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Alfa Value Scalability on Single and Double Exponential Smoothing Comparatives Yuli Astuti; Irma Rofni Wulandari; Muhammad Noor Arridho; Erni Seniwati; Dina Maulina
IJISTECH (International Journal of Information System and Technology) Vol 5, No 4 (2021): December
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v5i4.165

To find out sales forecasts in the future, it is not only based on estimates but must be calculated carefully based on the experience of previous sales transactions. This observation can be made based on sales data a few months ago to be used as actual data to get predictive value in the future period. Prediction or forecasting is done with two methods Single Exponential Smoothing (SES) and Double Exponential Smoothing (DES), from these two methods, will be sought the most suitable alpha value to get the percentage error value. There are two error values : Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). By using sales data from February to December 2019, the predicted value of 430 orders was obtained in the SES method and resulted in a sales prediction of 402 orders in the DES method with the smallest error accuracy value of 26.88% in the SES method and an accuracy value of 22.71%. in the DES method with the acquisition of scalability of the right alpha value for both, namely 0.3 and the beta value of 0.3 in the DES method

Penerapan Metode Single Exponential Smoothing untuk Memprediksi Penjualan Katering pada Kedai Pojok Kedaung Muhammad Noor Arridho; Yuli Astuti
Jurnal Teknik Informatika UMUS Vol 2 No 02 (2020): November
Publisher : Universitas Muhadi Setiabudi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46772/intech.v2i02.288

Kedai Pojok Kedaung merupakan sebuah Rumah Makan yang sudah lebih dari 10 tahun dan banyak dikenal oleh masyarakat luas khususnya dilingkungan masyarakat Kalimantan Timur, yang sudah menjadi partner dalam melayani jasa catering untuk perusahaan pertambangan. Namun, di dalam proses pengelolaan data masih dilakukan secara manual menggunakan alat tulis, kalkulator, buku sebagai media pencatatan dan disimpan dalam bentuk arsip yang tidak tertata rapi. Selain itu, dalam membuat laporan sering terjadi kesalahan dalam penghitungan. Hal tersebut menyebabkan tingginya risiko kesalahan dan kehilangan informasi data-data yang dikelola. Sehingga membutuhkan waktu yang relatif lama untuk mengatur proses bisnis yang ada disana. Selanjutnya, setiap jenis usaha apapun tentu memerlukan persiapan agar dapat menunjang proses penjualannya. Dalam memenuhi permintaan pesanan katering yang tidak menentu terkadang menimbulkan masalah saat ada permintaan dalam jumlah yang lebih besar ataupun kecil. Berdasarkan permasalahan di atas, maka akan dikembangkan suatu Sistem prediksi yang dapat menangani, mengolah dan meminimalisir kesalahan data-data tersebut. Serta dapat membantu pemilik dalam mengelola usahanya. Didalam implementasinya data yang diolah sebanyak 11 periode yang disajikan per bulan, hasil yang didapatkan dari penelitian ini adalah hasil analisa dari metode Single Exponential Smoothing untuk memperoleh informasi prediksi penjualan dan nilai kesalahan serta persentase kesalahan menggunakan metode MAD dan MAPE.

Alfa Value Scalability on Single and Double Exponential Smoothing Comparatives Yuli Astuti; Irma Rofni Wulandari; Muhammad Noor Arridho; Erni Seniwati; Dina Maulina
IJISTECH (International Journal of Information System and Technology) Vol 5, No 4 (2021): December
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v5i4.165

To find out sales forecasts in the future, it is not only based on estimates but must be calculated carefully based on the experience of previous sales transactions. This observation can be made based on sales data a few months ago to be used as actual data to get predictive value in the future period. Prediction or forecasting is done with two methods Single Exponential Smoothing (SES) and Double Exponential Smoothing (DES), from these two methods, will be sought the most suitable alpha value to get the percentage error value. There are two error values : Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). By using sales data from February to December 2019, the predicted value of 430 orders was obtained in the SES method and resulted in a sales prediction of 402 orders in the DES method with the smallest error accuracy value of 26.88% in the SES method and an accuracy value of 22.71%. in the DES method with the acquisition of scalability of the right alpha value for both, namely 0.3 and the beta value of 0.3 in the DES method

ANALISIS ASPEK-ASPEK KUALITAS SKEMA DATABASE KING AKOR’S SRAGEN Andhika Wisnu Widyatama; Rizky Arya Kurniawan; Hani Setiani; Muh Wal Ikram; Muhammad Noor Arridho; Alvian Trias Kurniawan; Ema Utami
Journal of Information System Management (JOISM) Vol. 2 No. 2 (2021): Januari
Publisher : Universitas Amikom Yogyakarta

