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All Journal Jurnal Manajemen Pendidikan Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) CKI On Spot International Journal of Computer Technology and Science International Journal of Information Engineering and Science International Journal of Electrical Engineering, Mathematics and Computer Science Journal of Engineering, Electrical and Informatics
SOPAN ADRIANTO
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mathematics Social Sciences

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PENGARUH KETERAMPILAN TEKNIS, KETERAMPILAN SOSIAL, KETERAMPILAN KONSEPTUAL, DAN KETERAMPILAN MANAJERIAL TERHADAP KINERJA KEPALA SEKOLAH DASAR NEGERI DI WILAYAH JAKARTA PUSAT SOPAN ADRIANTO
Jurnal Manajemen Pendidikan Vol 2 No 1 (2011): Jurnal Manajemen Pendidikan Volume 2 Nomor 1 Juli 2011
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (170.726 KB) | DOI: 10.21009/jmp.v2i1.2469

Abstract

The aim of this causal research is to obtain information related to the possibility that principals’ performance effected by technical skills, social skills, conceptual skills, and managerial skills.Survey was applied in this research which data have been analysed by path analysis after all variables put into a correlation matrix. In this research, the principals have been choosen as unit analysis and 114 samples selected randomly.The result of analysis find out that principals’ performance is effected directly by managerial skills, but effected indirectly by technical skills, social skills, and conceptual skills.Based on those findings it could be concluded that variation of principals’ performance might have been effected by the variation of technical skills, social skills, conceptual skills, and managerial skills.Therefore, technical skills, social skills, conceptual skills, and managerial skills should be put into the consideration in managing the principals’ performance of the State Elementary Schools in Central Jakarta.
PERANAN PENDIDIKAN SEBAGAI TRANSFORMASI BUDAYA Sopan Adrianto
CKI ON SPOT Vol 12, No 1 (2019): CKI ON SPOT
Publisher : STIKOM CKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (105.362 KB)

Abstract

Education is a process of civilizing humans so education is very important for the transfer of culture. Education aims to build the totality of human capabilities, both as individuals and members of society. As a vital element in civilized human life, culture takes its constituent elements from all the sciences which are considered truly vital and are very necessary in interpreting everything in their lives. Humans who do not know culture are not the same as their own people. Therefore we mustpreserve and preserve culture by means of the educational process including cultural elements. So cultural elements should be included in the education process so that output from education is not only knowledge but is ready to live in society
Smart Absen Siswa dan Guru dengan Menggunakan Computer Vision pada Mafatih Islamic School Tebet Dadang Iskandar Mulyana; Sopan Adrianto; Muhammad Rifqi Syatria; Muhammad Rival; Rodhi Shafia Zaidan
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3792

Abstract

An integrated technology-based attendance system was developed to address the inefficiencies of queuing and the dependency on manual input at Mafatih Islamic School. The proposed solution leverages a ResNet model within the dlib framework (Python) alongside a Laravel API for real-time face detection using a camera installed at the entrance. Data is temporarily stored in SQLite as an offline backup and later transmitted to the server in base64 format, accompanied by bounding box visualization as audit evidence.This system is capable of handling.
Classification Of Image Corner Point Detection System To Identify A Shape Using The Viola Jones Method Frencis Matheos Sarimole; Sopan Adrianto; Dedi Gunawan; Fiktor Kurnia Tafonao
International Journal of Computer Technology and Science Vol. 1 No. 3 (2024): July : International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i3.314

Abstract

Along with the times, computer technology is developing very rapidly. The increasingly rapid development of computer technology means that everyone is required to utilize computer technology in their daily lives. Utilization of technology is one of the implementation roles of scientific disciplines. The reason behind the formation of this research is so that in the future it will become a fun learning concept in the introduction of objects and shapes in children and the motor development of children. children are usually more interested in seeing pictorial text, or pictures that contain lots of color. The Viola Jones method itself was chosen as the research completion algorithm. The Viola Jones method is usually used as a method in research that discusses the detection of objects, faces and others. The Viola Jones method was chosen because it has a high level of accuracy that can reach 100% probability.
Implementation of the Naive Bayes Model Multicategory for Analysis Sentiment Product Wardah on Shopee E-Commerce Mesra Betty Yel; Sopan Adrianto; Rasiban Rasiban; Eva Widiyanti
International Journal of Information Engineering and Science Vol. 2 No. 2 (2025): May : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i2.6

