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All Journal SMATIKA JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Teknologi Komputer dan Sistem Informasi JSAI (Journal Scientific and Applied Informatics) ILKOMNIKA: Journal of Computer Science and Applied Informatics G-Tech : Jurnal Teknologi Terapan JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Ilmiah Intech : Information Technology Journal of UMUS Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Journal Automation Computer Information System (JACIS) JAMU : Jurnal Abdi Masyarakat UMUS Fahma : Jurnal Informatika Komputer, Bisnis dan Manajemen AR-RUMMAN: Journal of Education and Learning Evaluation Smatika Jurnal : STIKI Informatika Jurnal
Tito Prabowo
Ilmu Komputer, Universitas Nahdlatul Ulama Blitar, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Other

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Perancangan Sistem Informasi Inventaris pada PT. Rejoso Manis Indo Menggunakan Metode Rapid Application Development Panky Yoga Pratama; Abd. Charis Fauzan; Tito Prabowo
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 14 No 01 (2024): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v14i01.1209

Abstract

Technology that cannot be stopped and is increasingly developing requires companies like PT. Rejoso Manis Indo to adopt a more sophisticated and efficient system. This company's still manual inventory management process faces various problems, such as recording errors, lost or damaged data, and low efficiency. Difficulty tracking the status of goods also results in inaccurate data. This research aims to design an inventory information system using the Rapid Application Development (RAD) method which involves users at every stage of development. Data was collected through Likert scale questionnaires, interviews, and literature studies. This system was implemented using PHP CodeIgniter, and MySQL, and checked using the System Usability Scale (SUS) and black box testing. The research results show that the developed inventory information system increases effectiveness and efficiency, with a user satisfaction level of 77 with a value of B (Good). In conclusion, this system is effective in overcoming inventory problems at PT. Rejoso Manis Indo, although further research is needed to involve more users from various departments and examine the security and scalability aspects of the system.
Penerapan Metode Weighted Product Berbasis Visualisasi Graph Database dalam Merekomendasikan Parfum Isi Ulang Defy Lukbatul Qolbiah; Abd. Charis Fauzan; Tito Prabowo
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 4 (2023): Juni 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i4.6181

Abstract

Perfume is useful for increasing self-confidence, creating satisfaction, eliminating bad odors, and making self-assessment more attractive. Refill perfumes are made from certain perfume seeds dissolved in a suitable solvent. Perfume has many types and strengths of aroma, but there are obstacles when people want to choose the desired perfume scent. This problem becomes research material because it is expected that this problem can be solved. To determine perfume recommendations, it is calculated using the Weighted Product method and visualized using a graph database. In the Neo4j Graph Database visualization, the perfume category and perfume name are used as nodes and the ranking results are used as edges. From the ranking results using the Weighted Product method, 21 perfumes for each category are entered into the Graph Database visualization and a total of 63 perfumes will appear in the perfume recommendation system.Refill perfume is a perfume made from certain perfume seeds dissolved in the appropriate solvent.
Analisis Deret Waktu untuk Forecasting Populasi Ternak di Indonesia dengan Model LSTM Tito Prabowo; Lestariningsih; Abd. Charis Fauzan; Veradella Yuelisa Mafula
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7566

Abstract

Livestock population in Indonesia is one of the key indicators supporting national food security, particularly in meeting the demand for animal-based protein. However, the suboptimal utilization of livestock population data for strategic planning remains a challenge in the livestock sector. This study aims to predict livestock population in Indonesia using the Long Short-Term Memory (LSTM) method, a variant of Recurrent Neural Network (RNN) designed for time series data analysis. The livestock population data used in this research was obtained from the Central Statistics Agency (BPS) for the period of 2006 to 2022. The LSTM model was trained using 80% of the data for training and 20% for testing, with evaluation conducted using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results indicate that the LSTM model can forecast the national livestock population up to 2033 with good accuracy, particularly for livestock such as goats (MAPE 5.47%) and beef cattle (MAPE 5.64%). However, a higher error rate was observed for buffalo (MAPE 16.57%). The predictions indicate a significant growth trend in poultry populations, such as broiler chickens and laying hens. In conclusion, this model can support data-driven decision-making to ensure stable and sustainable animal protein availability, thereby strengthening national food security.
Comparison of JSON and MessagePack Serialization Performance on End-to-end latency over HTTP Protocol Muhammad Ilham Dzurinadib; Muhamat Maariful Huda; Tito Prabowo
G-Tech: Jurnal Teknologi Terapan Vol 10 No 3 (2026): G-Tech, Vol. 10 No. 3 July 2026
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v10i3.10072

