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All Journal CCIT (Creative Communication and Innovative Technology) Journal JSAI (Journal Scientific and Applied Informatics) IJIIS: International Journal of Informatics and Information Systems Jurnal Teknologi dan Sistem Tertanam International Journal of Engineering, Science and Information Technology JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Sistim Informasi dan Teknologi Information Technology Education Journal West Science Social and Humanities Studies Jurnal Teknologi Informasi
Rasna
Universitas Yapis Papua
Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation

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Representation over Kernel: A Cross-Category Analysis of Semantic Review Embedding versus Rating-Overlap Collaborative Filtering for User Cold-Start Moh Rahmat Irjii Matdoan; Triyanna Widiyaningtyas; Firmansyah Ibrahim; Rasna
Information Technology Education Journal Vol. 5, No. 3, August (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i3.13484

Abstract

Purpose – The user cold-start problem cripples recommenders when a new user has almost no interaction history. This study asks two questions prior work conflates: does semantic review embedding similarity outperform conventional rating-overlap collaborative filtering (CF) in cold-start, and does a magnitude-sensitive kernel over the embedding add anything beyond ordinary cosine similarity? Design/methods/approach – Under one identical protocol on two Amazon review domains of differing sparsity, RBF-SBERT (an RBF kernel over SBERT embeddings) is compared with cosine, Pearson, an XGBoost baseline, rating-overlap CF, and two popularity baselines. Cold-start users (one to three interactions) use a per-user sampled protocol; significance uses Wilcoxon and Cohen's d. Findings – In the sparse domain the embedding beats even the strongest simple baseline, item-count popularity, on precision (P@5 0.567 vs 0.252; d=0.65) and ranking (AUC 0.869 vs 0.821); in the denser domain that edge vanishes as popularity matches AUC and exceeds precision, so the advantage is governed by sparsity. Rating-overlap CF is weakest, collapsing to its mean-rating fallback. The RBF kernel is inert (≈ cosine, d=0.007–0.107) because the pooled magnitude it uses is nearly constant (CV 0.07–0.09) and tracks review length, not preference. Research implications/limitations – Cold-start gains arise from the representation, not the kernel; methods must be benchmarked against popularity under sparsity-aware protocols. Evaluation covers two Amazon categories under one sampled protocol. Originality/value – The study separates representation from kernel and precision from ranking quality, giving a reproducible account of when review-based embedding helps cold-start and why.
Implementation of Dijkstra and Ant Colony Algorithms for Web-based Shortest Route Search for LPG Gas Distribution Rasna Rasna; Moh. Rahmat Irjii Matdoan; Nurlaela Kumala Dewi; Afferdhy Ariffien; Seno Lamsir
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.805

Abstract

National energy needs and efforts to fulfill them are currently vital issues to be discussed and resolved. One type of energy that still has various problems is fuel gas, especially LPG (Liquid Petroleum Gas). The gas scarcity in each region differs; not all regions experience gas shortages, and some areas have excess LPG gas stocks. The problem of the scarcity of 3 kilogram (Kg) LPG gas is not the first time this has happened. In recent months, people in some regions have complained about the scarcity of subsidized 3-kilogram (kg) LPG gas. This situation certainly makes it difficult for the community. Not only does the scarcity hamper community activities, but it also makes the price of gas refills more expensive than usual. With the increasing demand for LPG gas every year, the government must provide large stocks of LPG gas. But what power if the LPG gas stock is less or runs out at specific locations. Therefore, applying gas base route search is needed to overcome the shortage of gas stock at a location. This application applies two search methods, namely the Dijkstra algorithm and the ant colony algorithm, to find the fastest route to the location of the gas base in the XYZ area. In the algorithm process, Dijkstra requires distance data for each city before starting the algorithm process. The Ant Colony Algorithm does not require the distance of each city because, in an Ant Colony, the distance between towns is calculated after the ants complete their journey. From the results of the process of the two algorithms, it is known that the path produced by Dijkstra's algorithm is more consistent and precise than the Ant Colony algorithm, which gives results that are not necessarily the same for each process.
Application of Hashing Method in Medical Term Dictionary Application Moh. Rahmat Irjii Matdoan; Rasna Rasna; Sahlan M Saleh; Andrian Sah; Seno Lamsir
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.662

