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All Journal SKANIKA: Sistem Komputer dan Teknik Informatika Indonesian Community Journal
Riskiana Wulan
Universitas Budi Luhur, Indonesia
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Engineering Environmental Science Public Health Social Sciences Other

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PKM Penerapan Teknologi Aplikasi Zakat Berbasis Mobile Application Pada Masjid Raudhotul Jannah Komplek Taman Cipulir Estate Agus Umar Hamdani; Indra Indra; Puspita Rani; Riskiana Wulan
I-Com: Indonesian Community Journal Vol 4 No 2 (2024): I-Com: Indonesian Community Journal (Juni 2024)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/icom.v4i2.4407

Abstract

Optimizing the management of zakat funds can be used to empower the economy of the poor so as to reduce poverty levels. Therefore, there needs to be a body tasked with managing zakat funds so that they can provide optimal contributions to the community. The zakat administrators of the Roudhotul Jannah Taman Cipulir Estate Mosque were given the task of collecting and managing zakat funds from mosque congregations. This service is carried out by writing in a book and inputting zakat funds through the zakat management website. The weakness of the current zakat management is that the data collection process for muzakki and mustahiq is still carried out by zakat administrators, causing the administration process to be slow. Apart from that, prospective muzakki who are outside the mosque environment cannot be served well. Based on the conditions above, training and assistance in managing zakat is needed for the zakat administrators of the Raudhotul Jannah Mosque in order to create optimal services. The method used in this activity is training and mentoring. This activity takes the form of training on the use of mobile application-based zakat management applications for zakat administrators. Based on the evaluation of the implementation of this community service activity, the percentage of partner satisfaction was 88% and the percentage of mobile application-based zakat management application testing was 96%, so it is hoped that there will be an increase in knowledge and understanding regarding good zakat governance and can continue to be used in the future..
IMPLEMENTASI ALGORITMA MULTINOMIAL NAÏVE BAYES UNTUK MENDETEKSI TWEET UJARAN KEBENCIAN BAHASA INDONESIA TERHADAP PSSI Wulan, Riskiana; Hertanto, Indra
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 8 No 1 (2025): Jurnal SKANIKA Januari 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v8i1.3355

Abstract

This study focuses on the application of the Multinomial Naive Bayes algorithm to detect hate speech in Indonesian tweets and test its accuracy level. According to The 2022 World Football Report, around 69% of Indonesia's population shows a high interest in football, creating a positive digital environment. The Dataset used consists of tweet data related to PSSI and politic taken from Twitter, which is then manually labeled into three classes, namely non-HS (Hate Speech), insults and provocations. The Dataset used consists of 2,210 tweets taken from Twitter, then manually labeled into three classes, namely non-HS (Hate Speech), insults, and provocations. Before dividing the Dataset into train and test data, an undersampling technique was applied to handle class imbalance, with the aim of ensuring a balanced distribution between the three categories. After undersampling, the training Dataset consisted of 350 tweets and the test Dataset consisted of 88 tweets. Evaluation of each method was carried out using matrix precision, recall, and F1-score. The results of the study indicate that the Multinomial Naïve Bayes algorithm obtained an accuracy of 62%. This accuracy result is expected to be useful for developing an effective and accurate hate speech detection model on social media platforms, especially Twitter, so that it can help reduce the awareness of the Indonesian people about the dangers of the spread of hate speech.
Implementasi Jaringan Syaraf Tiruan Backpropagation untuk Peramalan Penjualan pada PT. Central Pacific Development Indra Hertanto; Riskiana Wulan; Lutfi Rizaldi Mahida; Dzaky Rakha Meilano; Prayoga Ajitya Setiawan; Indra Indra
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 8 No 2 (2025): Jurnal SKANIKA Juli 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v8i2.3589

Abstract

Central Pacific Development possesses an abundance of sales transaction data, yet currently lacks a system to optimally leverage this data for strategic planning. This research aims to implement an Artificial Neural Network (ANN) using the Backpropagation method to predict product sales, based on historical data from January 2022 to November 2024. The system involves stages such as data normalization, splitting the dataset into training and testing sets, and evaluating model performance using Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) metrics. A Multi-Layer Perceptron (MLP) model with a 12-15-1 configuration yielded the best results, achieving a training MSE of 0.000999, a testing MSE of 0.062680, a MAPE of 22.24%, and an accuracy of 77.75%. The developed system can assist the company in designing data-driven production and marketing strategies, while also opening opportunities for further development through the integration of big data technologies or hybrid methods to improve prediction accuracy.
Co-Authors Agus Umar Hamdani Dzaky Rakha Meilano Hertanto, Indra Indra Hertanto Indra Indra indra indra Lutfi Rizaldi Mahida Prayoga Ajitya Setiawan Puspita Rani