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All Journal CommIT (Communication & Information Technology) Jurnal TIMES Sinkron : Jurnal dan Penelitian Teknik Informatika METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Teknik Informatika (JUTIF) Jurnal Info Sains : Informatika dan Sains Jurnal Armada Informatika Journal of Computing Theories and Applications
Octara Pribadi
STMIK TIME
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Perancangan Aplikasi Kids Memory Game Berbasis Android Octaviandy, Pieter; Pribadi, Octara; Juliyanto
Jurnal TIMES Vol 9 No 1 (2020)
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (798.214 KB) | DOI: 10.51351/jtm.9.1.2020618

Abstract

Child growth is the most important moment for a child. Children who are still young must be equipped with useful education so that later it will be useful when the child is growing up. Children's memory is very important to be trained as a child because with the process of memory training it can train the child to be fast in learning something good whether it's a lesson or other general matters. In practice, the learning process to train the child's memory is still done manually, namely by picture books, this is less interesting for the child because children prefer to play while learning. Besides the existing textbooks are quite boring because there are no games or sound effects that attract the child's interest to learn. Therefore, the above problems will be designed an educational game that trains children's memory with the concept of play. The results of this study are in the form of an educational game called Kids Memory Game which is used as a media for children's education and media to train children's memory.
Sistem Kendali Jarak Jauh Air Conditioner (AC) Berbasis IoT Pribadi, Octara
Jurnal TIMES Vol 9 No 1 (2020)
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3.436 KB) | DOI: 10.51351/jtm.9.1.2020622

Abstract

Dalam penelitian ini penulis merancang sistem kendali jarak jauh untuk mengendalikan Air Conditioner (AC) menggantikan remote konvensional. Penulis menggunakan mikrokontroler ESP8266 dan Infrared Led (IR Led) serta aplikasi blynk. Dalam penelitian ini akan dilihat apakah sistem yang dirancang dapat berjalan dengan baik, dengan pengkondisian jaringan WiFi yang digunakan secara khusus untuk sistem yang dirancang. Diharapkan dalam penelitian ini bisa menjadi referensi bagi peneliti lain dalam mengembangkan peneltian serupa, dan tidak menutup kemungkinan juga dapat dihasilkan produk jadi siap pakai dikemudian harinya.
Design of a Web-Based School Profile at Northern Green School Medan Using the Importance Performance Analysis Method Destisonya Buulolo; Jackri Hendrik; Octara Pribadi
Jurnal Info Sains : Informatika dan Sains Vol. 15 No. 01 (2025): Informatika dan Sains , 2025
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

School profile website in today's education world is very important, to convey information and school identity to the public. Currently, SD Northern Green School Medan does not have one that can function as a means of promotion that presents various important information such as school name, location, vision and mission, student achievements, gallery, and contacts that can be reached by parents and the public who want to register their children at SD Northern Green School Medan. This study aims to design a web-based school profile that is able to meet the information needs of users. The method applied in this study is the Importance Performance Analysis (IPA) Method, which helps in identifying the required attributes and evaluating their performance from the user's perspective. Data were obtained through direct observation and distributing questionnaires to 50 respondents. The results of the analysis using the Importance Performance Analysis (IPA) method show that elements such as school profile, achievements, activity gallery, and contact information are important parts that must be on the SD Northern Green School Medan website. This website was developed using HTML, PHP, and MySQL. With the presence of this website, it is hoped that the school will be able to be more effective in conveying information and improving the reputation of SD Northern Green School Medan in the current digital era.
Sistem Pemantauan Kualitas Udara Berbasis IoT di Peternakan Yakin Telur Hendri; Pribadi, Octara; Hendrik, Jackri
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp145-150