Abstract

The number of words or terms that appear and are used in human life makes it difficult for a person to master all of these words. To overcome this, these words or/terms are compiled in a dictionary, one of which is a dictionary of medical terms. This research aims to create software that can perform its function as a medical terminology dictionary program and implement the Hash method into software that can be used for data search. This research applies the hash method to find the hash value using a rolling hash. The hash method uses input text to be transformed into numbers, thus speeding up the computational process. The application of the hash method in the addressing/storage process in the Database is very efficient in terms of time and place. The output appears in the form of word meaning and hash value. The hash value is raised to know the value of the searched term using the rolling hash formula. With this research, it is hoped that searching for the meaning of medical terms in a computerized manner can be consistent with manual searches.
Electre Method Decision Support System for Concrete Type Selection in Building Structures Elyandri Prasiwiningrum; Rasna Rasna; Putu Doddy Heka Ardana; Fifto Nugroho; Qurrotul Aini
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.843

Abstract

Choosing the correct type of concrete in building construction is a crucial step that significantly affects the structure's quality, durability, and safety. Concrete, as the most widely used building material, has various types with different characteristics, such as compressive strength, tensile strength, modulus of elasticity, and durability. During this time, people who make concrete often ignore the strength of the concrete itself. They do not care what will happen if the manufacture of concrete is not by the recommended concrete construction. Concrete is the primary material for constructing a building such as a building. The quality of concrete is determined by its constituent materials, which include hydraulic cement, coarse aggregate, fine aggregate, water, and other additives. The concrete mix determines the strength of the concrete. If the building is built with unsuitable concrete, it will be quickly destroyed during natural disasters such as earthquakes. Based on this, the concrete type selection must be precise and accurate. Decision Support Systems are used in this research to provide additional input to decision-makers. Decision support systems can deliver maximum results by using algorithms or methods. The Electre method is one of the multicriteria decision-making methods based on ranking by pairwise comparisons of existing alternatives based on appropriate criteria. Overall, this research is expected to significantly improve the quality of decision-making in selecting concrete types, resulting in a safer, more durable, and more efficient building structure. The results obtained after inputting criteria values and alternative values are concrete types such as reinforced concrete, precast concrete, and lightweight concrete.
Forecasting the Inventory of Milled Dry Grain Using the Lot Sizing Method at Markom Rice Mill Afferdhy Ariffien; Seno Lamsir; Rasna Rasna; Qurrotul Aini; Moh. Rahmat Irjii Matdoan
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.817

Abstract

Today's industrial activities are increasing with sophisticated technology, all applied to satisfy consumers in various services. One of the important parts of an industry is the inventory of goods. This is related to the continuity of the resulting production. In meeting the needs of consumers, a plan is needed in production so that there is no shortage of raw materials and the production process does not stop. Grain is an agricultural commodity whose demand and production levels occasionally increase. We can see that until now, our country, Indonesia, still imports rice from other countries, where rice is the main production product produced from grain. The problem can be solved with the Lot sizing method used in this study, which is used to determine the size of the order quantity. In the rice mill itself, grain storage has a limited capacity, so it cannot be directly stored with a large capacity when the price of grain is down. Applying this method as an application will make it easier to manage grain inventory at the rice mill and estimate inventory costs for the next 1 () year. The results of the lot sizing calculation (silver meal) show that for the next year, the smallest cost of procurement of dry milled grain (MDG) demand is obtained from the procurement of demand every month. In other words, procurement is more appropriate every month or period so that the costs incurred for grain inventory are smaller. The following data are the results of the silver meal lot sizing calculation: (1) 39015.4 kg, (2) 35871.2 kg, (3) 39536 kg, (4) 33894.8 kg, (5) 31402 kg, (6) 27982.5 kg, (7) 41461.9 kg, (8) 35336.7 kg, (9) 41305.6 kg, (10) 45717.5 kg, (11) 42007.9 kg, (12) 50828 kg. The cost incurred per order is Rp. 6,000,000
Pattern Recognition of Chinese Characters Using the Sokal Sneath Four Method Rasna Rasna; Andrian Sah; M. Ali Nur Hidayat; Jusmawati Jusmawati; Mursalim Tonggiroh
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.668

