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Bulletin of Information Technology (BIT)
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27220524     DOI : 10.47065/bit.v2i3.106
Core Subject : Science,
Computer Science & IT
Jurnal Bulletin of Information Technology (BIT) memuat tentang artikel hasil penelitian dan kajian konseptual bidang teknik informatika, ilmu komputer dan sistem informasi. Topik utama yang diterbitkan mencakup:berisi kajian ilmiah informatika tentang : Sistem Pendukung Keputusan Sistem Pakar Sistem Informasi, Kriptografi Pemodelan dan Simulasi Jaringan Komputer Komputasi Pengolahan Citra Dan lain-lain (topik lainnya yang berhubungan dengan teknologi informasi)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 436 Documents
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Explainable Gradient Boosting for Egg Production Anomaly Detection in Laying Hen Farms Intra Swadaya Hidayat; Febria Sri Handayani; Yarza Aprizal; Rendy Almaheri Adhi Pratama; Muhammad Jhonsen Syaftriandi
Bulletin of Information Technology (BIT) Vol 7 No 3: September 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i3.3071

Abstract

Abstract- Small-scale laying-hen farms require analytical tools that can detect abnormal egg-production patterns while remaining interpretable for operational decision support. This study develops and evaluates an explainable gradient boosting framework for low-production anomaly detection using farm-level environmental, management, and production records. The dataset contained 481 observations with eight variables, including flock size, feed amount, ammonia, temperature, humidity, light intensity, noise, and total egg production. Exact-duplicate inspection found 407 duplicated rows; therefore, the 74 unique observations were used as the primary evaluation dataset. Egg production rate was derived by normalizing total egg output by flock size, and low-production anomalies were defined using the 10th percentile threshold, resulting in eight anomaly cases. Supervised tree-based models were evaluated using repeated stratified four-fold cross-validation with 20 repeats, and unsupervised methods were used as anomaly baselines. XGBoost achieved the best full-feature performance, with F1-score of 0.928, recall of 1.000, ROC-AUC of 0.997, and PR-AUC of 0.984. Sensitivity analysis without flock size showed that environmental and management variables retained useful signal. SHAP analysis indicated that flock size, light intensity, and temperature were the dominant predictors. The findings support interpretable operational monitoring of low egg-production patterns, although the results require validation on larger expert-labeled datasets.
Pengembangan Smart Egg Incubator Semi Otomatis Berbasis Internet of Things dengan Notifikasi Cerdas Ali Akbar Ritonga; Ramadani Ritonga; Elysa Rohayani Hasibuan; Rohani Rohani
Bulletin of Information Technology (BIT) Vol 7 No 3: September 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i3.3082

Abstract

Abstract—Conventional egg incubation still faces challenges such as unstable temperature and humidity, manual egg turning, and limitations in continuously monitoring incubator conditions. These conditions can increase the monitoring burden and affect the stability of the incubation process. This study aims to develop a semi-automatic Smart Egg Incubator based on the Internet of Things (IoT) to perform real-time temperature and humidity monitoring, automatic egg turning, and a smart notification system for changes in incubation conditions. The research method employs a Research and Development approach with a prototyping methodology, including needs assessment, system design, hardware and software implementation, and functional testing using black-box testing. The system was developed using an ESP32, a DHT22 sensor, a heater, a DC fan, a servo motor, and an IoT platform as the data communication medium. Test results showed that the monitoring, temperature control, automatic egg turning, data communication, and notification functions operated as designed in the conducted test scenarios. The contribution of this research lies in the integration of real-time incubation condition monitoring, automatic egg turning, and smart notifications into a single semi-automatic IoT-based prototype. This integration provides a more practical and responsive alternative to manual monitoring and supports the development of more efficient egg-hatching systems.Keywords: Internet of Things; Smart Egg Incubator; ESP32; Real-Time Monitoring; Automatic Egg Turner; Notification System. Translated with DeepL.com (free version)
Klasifikasi Kinerja Konten YouTube Mobile Legends Menggunakan LightGBM dengan Pelabelan Berbasis K-Means dan Interpretasi SHAP Wayan Praka; Ella Kristiantini Susan; Lidya Nurmala Eva
Bulletin of Information Technology (BIT) Vol 7 No 3: September 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i3.3138

