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All Journal ETIKONOMI Jurnal Keuangan dan Perbankan Gadjah Mada International Journal of Business Journal of Accounting and Investment Binus Business Review INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Artificial Intelligence and Data Mining Prosiding Working Papers Series In Management Jurnal Kreativitas PKM Jurnal Manajemen Jurnal Bakti Masyarakat Indonesia Ilomata International Journal of Management International Journal of Engagement and Empowerment (IJE2) Empowerment Society Jurnal Mahasiswa Karakter Bangsa Seulanga : Jurnal Pendidikan Anak Indonesian Capital Market Review eProceedings of Engineering Madani : Jurnal Pengabdian Kepada Masyarakat Karimah Tauhid
Siti Saadah
Universitas Katolik Indonesia Atma Jaya, Jakarta
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Other

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Prosedur Akuntansi Penerimaan dan Pengeluaran Kas Pada Kantor Kecamatan Cicurug Saadah, Siti; Lasmana, Andy
Karimah Tauhid Vol. 4 No. 3 (2025): Karimah Tauhid
Publisher : Universitas Djuanda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30997/karimahtauhid.v4i3.17291

Abstract

Penelitian ini bertujuan untuk mengetahui prosedur akuntansi penerimaan serta pengeluaran kas yang dilaksanakan oleh Kantor Kecamatan Cicurug, menggunakan metode kualitatif deskriptif, dengan partisipan dari bagian keuangan, perencanaan, dan evaluasi kantor kecamatan Cicurug. Wawancara, observasi, dan dokumentasi dilakukan untuk memperoleh data. Hasilnya, prosedur akuntansi penerimaan dan pengeluaran kas di kantor kecamatan cicurug sesuai dengan Permendagri No. 77 Tahun 2020, dengan Penerimaan kas yang sepenuhnya berasal dari APBD. Selain itu, mekanisme uang persediaan, ganti uang, serta pembayaran langsung untuk gaji serta tunjangan, dilakukan saat melakukan Pengeluaran kas di kantor Kecamatan Cicurug.
Stock liquidity and stock returns: the moderating role of financial constraints Veronika Daniar Febrianti; Siti Saadah
Journal of Accounting and Investment Vol. 24 No. 2: May 2023
Publisher : Universitas Muhammadiyah Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jai.v24i2.16483

Abstract

Research aims: This study aims to analyze the effect of stock liquidity on stock returns in large and small capitalization companies and the moderating role of financial constraints in the relationship. Design/Methodology/Approach: In this study, panel data analysis was conducted on 113 manufacturing sector companies on the Indonesia Stock Exchange from 2015 to 2019, grouped into small and large capitalization companies. To avoid measurement errors from applying the KZ index, which is very likely to occur, this study used the upper quartile (Q3) of the Debt-to-Equity Ratio (DER) and a dummy variable as an artificial variable to measure financial constraints instead of the KZ index.Research findings: The results highlighted that liquidity is a predictor that could significantly explain the movement of stock returns in this sector. Investors, thus, will require additional compensation in the form of higher returns for holding less liquid stock. The study also found a significant moderating role of financial constraints. Consequently, as the illiquidity of stocks increases, additional greater compensation will be requested by investors on the stocks of companies experiencing financial constraints.Theoretical contribution/Originality: This study provides additional empirical evidence for the studies documented that investors will ask for additional return compensation for stocks with low liquidity, and investors will demand higher additional returns in companies experiencing financial constraints. This finding indicates that liquidity is essential in risk premium forming stock returns.Practitioner/Policy implication: This study can be used for investors or traders when choosing an investment strategy to be carried out.
The Influence of the Learning Environment in Shaping Early Childhood Learning Motivation Oktaviana, Yogi; Azzahra, Rizqina; Saadah, Siti
Seulanga : Jurnal Pendidikan Anak Vol. 6 No. 1 (2025): Seulanga : Jurnal Pendidikan Anak
Publisher : Jurusan Pendidikan Islam Anak Usia Dini

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47766/seulanga.v6i1.6070

Abstract

Early childhood learning motivation is the most important development in learning aspect motivation. The learning environment greatly influences the learning process, which must create a conducive and supportive environment, because it significantly affects early childhood learning motivation. Early childhood learning motivation is influenced by various factors, which include parental support, teacher quality, and adequate facilities. Therefore, early childhood learning motivation must be created, because it greatly affects their enthusiasm for learning. The purpose of this paper is to analyze the effect of learning environment on early childhood learning motivation, with several factors considered. This study found that the interaction between parents and children, teachers and children, friends and children greatly influences early childhood learning motivation. This research has significant implications for developing appropriate learning strategies, thus providing high learning motivation for early childhood. The research method used is the literature method with journal and observation collection techniques. Which from the results of this study strongly proves that the learning environment and motivation for early childhood is very influential on themselves for the next level
Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) Methods to Forecast Daily Turnover at BM Motor Ngawi Larasati, Larasati; Saadah, Siti; Yunanto, Prasti Eko
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 1 (2024): March 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i1.27643