Abstract

Pattern recognition is a discipline that aims to classify or describe objects based on their characteristics, quantitative measurements, or critical properties. Where a pattern is defined as an entity that is initially undefined, it can be identified and named through quantitative analysis. Pattern recognition can be applied to various fields, such as handwriting recognition, face recognition, eye recognition, skin, and image processing. One example of the application of pattern recognition is character recognition in letters used in learning. In this research, the digital image used as input comes from a two-dimensional image obtained through a digital camera. The digital image describes the light intensity in light and dark areas in the form of pixels and provides information about the object's color. To support the process of recognizing alphabet letters, which in this case are specifically Chinese alphabet letters, it will be assisted by using the Sokal Sneath Four Method. This significant mathematical approach helps create a compatible and accurate system for recognizing letter patterns through intensive data training. This method involves a series of steps, including data preprocessing, feature extraction, and classification, to train the system to recognize Chinese characters. The more training given to the system, the higher its accuracy in recognizing letter patterns, especially Chinese alphabet letters. The test results show that this Chinese alphabet letter pattern recognition system has a success rate of 65%, with a failure rate of 35%. Nevertheless, these results show room for further improvement in the algorithms used and the addition of training data to improve system performance and accuracy.
Weather Classification and Prediction on Imagery Using Boltzmann Machine Rasna Rasna; Moh. Rahmat Irjii Matdoan; Junaidi Salat; Fitria J; Seno Lamsir
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.806

Abstract

Weather is a physical process or event that occurs in the atmosphere at a specific time and place, as well as its changes over a short period in a particular location on Earth. To produce weather forecast information, there is a series of processes that must be carried out until the weather information is conveyed accurately. The stages involved in the feature extraction process are carried out first. This process is carried out to obtain specific characteristics or features from a dataset. After the feature extraction process has been completed, the next step is to predict the weather based on the input images. To classify the weather on Earth using various algorithms, one of which is the Machine Boltzmann. The pattern recognition method used is Machine Boltzmann as an application of a simpler and more complex method. Generally, the weather prediction system using Machine Boltzmann consists of several stages, namely image acquisition, greyscale processing, segmentation/location using Sobel edge detection, classification using the Machine Boltzmann method, and finally producing output in the form of weather class results. The classification process in this research involves images of clear, cloudy, and rainy weather as inputs. The output of the system is the determination of whether the input weather image falls into the category of clear, cloudy, or rainy weather. The results of the study show that the classification of weather based on captured images has the highest accuracy for clear weather, with a percentage of 73.33%. For cloudy weather, the success rate is equal to the error rate, which is 50%, while rainy weather was not recognized at all.
Application Introduction and Learning Geometry of Space to Student Elementary School Using Method Rolling Hash Based on Android Heri Fajri; Lucy Lidiawati Santioso; Rasna Rasna; Muhammad Awal Nur; Rajib Ghaniy
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.772