Abstract

YouTube is a video-sharing platform widely used by content creators, including those in the gaming category such as Mobile Legends. The intense competition among Mobile Legends content creators has made content performance analysis essential for developing data-driven content strategies. However, most previous studies have relied on manual data labeling, which is prone to subjectivity and lacks efficiency. Furthermore, high-accuracy classification models are often treated as black-box models, making it difficult to explain the factors influencing prediction outcomes. This study aims to develop a YouTube Mobile Legends content performance classification model by integrating K-Means, LightGBM, and Shapley Additive exPlanations (SHAP). The dataset consists of 3,052 videos collected using the YouTube Data API v3. The K-Means algorithm was employed to generate automatic labels, while LightGBM was used as the classification model and SHAP was applied to interpret the model's predictions. The results indicate that the optimal number of clusters was K=2, producing two performance classes: High Performance (72.44%) and Low Performance (27.56%). The dataset was subsequently divided into 80% for training and 20% for testing. On the testing dataset, the LightGBM model achieved an accuracy of 93.78%, precision of 93.87%, recall of 93.78%, and an F1-score of 93.81%. Furthermore, 10-fold cross-validation yielded a mean accuracy of 92.75% with a standard deviation of 0.0148, demonstrating the model's robustness and stability. SHAP analysis revealed that Subscriber Count was the most influential feature, followed by Duration, Video Age, and Title Length. These findings demonstrate that the integration of K-Means, LightGBM, and SHAP provides an effective approach for objectively, accurately, and transparently classifying the performance of Mobile Legends content on YouTube, while offering valuable insights to support content creators in developing data-driven content strategies.
Analysis of the Spatial Distribution of Rice Prices Acrossprovinces in Indonesia Using the K-Means Algorithm Parini; Yessica Siagian; Guntur Maha Putra; Julpan Hartono Suria Manja Manurung; Nuri Apriani; Putri Wulandari
Bulletin of Information Technology (BIT) Vol 7 No 3: September 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i3.3146

Abstract

Differences in rice prices across provinces in Indonesia reflect variations in distribution and market conditions that can be analyzed using a data clustering approach. This study aims to map the characteristics of interprovincial rice prices using the K-Means Clustering algorithm. The dataset consists of prices for Premium Rice, Medium Rice, Non-SPHP Medium Rice, and SPHP Rice obtained from official government data. The research stages included data preprocessing, transformation, normalization using StandardScaler, determining the number of clusters using the Elbow Method and Silhouette Score, and visualizing the results using Principal Component Analysis (PCA). The Elbow Method results indicated an efficient point at K = 5, while the highest Silhouette Score of 0.5658 was obtained at K = 7; thus, seven clusters were selected as the best model. PCA visualization reveals that provinces in Indonesia exhibit rice price characteristics that form seven groups with varying degrees of similarity. The research results indicate that the K-Means algorithm is capable of effectively identifying rice price clustering patterns and producing a map that can support the analysis of inter-regional price characteristics as a basis for formulating food distribution policies and stabilizing rice prices in Indonesia.
Implementasi Metode Dempster-Shafer Pada Sistem Pakar Diagnosa Penyakit Tumor Mediastinum Pada Manusia Berbasis Web Ipandi Siburian
Bulletin of Information Technology (BIT) Vol 1 No 1: Maret 2020
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Artificial intelligence (Artificial Intelligence) is a system that adopts knowledge from experts into an expert system, so that the computer can do as it is done by experts (experts) who act and can assist in providing solutions and making knowledge-based decisions appropriately. Expert systems are computer-based systems that use knowledge, facts, and reasoning techniques in solving problems, and usually can only be solved by an expert in a particular field. The expert system adds value to technology to help doctors diagnose diseases and provide information about the types of diseases, as well as general symptoms of mediastinal tumors.Mediastinum tumors are tumors found in the mediastinum, namely the imaginary cavity between the left and right lungs, the mediastinum contains the heart, large blood vessels, trachea, thymus, lymph nodes and connective tissue. The mediastinum is an important part of the thorax which is located between the pleuralist cavita and contains many important organs and vital structures. The mediastinum is divided into 4 chambers, namely anterior (front), middle, and posterior (back) superior and medial. Implementing the dempster-shafer method in the expert system it aims to diagnose web-based mediastinal tumor in humans based on the symptoms of mediastinal tumor. From the results of this study, it can be concluded that the expert system of diagnosing mediastinal tumors in humans is expected to help doctors (experts) in providing accurate and accurate diagnosis, so that patients know what disease they are suffering from.
Sistem Pakar Diagnosa Penyakit Pyelonephritis Pada Manusia Dengan Menggunakan Metode Fuzzy Mamdani Hotmaria Sianturi
Bulletin of Information Technology (BIT) Vol 1 No 1: Maret 2020
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Observing everyday life in society seems to be not only an educational, economic, and cultural factor which is a big problem for people today. It turns out that social factors related to the level of well-being, and public health are far more important issues to pay attention to. Because as we all know that the level of living welfare greatly impacts on the health level of the community itself. The choice of the problem concerning the type of Pyelonephritis in the human kidney as a sample of this study, is the fact that the kidney is an important organ in our body's metabolic system, because of the density of activities, we often forget to look after it. Irregular eating patterns, lack of fiber intake and mineral water, and consumption of high-calorie instant foods or drinks, have unwittingly made the kidneys work harder. In general, many people are reluctant or reluctant to see a doctor when they feel the symptoms experienced or also influenced by the absence of fees for consulting a doctor or the limitations of doctors in a particular area, causing handling of patient consultations less effectively and efficiently. So by relying on advancements in technology and information, it is very important to apply expert systems to diagnose diseases in the kidneys. This expert system was created for processing consultation data on pyelonephritis in the kidneys which can be done digitally, so that time is more effective, efficient and helps to deal with patients who are faster consulted. To produce a more accurate expert system, a supporting method is needed, namely fuzzy mamdani method
Sistem Pendukung Keputusan Untuk Pemilihan Buruh Harian Lepas Menjadi Karyawan Tetap Menggunakan Metode Profile Matching (Studi Kasus : PT. Nafasindo) Haidi Haidi
Bulletin of Information Technology (BIT) Vol 1 No 1: Maret 2020
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

