber Rejo yang terletak di tengah Kota Balikpapan dikenal dengan kegiatan budidaya kolam ikan lele yang menjadi komoditas utama masyarakat setempat. Selain dijual sebagai ikan segar, sebagian hasil panen juga diolah menjadi berbagai produk makanan seperti pempek, otak- otak, dan nugget lele. Namun, proses pengolahan tersebut menghasilkan limbah berupa kulit dan tulang ikan yang belum dimanfaatkan secara optimal, padahal limbah tersebut memiliki potensi untuk diolah menjadi produk pangan bernilai tambah. Untuk menjawab permasalahan ini, diperlukan pendampingan teknologi dan inovasi dalam pemanfaatan limbah hasil olahan ikan. Melalui program pengabdian masyarakat yang berkolaborasi dengan mitra UP2K Kampung Pelita, dilakukan upaya peningkatan produktivitas yang juga didukung dengan pembuatan mesin spinner sederhana sebagai alat bantu produksi. Kegiatan telah dilaksanakan dengan baik ini dengan memberdayakan UP2K dalam mengolah limbah ikan lele menjadi produk amplang dan kerupuk kulit, sekaligus melaksanakan rebranding usaha untuk memperkuat identitas pasar. Dengan demikian, kegiatan pengabdian masyarakat ini tidak hanya menghasilkan produk alternatif, tetapi juga memperkuat daya saing usaha, memperluas peluang pemasaran, serta berkontribusi terhadap peningkatan kesejahteraan masyarakat secara berkelanjutan.

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