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All Journal Jurnal Teknik ITS JURNAL REKAYASA TEKNOLOGI INFORMASI Voice Of Informatics CSRID (Computer Science Research and Its Development Journal) Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Mantik Journal of Intelligent Decision Support System (IDSS) Nusantara Hasana Journal Teknik: Jurnal Ilmu Teknik dan Informatika Jurnal Abdi Masyarakat Indonesia Jurnal Mandiri IT Brilliance: Research of Artificial Intelligence Jurnal Minfo Polgan (JMP) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Informatika dan Teknologi Informasi JSITP Jurnal Indonesia Sosial Teknologi Journal of Artificial Intelligence and Digital Business Jurnal Publikasi Teknik Informatika (JUPTI) Jurnal Masyarakat Madani Indonesia Jurnal Ekonomi, Teknologi dan Bisnis Innovative: Journal Of Social Science Research SOROT: Jurnal Pengabdian Kepada Masyarakat SmartComp Jurnal Akademik Pengabdian Masyarakat Svarga Pena: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika dan Desain Komunikasi Visual
Sarif Surorejo
STMIK YMI Tegal
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Application of association rule for prediction of menu ordered at café minapadi Zain Hidayatullah, Fikri; Surorejo, Sarif; Andriani, Wresty; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 12 No. 4 (2024): April: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v12i4.279

Abstract

This research aims to develop a predictive model that helps prepare menus based on customer preferences at Café Minapadi, hoping to improve operational efficiency and customer satisfaction. Using rule-association data mining techniques, the study uncovered hidden patterns in extensive transaction data, applying a priori algorithms in datasets to explore menu ordering frequencies and trends. Data analysis includes cleansing, transforming, and selecting features to generate relevant insights. The results found that items such as coffee and chocolate cake were often purchased together, providing an opportunity for menu optimization and special promotions. Evaluation of predictive models shows the possibility of increased accuracy in stock preparation and adjustment of menu offerings, providing significant benefits in business decision-making in the culinary sector.
Prediction of Bank Central Asia stock prices after dividend distribution using ARIMA method Surorejo, Sarif; Sulthon, Muhammad; Anandianskha, Sawaviyya; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.294

Abstract

This study explores the prediction of Bank Central Asia (BBCA) stock prices following the annual dividend distribution using the Autoregressive Integrated Moving Average (ARIMA) method. The primary goal is to provide a robust forecasting tool to aid investors and financial analysts in making informed decisions. The research employs a quantitative approach with a quasi-experimental design, analyzing weekly BBCA stock price data from January 2019 to February 2024. The findings demonstrate that the ARIMA (2, 1, 2) model provides stable and reliable predictions of BBCA stock prices, showing slight weekly variations but overall stability. Practically, these predictive models can be integrated into a web-based platform, allowing real-time stock price forecasting and broader accessibility for users. This study contributes to the financial literature by validating the ARIMA model's applicability in the Indonesian stock market and suggesting the exploration of hybrid models and external economic factors for future research.
Application of weighted aggregated sum product assessment method in determining the best flour to produce vermicelli Surorejo, Sarif; Rivaldiansyah, Rafik; Dwi Kurniawan, Rifki; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.296

Abstract

This study explores the application of the Weighted Aggregated Sum Product Assessment (WASPAS) method's selection of the best wheat flour for vermicelli production, which aims to improve product quality and production efficiency. The study aimed to integrate experimental data with sophisticated decision-making models to identify the most suitable type of flour based on a comprehensive set of criteria. Using a quantitative approach, this study combines experimental methods, quantitative analysis, and model validation, using the WASPAS method to evaluate and rank various flours. The results showed significant differences among flour types, with selected flours showing superior performance across multiple parameters, including chemical composition and functional properties. The study's findings underscore the potential of advanced decision-making tools such as WASPAS in improving food production processes, demonstrating broader applicability across the food industry to optimise raw material selection.
Comparison of dijkstra and genetic algorithms for shortest path guci Surorejo, Sarif; Al Fattah, Muhammad Raikhan; Andriani, Wresti; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.298

Abstract

This study aims to compare the performance of the Dijkstra algorithm and the Genetics algorithm in determining the shortest path to the Guci tourist destination. The research design combines experimental methods, quantitative analysis, and model validation. The data used is the distance between points on two alternative routes to Guci. Data pre-processing is done to ensure quality and consistency. The relevant variables are selected, and model optimization is performed to obtain the best parameter configuration for both algorithms. Dijkstra and Genetics algorithms are implemented using Python, taking into account computational efficiency and ease of integration. Model evaluation is done through a series of tests with time execution and convergence metrics. The results showed that Dijkstra's algorithm was superior in finding the shortest path with a distance of 43.0 km and an execution time of 0.0017 seconds, compared to the Genetics algorithm which found a path with a distance of 44.7 km and an execution time of 0.0048 seconds. It can be concluded that Dijkstra's algorithm is more effective and efficient in this case, but Genetics algorithms have the potential for more complex optimization problems.
Application of fuzzy genetic system to predict the number of outpatient visits Surorejo, Sarif; Cahyo, Septian Dwi; Fadilah, Nurul; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.299