Abstract

The growth of information technology has driven changes in consumer behavior, one of which is through e-commerce platforms such as Shopee. This phenomenon has generated a large number of customer reviews, including those for local cosmetic products such as Wardah. These reviews serve as an important source of information for understanding customer perceptions and satisfaction levels. However, manual analysis of large and linguistically diverse datasets is inefficient and potentially subjective. This study aims to implement the multi-category Naive Bayes algorithm to classify the sentiment of Wardah product reviews on Shopee into three categories: positive, negative, and neutral. The data were collected using a web scraping technique and processed through a series of preprocessing stages including case folding, tokenization, stopword removal, stemming, and text cleaning. Subsequently, term weighting was performed using the TF-IDF method prior to classification. Model performance was evaluated using a confusion matrix as well as accuracy, precision, and recall metrics. The results indicate that the multi-category Naive Bayes algorithm achieved an accuracy of 86.00%, a precision of 86.63%, and a recall of 98.24%. This approach can assist business practitioners in objectively understanding customer opinions and supporting decision-making in business strategy and product development.
Optimization of Signature Language Tracking Objects Using GMM Models and Kalman Filters Including ROI Dadang Iskandar Mulyana; Sopan Adrianto; Tatinia Arda Rizqi Amalia; Putri Elsa Widiastuti
International Journal of Electrical Engineering, Mathematics and Computer Science Vol. 1 No. 3 (2024): September : International Journal of Electrical Engineering, Mathematics and Co
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijeemcs.v1i3.7

Abstract

Sign language recognition is one of the areas of image recognition and image processing technology that is developing rapidly in human-computer interaction. This technology really helps the deaf and speech impaired in communicating with non-disabled people. This research aims to examine the optimization of an object tracking system in sign language using the Gaussian Mixture Model (GMM) and Kalman Filter by including the Region of Interest (ROI). The proposed system consists of three main components, namely hand detection, object extraction, and classification. Hand detection is done using the Kalman Filter to track hand movements accurately. Next, Region of Interest (ROI) features, such as shape, direction and movement features, are extracted from the detected part of the hand. These features are fed into a Gaussian Mixture Model (GMM) classifier, which can recognize sign language based on the extracted features. With the combination of GMM and Kalman Filter in this research, it can increase accuracy in object tracking, reduce interference from the background, and ensure the tracking focus remains on important objects. The dataset used is in the form os SIBI alphabet symbols, namely A-Z with the amount of data for each class, namely 620 images. Based on the research result, model testing using GMM, Kalman Filter and ROI produces higher accuracy of 99%, while model testing using GMM and ROI produces accuracy of 90%.
Implementation of the Naive Bayes Algorithm and Support Vector Machine for Public Sentiment Analysis towards the Ratification of the Job Creation Bill on Twitter Untung Surapati; Sopan Adrianto; Erno Sumantri; Melinius Nopianto
Journal of Engineering, Electrical and Informatics Vol. 2 No. 1 (2022): Februari : Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i1.202

Abstract

The test design of the Public Sentiment Analysis on the Ratification of the Job Creation Bill with the RapidMiner Studio application. The initial stage is to collect data in the form of tweets of Twitter users and then put it into a CSV file, the data obtained will be divided into training data and test data. Furthermore, the training data will be labeled consisting of 2 types of labels, namely Positive and Negative labels, then the data will be cleaned from unneeded words such as Mention or Hastag, then the data will go through several stages in the Preprocessing stage to convert raw data into data that is ready to be processed. Furthermore, each word will be weighted with the TF-IDF method. The final result of the comparison with these two test methods, namely the prediction of Public Sentiment Towards the Issue of Determining the Job Creation Bill based on data obtained from Twitter and implemented by the SVM (Support Vector Machine) method, showed an accuracy value of 96.52%. Of the 605 test data, 492 data were predicted as Negative Sentiment and 112 data as Positive Sentiment and the Naive Bayes Method showed an accuracy value of 49.67%. Of the 605 test data, 492 data were predicted as Negative Sentiment and 112 data as Positive Sentiment.
Co-Authors Betty Yel, Mesra Dadang Iskandar Mulyana` Dedi Gunawan Erno Sumantri Eva Widiyanti Fiktor Kurnia Tafonao Melinius Nopianto Muhammad Rifqi Syatria Muhammad Rival Putri Elsa Widiastuti Rasiban Rasiban Rodhi Shafia Zaidan Sarimole, Frencis Matheos Tatinia Arda Rizqi Amalia Untung Surapati