Abstract

The number of motorcycles on the report of Indonesian BPS statistics from the Indonesian State Police between 2019 to 2021 by its type has increased annually. Routine motorcycle checks, services, and maintenance are essential to keep a motorcycle in good condition and more durable; therefore, buying spare parts is enlarged in line with the growth of public motorcycle ownership. The necessity of buying spare parts increases with the growth of public motorcycle ownership. Numerous stores in Ngawi offer motorcycle spare parts and check services for routine motorcycle maintenance. One of these stores is BM Motor. To develop an effective product-selling strategy, it is essential to forecast the daily turnover of the shop. To achieve this, the present research aims to analyze the daily turnover using Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM). These methods were applied to a time-series dataset, allowing for an in-depth examination of the patterns and trends in the shop's turnover. The research compares several hyperparameter tunings and scenarios to optimize the models that forecast daily turnover data at the store. The outcomes presented that the LSTM model achieved a lesser MAE score of 0.087, while the RNN model scored 0.092. These findings proved that the LSTM model achieved lower MAE than the RNN model, it means LSTM is more accurate than the RNN model.
Forecasting of GPU Prices Using Transformer Method Faisal Hadi, Risyad; Saadah, Siti; Adytia, Diditq
eProceedings of Engineering Vol. 10 No. 5 (2023): Oktober 2023
Publisher : eProceedings of Engineering

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Abstract

Abstract— GPU or VGA (graphic processing unit) is a vital component of computers and laptops, used for tasks such as rendering videos, creating game environments, and compiling large amounts of code. The price of GPU/VGA has fluctuated significantly since the start of the COVID19 pandemic in 2020. This research aims to forecast future GPU prices using deep learning-based time series forecasting using the Transformer model. We use daily prices of NVIDIA RTX 3090 Founder Edition as a test case. We use historical GPU prices to forecast 8, 16, and 30 days. Moreover, we compare the results of the Transformer model with two other models, RNN and LSTM. We found that to forecast 30 days; the Transformer model gets a higher coefficient of correlation (CC) of 0.8743, a lower root mean squared error (RMSE) value of 34.68, and a lower mean absolute percentage error (MAPE) of 0.82 compared to the RNN and LSTM model. These results suggest that the Transformer model is an effective and efficient method for predicting GPU prices.Keywords— GPU, Transformer, Forecasting, Time Series Forecasting
Prediksi Harga Dogecoin Berdasarkan Sentimen dari Twitter Menggunakan LSTM Prasetyo Nugroho, Ecky; Saadah, Siti; Afianti, Farah
eProceedings of Engineering Vol. 10 No. 5 (2023): Oktober 2023
Publisher : eProceedings of Engineering

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Abstract

Abstrak— Dogecoin adalah mata uang kripto yang diciptakan oleh Billy Markus dan Jackson Palmer, tetapi mereka membuat Dogecoin hanya untuk dibuat sebagai bahan candaan di dunia mata uang kripto. Tugas akhir ini menganalisis sentimen dan prediksi terhadap Doge dengan melakukan korelasi antara harga Doge terhadap data yang dikumpulkan dari media social Twitter mengenai Doge. Penelitian ini dilakukan menggunakan pendapat-pendapat yang disampaikan oleh pengguna jejaring sosial yang menggunakan bahasa Inggris. Metode yang digunakan adalah LSTM dengan mengacu pada penelitian-penelitian sebelumnya yang menunjukkan bahwa LSTM memberikan akurasi tertinggi. Data yang digunakan pada penelitian ini adalah harga doge dan tweet pada periode januari-april 2021. Menentukan korelasi antara doge dan tweet dilakukan dengan korelasi pearson dimana hasil korelasi tersebut menentukan korelasi positif, korelasi negatif dan tidak berkorelasi, setelah itu dilakukan prediksi harga doge close dengan LSTM. Harga Doge Close berkorelasi dengan sentimen, namun tidak kuat tidak juga lemah. Tidak ada peningkatan akurasi hasil prediksi dibandingkan pengujian pertama yang dimana pada pengujian pertama nilai RMSE sebesar 0,003 dan pengujian kedua nilai RMSE sebesar 0,008.Kata kunci— analisis sentimen, LSTM, prediksi, korelasi
Post-harvest seaweed quality support in Pagarbatu Village, Sumenep, using SWSolar Dryer technology to create competitive seaweed farmers Zuhri, Ach; Ahsan, Agung Firdausi; Saadah, Siti; Ghibran, Moh Iqbal; Aini, Anis Nur
IMPOWERMENT SOCIETY Vol 9 No 1 (2026): February 2026
Publisher : Institut Teknologi dan Bisnis Widya Gama Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30741/eps.v9i1.1735