Abstract

Improving the management and use of resources in outpatient care is a challenge faced by health facilities in today's digital era. The inability to accurately predict patient flow can result in inadequacies in staff scheduling and effective space management. Therefore, this study aims to develop a predictive model of outpatient visits using the fuzzy system genetic method. The research methods used include the design of a combination of experimental methods, quantitative analysis, and model validation. Outpatient visit data is taken from a hospital and processed using the Fuzzy Genetics System which optimizes fuzzy rules with genetic algorithms. The results of the model implementation show accurate and adaptive predictions to variations and uncertainties in patient visiting patterns. Based on the results of the study, it can be concluded that the use of fuzzy system genetic methods in predicting outpatient visits can improve the operational efficiency of health facilities. The developed prediction model is able to provide predictions that are more accurate, adaptive, and responsive to the real needs of health facilities. With the adoption of this method, health facilities can optimize management and resources in outpatient health services. This research contributes significantly to the development of predictive models that are more efficient and applicable in the dynamic context of healthcare.
Implementation of the Fuzzy Tsukamoto method to determine the amount of beverage production Surorejo, Sarif; Firmansyah, Muchamad Aries; Arif, Zaenul; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.302

Abstract

Optimization of the amount of beverage production by applying the Fuzzy Tsukamoto Method at PT. Sariguna Primatirta Tbk. This study aims to develop a predictive model that can assist companies in determining the optimal amount of beverage production, minimizing production costs, and maximizing customer satisfaction. The research method uses a quantitative approach with a combination design of experimental methods, quantitative analysis, and model validation, including the collection of historical data on production, market demand, and raw material availability, data pre-processing, selection of input and output variables, implementation of the Fuzzy Tsukamoto algorithm, and model evaluation with Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) metrics. The results showed that the Fuzzy Tsukamoto Method succeeded in determining the amount of beverage production with good accuracy, with an MAE of 0.25 and RMSE of 0.274 after the data was understated, proved effective in handling the uncertainty of market demand and providing optimal production recommendations based on fuzzy rules from expert knowledge. The implications of this research contribute to the scientific literature in the field of computer science and industrial management, as well as practical benefits for  PT. Sariguna Primatirta Tbk in improving its production effectiveness, with the potential to be adopted by similar industries to improve operational efficiency.
Expert system for diagnosing pests and diseases of shallot plants with naïve bayes method Surorejo, Sarif; Albana, Muhammad Syifa; Santoso, Nugroho Adhi; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.304

Abstract

The development of an expert system for diagnosing pests and diseases of onion plants is of great importance given the significant role of these crops in the agricultural industry. This research aims to design and develop an expert system that can diagnose various pests and diseases that attack onion plants using the Naive Bayes method. This method was chosen for its ability to classify data based on probability assuming independence between features. This system is designed to assist farmers in identifying pests and diseases more accurately and quickly so that appropriate control measures can be taken immediately.  The training data used in this study included symptoms that often occur in onion plants due to pest or disease attacks. Each symptom is associated with the probability of the appearance of a particular pest or disease. This expert system is designed with an easy-to-use interface for farmers, where they can enter the symptoms observed in plants. Based on these inputs, the system will analyze and provide a diagnosis along with recommendations for control actions that can be taken. The system testing results show that this expert system has good accuracy in diagnosing pests and diseases in onion plants. Thus, this system can be an effective tool for farmers in managing the health of their onion plants. Further research is recommended to improve disease and pest databases and expand the application of these systems to other plant types.
Application of the latent dirichlet allocation method to determine news text topics Surorejo, Sarif; Maulana, M Taufik Fajar; Andriani, Wresti; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.306

Abstract

This research discusses the application of the Latent Dirichlet Allocation (LDA) method to determine news text topics, providing new insights into media content analysis. This research aims to develop a model that can increase the accuracy and efficiency of topic identification in Indonesian news texts. The research uses a quantitative approach with experimental methods, quantitative analysis, and model validation, where news text data is processed and analyzed using LDA. The results show that the developed model can accurately identify news topics, showing significant improvements compared to existing methods. The implications are substantial for practitioners and researchers in journalism and media analysis, offering more efficient and effective strategies for managing and understanding large flows of information and opening new directions for advanced research in news text analysis.
Penerapan Metode SAW dalam Sistem Pendukung Keputusan pada Pemberian Bantuan Pedagang Pasar umar, moh azizul umar; Sarif Surorejo; Pingky Septiana Ananda
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 2 No. 2 (2022): Oktober : Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v2i3.159