Abstract

Along with technological advancements, smartphones have evolved from being just a means of communication to now being multifunctional devices that reflect the status of their users and offer various features, such as cameras, music and video players, video calls, voice recorders, games, and internet access. These innovations' progress made them widely used by humans in their activities. One of the innovations that utilizes this technology is a building space introduction and learning application explicitly designed for elementary school students, using the Android-based Rolling Hash method. This application is an interactive educational tool that provides comprehensive information about building spaces, explains the various forms of building spaces, provides applicable examples, and offers solutions to related problems. This application's primary focus is implementing the Rolling Hash algorithm for string matching, which was chosen for its ability to perform fast and accurate matching in answering questions. By implementing this algorithm, the application can efficiently handle various questions involving strings, enhancing students' learning experience. This application uses Java programming language with ADT IDE for Eclipse and SQLite as a database system to store and manage data. The result of this final project is a learning application that not only facilitates the introduction of building space concepts to elementary school students but also shows how modern technology can improve learning methods. The Rolling Hash algorithm proved its effectiveness in fast and precise string matching, providing an optimal solution for this educational application and presenting a model of how technological tools can support primary education innovatively and practically.
Web-based Rabies Disease Diagnosis Expert System with Forward Chaining and Dempster Shafer Methods Junaidi Salat; Rasna Rasna; Muhammad Ichsan; Dahlan Abdullah; Seno Lamsir
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.801

Abstract

Rabies is a hazardous zoonotic disease that poses a significant threat to both animals and humans, as it can result in death. The disease is caused by a single-stranded RNA virus commonly found in infected animals' saliva, which can be transmitted to humans through bites. Although many people keep animals as pets, many lack adequate knowledge about the potential risks of rabies transmission. In Indonesia, most cases of rabies transmission to humans are caused by bites from infected dogs, followed by bites from monkeys and cats. The absence of an effective treatment for Rabies makes prevention and early diagnosis extremely important. One approach that could help manage the disease is creating an expert system for rabies diagnosis. The Rabies Disease Expert System is developed based on a needs analysis conducted through interviews with veterinarians to understand the classification of symptoms and the diagnostic process for Rabies. It's important to note that while the system is a valuable tool, it does have limitations and should not replace the role of a veterinarian. The system employs two critical methodologies: the Forward Chaining and Dempster-Shafer algorithms. These algorithms allow the system to trace the progression of symptoms and calculate the probability of a rabies infection. The system is an interactive platform where users—such as animal owners or medical professionals—can input observed symptoms in either animals or humans. Based on these inputs, the system provides a probable diagnosis. For example, the expert system might determine that a dog is in the 'Excitation Stage' of Rabies with a 54% confidence level. The integration of Forward Chaining and Dempster-Shafer methods ensures that the system continuously refines its diagnostic accuracy, aiming for a confidence level close to 100%. This expert system offers a promising tool to aid in the early detection and management of Rabies, potentially reducing the risk of widespread transmission.
Co-Authors Ade Surahman Afferdhy Ariffien Afferdhy Ariffien Alam, Sitti Nur Andrian Sah Bobi Aditama Dahlan Abdullah Elkana Timotius Elyandri Prasiwiningrum Fajrin Noviansyah Fifto Nugroho Fitria J Gustaf Griapon Heri Fajri, Heri Husain Ali Ibrahim, Firmansyah Irjii Matdoan Junaidi Salat Jusmawati Jusmawati Jusmawati Loso Judijanto Lucy Lidiawati Santioso M Safii M. Ali Nur Hidayat Moh Rahmat Irjii Matdoan Moh. Rahmat Irjii Matdoan Moh. Rahmat Irjii Matdoan Moh. Rahmat Irjii Matdoan Mohammad Rahmat Irjii Matdoan Muhammad Bakri Muhammad Ichsan Muhammad Ridwan Rumasukun Mursalim Tonggiroh Nur, Muhammad Awal Nurlaela Kumala Dewi Putu Doddy Heka Ardana Qurrotul Aini Qurrotul Aini Rajib Ghaniy Robo, Salahudin Rostini Anwar Sahlan M Saleh Seno Lamsir Sheila putri aprilianti Siti Marwa Siti Nurhayati Sitti Alam Triyanna Widiyaningtyas