Abstract

The increasing use of HTTP-based communication in modern service-oriented systems requires efficient data serialization formats to reduce communication latency and transmission overhead. This study compares the performance of JSON and MessagePack serialization formats in HTTP communication using the Go programming language. Performance was evaluated using synthetic datasets containing 10, 100, 1000, and 5000 records. The measured parameters included payload size, encoding latency, decoding latency, and End-to-end latency. The results show that MessagePack consistently outperformed JSON across all evaluated metrics. For the largest dataset containing 5000 records, MessagePack reduced End-to-end latency from 13.269 ms to 3.894 ms and generated a smaller payload size (335.87 KB) than JSON (350.53 KB). The performance advantage became more pronounced as the dataset size increased, particularly in decoding and End-to-end latency processes. These findings indicate that MessagePack is an efficient alternative to JSON for HTTP-based communication systems requiring low latency, bandwidth efficiency, and high-performance data exchange.
Pemanfaatan Generatif AI untuk Promosi Visual Usaha Kuliner Rumahan "Oma Rusmini" Harliana Harliana; Yuniar Alam; RDR Yusron; Tito Prabowo
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 5 No. 4 (2025): Juli 2025 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/3wtbcj65

Abstract

Penelitian ini bertujuan memberikan pelatihan kepada pelaku usaha “Oma Rusmini” dalam memanfaatkan teknologi Generatif AI untuk merancang konten promosi, deskripsi produk, serta skrip video agar lebih menarik dan disesuaikan dengan karakteristik target pasar dan membantu mengevaluasi dampak akan penggunaan Generatif AI terhadap peningkatan efektivitas pemasaran produk pada media sosial dan platform online yang dimiliki pelaku usaha “Oma Rusmini”. Upaya yang dilakukan peneliti memiliki dampak peningkatan signifikan dalam prosentase kata unik, dengan rata-rata mencapai 60% pada setiap caption. Hal ini menunjukkan kosakata yang digunakan lebih bervariatif sehingga skor pembuka memperoleh nilai 3 karena langsung menarik perhatian dengan kata khas yaitu “oma” dan “pedasnya nendang”.
Penerapan Metode Time Series Model ARIMA dalam Peramalan Jumlah Pengunjung Perpustakaan di Lembaga Pendidikan Dasar M. Ulin Nuha; Muhmat Maariful Huda; Tito Prabowo
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7843

Abstract

This research is conducted to predict the number of visitors to libraries within primary education institutions by employing the Autoregressive Integrated Moving Average (ARIMA) modeling technique. The dataset comprises daily visitor records spanning from January 2023 to December 2024. The forecasting process adopts a time series framework, which includes steps such as data preprocessing, stationarity verification through the Augmented Dickey-Fuller (ADF) test, identification of parameters using Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) plots, and the selection of the optimal model based on statistical significance and performance metrics, particularly the Mean Squared Error (MSE). Out of 35 evaluated ARIMA configurations, the ARIMA(2,0,11) model demonstrated the best performance, achieving the lowest MSE score of 789.08 and exhibiting statistically meaningful parameters. Moreover, the model passed the Ljung-Box diagnostic test, confirming that the residuals behave as white noise.The forecasting results for January 2025 show a stable and realistic trend. Compared to baseline methods such as Naïve Forecast, the ARIMA model demonstrates superior performance by effectively capturing data fluctuations. Therefore, ARIMA(2,0,11) is considered effective and accurate in supporting data-driven library service planning for the future.
Perancangan Sistem Informasi Sanggar Seni Kirana Budaya Berbasis Website Menggunakan Metode Agile Development Ayu Pramesti Maharani; Tito Prabowo; Fatra Nonggala Putra
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7874