Abstract

Program bantuan adalah salah satu jalan yang diberikan pemerintah untuk penanggulangan masalah kemerosotan ekonomi pada pedagang yang disebabkan karena virus covid-19 yang menjalar di Indonesia menyebabkan jarang ada pelanggan untuk membeli sesuatu bahan atau produk ke pasar, bermaksud agar bisa memenuhi kebutuhan pedagang yang mempunyai ekonomi yang lemah dan meningkatkan kehidupan pedagang dengan menerima program bantuan. Proses untuk menentukan penerima program bantuan di pasar masih menggunakan cara yang masih manual dengan menulis formulir dalam wujud kertas yang sudah dibagikan, perhitungan matematis skor pun masih dilakukan secara manual dan dipindah ke format excel dari hasil seleksi yang sudah didata, hal ini hanya membuat lebih banyak peluang terjadinya error dan memperlambat performa para petugas pasar. Sering kali terjadi miskomunikasi penyaluran bantuan yang menjadi rumit, atau berkurangnya jumlah nominal, sehingga terjadi kesalah pahaman antar masyarakat. Metode Simple Additive Weighting (SAW) membutuhkan proses normalisasi matriks keputusan. Untuk penyelesaian masalah ini, penulis menggunakan metode Simple Additive Weighting (SAW) untuk mendapatkan penilaian kriteria majemuk dan lengkap. Kata Kunci: SPK, COVID 19, Bantuan, Metode SAW.
Implementasi Server Dengan Sistem Operasi Linux Debian Sebagai Pendukung Penerimaan Peserta Didik Baru Dengan Virtualbox Di SMK Bina Islam Mandiri Kersana Kabupaten Brebes Nugroho, Bangkit Indarmawan; Surorejo, Sarif; Santoso, Bayu Aji; Murtopo, Aang Alim; Syefudin, Syefudin; Arif, Zaenul; Kurniawan, Rifki Dwi; Karsidin, Karsidin; Adhi Santoso, Nugroho
Jurnal Teknik Informatika dan Desain Komunikasi Visual Vol 4 No 1 (2025): Jurnal Teknik Informatika dan Desain Komunikasi Visual
Publisher : Fakultas Komputer Dan Desain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51792/yn6j9k73

Abstract

Every job that is done using computer network technology, the data that we input has actually entered the server computer. Thus the data that we have entered will be automatically saved to the server computer. The real conditions in the field are that there are several things that may cause the PPDB process at SMK Bina Islam Mandiri Kersana, Brebes Regency to be less effective. The main causes are Human Resources, Hardware, PPDB Process and Software. The design of the computer network that will be used as the object of this study, one of the topologies used is the star topology. The materials for designing the implementation of this server are the server computer, client computer, switch and PPDB application. To be able to connect to a network, here it is necessary to have a server IP address which will later be used to connect to other computers in this case the client computer. Previously, install Linux Debian using the VirtualBox application for the server, then configure the network until finished, connect the server computer to the client computer using the media, namely the UTP cable, after that on the client computer set the IP and open the browser to see the results. So it can be concluded that the server system for accepting new students can be done easily, as long as there is a will and perseverance in making it.
Co-Authors ., Yustira Aang Alim Murtopo Adhi Santoso, Nugroho Al Fattah, Muhammad Raikhan Albana, Muhammad Syifa Ali Djamhuri Alzam Habibie Ananda, Pingky Septiana Anandianskha, Sawaviyya Andriani, Wresti Andriani, Wresty Arif , Zaenul Arif, Zaenul Aslam, Muhammad Nur Bangkit Indarmawan Nugroho Bayu Aji Santoso Cahyati , Divia Faiqotul Cahyo, Septian Dwi Defi Lugianti Dwi Kurniawan, Rifki Erni Unggul Sedya Utami, Erni Unggul Sedya Fadlilah, Chairil Aditya Nur Firmansyah, Muchamad Aries Gunawan Gunawan Gunawan Gunawan Gunawan Hastin Setyorini Isnaeni Hamidah Juniyanto, Rudi Karsidin, Karsidin Khofifah Indah Hasanah Khofifah Indah Hasanah Kurniawan, Rifki Dwi Maulana, M Taufik Fajar Milkhatunisya Milkhatunisya Milkhatunisya, Milkhatunisya Moh. Jamaludin Mohamad Rifki Septiadi Muhamad Lutfi Muhammad Alfan Maulana Muhammad Sulthon Muhammad Syahrul Maulana Muhammad Syahrul Maulana Mutaqin, Ahadan Fauzan Ningrum, Isna Lidia Nugroho Adhi Santoso Nugroho Adhi Santoso Nur Kholifatul Aula Nurokhman, Akhmad Nurul Fadilah, Nurul Pingky Septiana Ananda Pinky Septiana Prayoga, Alan Eka Putra, Alif Sya’Bani Rifki Dwi Kurniawan Rifki Dwi Kurniawan Rito Cipta sigitta Hariyono Rivaldiansyah, Rafik Romadhona, Wahyu Rudi Juniyanto Sagita, Rito Cipta Santoso, Aisyach Aminarti Santoso, Bayu Aji Santoso, Nugroho Adh Santoso, Nugroho Adhi Setiawati, Windi Subechi, Fadlan Hafid Syefudin Syefudin Syefudin Syefudin, Syefudin Ubaidillah, Muhamad Rizal umar, moh azizul umar Uswatun Khasanah Wresti Andriani Yustira . Zaenal Arif Zaenul Arif Zain Hidayatullah, Fikri