Peran basis data dalam sistem informasi adalah membantu pengelolaan data untuk pengambilan keputusan. Salah satu faktor penentu keberhasilan dalam pengambilan keputusan yaitu kualitas data. Adapun dimensi dari kualitas data yang akan diteliti pada kali ini adalah aspek kemampuan dibaca, agar terwujud kualitas data yang baik perlu dilakukan pengukuran apakah skema basis data dapat dijelaskan dan mudah di pahami. Analisis yang dilakukan pada King’s Akor Sragen menunjukan bahwa dengan mengidentifikasi permasalahan aspek kemampuan dibaca, maka penelitian ini menghasilkan kualitas skema basis data yang dimiliki sudah memenuhi kriteria tersebut. sehingga memudahkan teknisi baru untuk melakukan pengembangan sistem.

PERGERAKAN NILAI AKTIVA BERSIH (NAB) BERDASARKAN EVALUASI KESALAHAN METODE DOUBLE EXPONENTIAL SMOOTHING PADA REKSA DANA BNI-AM DANA LANCAR SYARIAH Muhammad Noor Arridho; Kusrini Kusrini; Muhammad Rudyanto Arief
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 3 No. 2 (2022): Desember 2022
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v3i2.64

Mutual funds are a place to raise public funds managed by legal entities which are then invested in se-curities in the form of stocks, bonds and money markets. In essence, investing can increase welfare in the future. However, the interest of the Indonesian people in investing is relatively low. Along with the devel-opment of mutual fund technology, it has become known to the wider community through the presence of capital market service application providers. although, mutual funds have a small risk, as capital increas-es the risk increases. In this study, the researcher predicts the movement of net asset value (NAV) in the BNI-AM Dana Lancar Syariah mutual fund using the Double Exponential Smoothing method with 1 varia-ble to give preference in minimizing investment risk.. Predictions were made based on historical data for the period from January to March 2022 and an evaluation of the MAPE prediction error of 0.0107% and MAD 0.171248 using an alpha weighting of 0.4.

Early Detection of Type 2 Diabetes Using C4.5 Decision Tree Algorithm on Clinical Health Records Setiani, Hani; Arridho, Muhammad Noor; Supriyanto, Supriyanto
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.10190

Type 2 Diabetes is a chronic metabolic disorder marked by elevated blood glucose levels. It is the most prevalent form of diabetes in society, commonly triggered by poor lifestyle habits and hereditary factors. If left unmanaged, the disease can lead to serious complications such as hypertension and other chronic conditions. Therefore, early detection plays a critical role in minimizing long-term impacts and promoting healthier behavioral changes. This research focuses on classifying Type 2 Diabetes using clinical data with the C4.5 Decision Tree algorithm. The dataset encompasses attributes including gender, age, height, weight, waist circumference, BMI, systolic and diastolic blood pressure, respiratory rate, and pulse rate. The model was evaluated under two scenarios: without data balancing and after applying the SMOTE technique for balancing. In the first scenario, the best performance was achieved with a training-testing split of 80:20, resulting in an F1 Score of 67.76%. However, the performance varied across different data proportions. In contrast, the second scenario showed more consistent results, with the 60:40 split yielding the highest F1 Score of 66.67%. These findings suggest that SMOTE effectively reduces bias toward the majority class and enhances sensitivity to the minority class. Therefore, data balancing is a crucial step in developing a reliable classification model for Diabetes Mellitus diagnosis.

Implementation of Fault Tree Analysis for Production Quality Control Evaluation Zulfahmi Noor; Nurmasitya Kemalaintan; Muhammad Noor Arridho
Asian Journal Science and Engineering Vol. 4 No. 2 (2025): Asian Journal Science and Engineering
Publisher : CV. Creative Tugu Pena

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51278/ajse.v4i2.2111

This study aims to evaluate the quality control of lightweight brick production at PT XYZ using the Fault Tree Analysis (FTA) method. In the manufacturing industry, product defects are a major challenge that can affect production efficiency, operating costs, and company competitiveness. Based on production data from January to December 2024, the total number of defects identified reached 125,334 units, consisting of three main types, namely cracks (63%), peeling (21%), and imprecision (16%). Through the application of FTA, this study revealed that the two dominant factors that are the root causes of product defects are human error and tools or equipment. Human error is mainly triggered by operator carelessness, overly rapid mold dismantling processes, and errors in installing cutting tools. Meanwhile, machine factors include worn components, excessive vibration, deteriorating cutting wire quality, and lack of regular maintenance. The results of the study emphasize the need for a comprehensive improvement strategy through increasing operator competence, enforcing work discipline, scheduled machine maintenance, and standardizing operational procedures. The implementation of these improvements is expected to reduce the defect rate and improve product quality in a sustainable manner.

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