Abstract

Seaweed is a leading commodity in Sumenep Regency. However, post-harvest quality remains low due to traditional drying methods, which, in turn, affects selling prices and farmer welfare. This community service program aims to improve the quality and competitiveness of seaweed farmers in Pagarbatu Village by applying SW-Solar Dryer technology. Implementation methods include outreach, management and production training, SW-Solar Dryer application, mentoring, and ongoing evaluation with "Kelana" fishing group partners. The results showed that the SW-Solar Dryer can reduce drying time from 2–3 days to just 5–8 hours. It maintains product hygiene because the process is carried out in a closed room. Moisture content produced also meets industry standards. Furthermore, the mentoring program encouraged diversification of processed seaweed-based products. This increased farmers' income and reduced dependence on collectors. Thus, the application of SW-Solar Dryer technology has proven effective in improving post-harvest management, expanding business opportunities, and creating more competitive seaweed farmers.
Interconnectedness of Financial Assets across the ASEAN-5 in Crisis Periods Sumani Sumani; Siti Saadah
ETIKONOMI Vol. 25 No. 1 (2026)
Publisher : Faculty of Economic and Business, Universitas Islam Negeri Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/etk.v25i1.46634

Abstract

Research Originality: This study advances the financial connectedness literature by integrating a multi-asset (Bitcoin–stocks–sovereign bonds) and time-varying framework within the ASEAN-5 context. Unlike prior studies, this study uncovers a hierarchical and asymmetric spillover structure that evolves across market regimes, providing new evidence on cross-asset transmission channels in emerging markets. Research Objectives: The study aims to investigate the magnitude, direction, and dynamics of volatility spillovers among Bitcoin, stock, and bond markets, and to assess whether these interconnections change between normal and crisis periods. Research Method: Using daily data from January 2018 to April 2026, volatility is estimated through a GARCH model. A generalized VAR-based forecast error variance decomposition (G-FEVD), combined with a rolling window approach, is employed to capture both directional and time-varying spillovers. Empirical Results: The findings show a hierarchical spillover pattern: sovereign bonds act as net transmitters to Bitcoin, while Bitcoin transmits risk to stock markets. Spillover intensity increases significantly during crisis periods, peaking during COVID-19, indicating strong state-dependent connectedness. Cross-asset diversification weakens under market stress. Implications: These findings imply that financial stability cannot be assessed in isolation, as shocks propagate across asset classes in a structured, time-varying manner. This study underscores the importance of integrated cross-market surveillance frameworks that include digital assets alongside traditional markets. JEL Classification: G15, N25, H5
Co-Authors ABADI Adytia, Diditq Agung Firdausi Ahsan Aini, Anis Nur Ambrosius Aprian Tri Putranto Andy Lasmana Anita Giovanni Azzahra, Rizqina Faisal Hadi, Risyad Farah Afianti Francisca Hermawan Ghibran, Moh Iqbal Gia Septiana Wulandari Hendri Hendri Ida Farida Ihsan, Rivan Nur Intan Surya Lesmana Irma Palupi Kurniawati, Elis Nia Kusumahadi Larasati Larasati Lestari, Risma Fuji Marsiana Luciana Sitanggang Novia Utami Nuning Trihadmini Nurani, Ratih Oktaviana, Yogi Permana, Fikri C Prasetyo Nugroho, Ecky Prasti Eko Yunanto Saputra, Dian Dieniawati Satrio, M Sri Hapsari Wijayanti Stanislaus Suryadi Uyanto Sumani Sumani Susanti Susanti Teresia Angelia Teresia Angelia Kusumahadi Tina Martina, Tina Triana Indrayani Utomo, Felicia Grace Ratnasari Veronika Daniar Febrianti Yohanes Berchman Suhartoko Yulianti, Yuli Yunia Panjaitan Zuhri, Ach