A daily freelance worker is someone who works alone and is not committed to a certain long-term business owner. Temporary daily workers also have obligations that must be fulfilled as something that must be done if the day laborer wants to get his salary, by doing work with a large target without taking into account working hours, this is the only obligation that must be done because casual daily laborers do not bound to a permanent work agreement where usually in the permanent employment agreement the worker must obey every regulation set by the business owner both the company and individual business. Permanent employees are someone who works with the conditions made by the company in work and all work activities have been arranged and the payroll process is carried out with the basic salary set by the company monthly. So from that the plantations of PT. Nafasindo make an assessment in choosing daily burh employees to become permanent employees by making decisions based on the judgments made in the field. thus the need for decision making such as a computerized decision support system so that decision making can be done quickly and accurately. thus this decision support system uses a profile matching or profile matching method which will be used between a fixed profile and a casual day laborer profile with a review process on the criteria that will be set to fulfill permanent employment.
Penerapan Algoritma Marr-Hilderth Untuk Pendeteksian Tepi Pada Citra CT-Scan Agus Purwanto
Bulletin of Information Technology (BIT) Vol 1 No 1: Maret 2020
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Peningkatan kualitas citra merupakan salah satu proses awal dalam peningkatan mutu citra. Peningkatan mutu citra diperlukan karena seringkali citra yang di jadikan objek pembahasan mempunyai kualitas yang buruk, misalnya citra mengalami deraw, kabur. Metode Marr-hilderth dibuat dengan beberapa tahapan yaitu antara lain: image enhancement berupa proses perbaikan citra dengan meningkatkan kualitas citra baik kontras maupun kecerahan.
Implementasi Algoritma Mars Pada Penyandian Record Database Alimah Alimah; Nelly Astuti Hasibuan; Taronisokhi Zebua
Bulletin of Information Technology (BIT) Vol 1 No 1: Maret 2020
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Database records in the form of text are very widely used, so it is very vulnerable to data theft by unauthorized parties. In order to maintain the security of database records, it can be done by using cryptographic techniques. Cryptographic techniques can encode database records by encrypting them in the form of passwords that are not understood. The Mars algorithm is an algorithm that uses a 128-bit key and the encryption process consists of 32 rounds. This symmetry algorithm will produce a higher level of security against the database record because it can encode it into a password with a fairly complex process that will make it difficult for cryptanalysts to access the image. This research uses the Mars Algorithm for the encryption and decryption process, so that in the process it is necessary to go through several long steps in order to produce the final cipher. This research describes the process of securing a database record by encoding it based on the Mars algorithm, in the form of a password that is difficult for others to understand and understand. This is done in an effort to minimize acts of misuse of database records
Sistem Pendukung Keputusan Pemilihan Dosen Berprestasi Menggunakan Metode SMARTER Pada Universitas Budi Darma Natalia Silalahi
Bulletin of Information Technology (BIT) Vol 1 No 1: Maret 2020
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Lecturers are one aspect that is involved in the education process at tertiary institutions, where lecturers are part of the academic staff who run the Tri Dharma of Higher Education. At the Tri Dharma College, lecturers are asked not only to conduct education but also carry out research, community service and scientific development. In addition to teaching lecturers as well as forming a good image for a college so that it is necessary to be given an appreciation for the results that have been done by the lecturer. The award is given to increase motivation for lecturers to continue to compete in carrying out the Tri Dharma of Higher Education. Decision support system is an appropriate system used to select outstanding lecturers at Budi Darma University. By using a decision support system, it is possible to get a valid benchmark for the Head of the University of Budi Darma. In this research, the selection of outstanding lecturers was conducted using the SMARTER method, where in the SMARTER the weighting of the criteria and sub-criteria was carried out using the ROC method

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