Abstract

The Kirana Budaya Art Studio is an institution engaged in the preservation of arts and culture through various activities such as dance training and costume rental. However, the manual administration management causes various challenges, such as time efficiency, data accuracy, and limitations in conveying information to the wider community. To overcome these problems, a website-based information system was developed that was designed to support the studio's operational needs. This system was built using the Agile Development method, which allows the development process to be carried out iteratively by involving input from end users on an ongoing basis. This approach ensures that the resulting system can adapt to the dynamic needs of the studio. The main features developed include class registration, schedule management and activity classes, and costume rental. The purpose of this research is to produce a website-based information system using the Agile Development method that can disseminate information as well as become a medium for renting art products and services to the wider community in an easily accessible manner. The results of the implementation of this system show increased efficiency in data management, more effective delivery of information to users or customers, and optimization of promotions through digital media. With this website-based information system, the Kirana Budaya Art Studio can improve the quality of services and support efforts to preserve arts and culture in a more professional and modern manner.
Perbandingan Logistic Regression dan Random Forest untuk Prediksi Respon Pelanggan Asuransi Harliana Harliana; Tito Prabowo; Ady Alzhava Nuary
Jurnal Informatika Komputer, Bisnis dan Manajemen Vol 24 No 2 (2026): Mei 2026
Publisher : LPPM STMIK El Rahma Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61805/fahma.v24i2.214

Abstract

Vehicle insurance companies increasingly rely on data-driven marketing strategies to identify prospective customers who are likely to respond positively to insurance offers. However, customer response prediction is challenging due to class imbalance, where non-responsive customers substantially outnumber responsive ones. This study aims to compare the performance of Logistic Regression and Random Forest models in predicting customer responses to vehicle insurance products using the Synthetic Minority Oversampling Technique (SMOTE). The analysis was conducted using the Vehicle Insurance dataset obtained from Kaggle. Experimental results indicate that Random Forest achieved the best overall performance, with an accuracy of 0.80, a positive-class F1-score of 0.59, and a ROC–AUC score of 0.88. In contrast, Logistic Regression produced a higher positive-class recall of 0.98 but a lower precision of 0.35, indicating a greater tendency to generate false-positive predictions. Feature importance analysis revealed that Previously_Insured, Vehicle_Damage, and Age were the most influential factors affecting customer responses. These findings suggest that the combination of Random Forest and SMOTE provides an effective approach for handling imbalanced data and improving customer response prediction in vehicle insurance marketing campaigns.
PREDIKSI HARGA BITCOIN MENGGUNAKAN ALGORITMA LONG SHORT-TERM MEMORY M.Sirojul Munir; Muhamat Maariful Huda; Tito Prabowo
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.7937

Abstract

Cryptocurrency, atau mata uang kripto, merupakan bentuk aset digital yang memanfaatkan teknologi kriptografi untuk mengamankan transaksi, mengontrol penciptaan unit-unit baru, serta memverifikasi transfer aset yang ada. Mata uang kripto yang pertama kali diperkenalkan adalah Bitcoin. Salah satu keunikan dari cryptocurrency, termasuk Bitcoin, adalah sifatnya yang terdesentralisasi, artinya tidak diatur oleh lembaga pusat seperti bank atau pemerintah, melainkan menggunakan teknologi blockchain. Perubahan harga Bitcoin dapat terjadi secara cepat dan drastis dalam waktu singkat, sehingga sulit diprediksi secara akurat. Untuk menangani permasalahan prediksi harga pada aset yang sangat volatil seperti Bitcoin, digunakan berbagai pendekatan algoritma pemodelan data, salah satunya adalah algoritma Long Short-Term Memory (LSTM). Berdasarkan hasil penelitian dapat disimpulkan bahwa time step harian (1 hari) menghasilkan nilai RMSE terkecil, yaitu 1823.24 atau 2.86% dari rata-rata nilai aktual.
Co-Authors Abd. Charis Fauzan Abd. Charis Fauzan Abd. Charis Fauzan Ady Alzhava Nuary Amalia Wahyu Eka Putri Ayu Pramesti Maharani Defy Lukbatul Qolbiah Dewi Anggraini Donatus Ray Dyta Bagus Nawawi Fatra Nonggala Putra Harliana Harliana Harliana Harliana Iqbal Baihaki Kasanah, Siti Uswatun Lestariningsih Lestariningsih M. Ulin Nuha M.Sirojul Munir Muhamat Maariful Huda Muhamat Maariful Huda Muhammad Ilham Dzurinadib Muhammad Riski Balian Muhammat Maariful Huda Muhmat Maariful Huda Panky Yoga Pratama Puji Laksono R.M.Herdian Bhakti RDR Yusron Setyawan, Dimas Ari Siti Karomah Siti Nuralia Subana Subana Syehka Sofia Arya Larasati Veradella Yuelisa Mafula Vion Age Tri Cahyo Vion Age Tricahyo Yuniar Alam