Abstract

Air quality in poultry farms plays a crucial role in animal productivity, as poor air quality can increase the risk of disease in chickens, cause stress, and ultimately reduce productivity and egg quality, leading to economic losses for farmers. Laying hens require stable and adequate temperature conditions during their growth period to ensure optimal development. The optimal temperature for laying hens during the brooding period (up to 14 days old) ranges between 30-32°C. A common issue faced by livestock farmers is the lack of adequate facilities to manage stress in livestock, which often hinders their ability to stabilize the air temperature in the chicken coop. Farmers often rely on manual methods to estimate and adjust the temperature inside the coop by feeling the heat, which is neither accurate nor efficient. This research aims to design an IoT-based air quality monitoring system at Yakin Telur Farm. The system is designed to monitor temperature, humidity, and ammonia gas levels in the chicken coop in real-time.
Akurasi K-Means dengan Menggunakan Cluster dan Titik Grid Terbaik pada Pemetaan Grid Interatif K-Means Perangin Angin, Johanes Terang Kita; Rizkita, Ari; Robet, Robet; Pribadi, Octara
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp127-129

Abstract

Traditional K-Means face 2 (two) main problems, namely: Determination of Initial Centroid and poor initial cluster. Determining the initial centroid using random numbers is one of the main problems in classical K-Means which results in low accuracy and long computation time. Likewise, determining the good centroid of each cluster without being accompanied by a process of paying attention to the performance of each cluster can also cause the accuracy value obtained is not good. This study will contribute to how the performance obtained by determining a good initial centroid is combined with the use of a good cluster. Determination of a good initial centroid is done by using the K-Means Grid Mapping which divides the determination of the centroid into several Grid Points. The result of this research is a combination of Iterative K-Means with Grid Mapping K-Means to become Iterative Grid Mapping K-Means which will get a good initial centroid and also a good cluster shown in the table of iris and abalone, comparison of the variables in the iris and abalone affecting the best cluster as a result.
Multi-Class Brain Tumor Segmentation and Classification in MRI Using a U-Net and Machine Learning Model Hendrik, Jackri; Pribadi, Octara; Hendri, Hendri; Hoki, Leony; Tarigan, Feriani Astuti; Wijaya, Edi; Ali, Rabei Raad
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5369

Abstract

Brain tumor diagnosis remains a critical challenge in medical imaging, as accurate classification and precise localization are essential for effective treatment planning. Traditional diagnostic approaches often rely on manual interpretation of MRI scans, which can be time-consuming, subjective, and prone to variability across radiologists. To address this limitation, this study proposes a two-stage framework that integrates machine learning (ML) based classifiers for tumor type recognition and a U-Net architecture for tumor segmentation. The classifier was trained to distinguish four tumor categories: glioma, meningioma, pituitary, and no tumor, while the U-Net model was employed to delineate tumor regions at the pixel level, enabling volumetric assessment. The novelty of this research lies in its dual focus that combines classification and segmentation within a single framework, which enhances clinical applicability by offering both diagnostic and spatial insights. Experimental results demonstrated that among the evaluated classifiers, XGBoost achieved the highest accuracy of 86 percent, surpassing other models such as Random Forest, SVC, and Logistic Regression, while the U-Net model delivered consistent segmentation performance across tumor types. These findings highlight the potential of hybrid ML and deep learning solutions to improve reliability, efficiency, and objectivity in brain tumor analysis. In real-world practice, the proposed framework can serve as a valuable decision-support tool, assisting radiologists in early detection, reducing diagnostic workload, and supporting personalized treatment strategies.
Co-Authors Aghaunor, Tabitha Chukwudi Ali, Rabei Raad Andi Andi Carles Juliandy Daniel Happy Putra david De Rosal Ignatius Moses Setiadi Destisonya Buulolo Edi Wijaya ENDRI ENDRI Feriani Astuti Tarigan Halim, Marwa Hendri Hendri Hoki, Leony Jackri Hendrik Jackri Hendrik Juliyanto Kartikadarma , Etika Ojugo, Arnold Adimabua Perangin Angin, Johanes Perangin Angin, Johanes Terang Kita Pieter Octaviandy, Pieter Rizkita, Ari Robert Robet Robet Robet rusdiana Sarker, Md Kamruzzaman Setyoko, Bimo Haryo Sukiman Sukiman Suwanty Suwanty Suwanty Suwanty, Suwanty Suyud Widiono Ugbotu, Eferhire Valentine Wilson