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All Journal Semantik Jurnal Pseudocode Wahana Teknik Sipil: Jurnal Pengembangan Teknik Sipil BANGUN REKAPRIMA Jurnal Teknologi Informasi Cyberku Jurnal Hilirisasi Technology kepada Masyarakat (SITECHMAS) Journal of Computing Theories and Applications Journal of Future Artificial Intelligence and Technologies
Stefanus Santosa
Politeknik Negeri Semarang
Humanities 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 Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Transportation Other

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KLASIFIKASI PESAN SMS MENGGUNAKAN ALGORITMA NAIVE BAYES DENGAN SELEKSI FITUR GENETIC ALGORITHM Indah Munitasri; Stefanus Santosa; Catur Supriyanto
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 14 No 1 (2018): Jurnal Teknologi Informasi CyberKU Vol.14 no 1 2018
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

Short Message service (SMS)is mobile communication that interest advertiser for its effective deliveries with cheap operational cost compare to printed media. Some spam SMS do not need mailing list to reach their customers. But, spam SMS could create higher respons from emails spam. Spam SMS includes promotion,scamming,and fraud.To overcome this problem,anti-spam filtering are needed to detect spam and non-spam SMS. Some anti-spam filtering algoritm such as Decission Tree, Naïve Bayes (NB),Support Vector Machine (SVM),and Neural Network. This research used Naïve Bayes classifier or known as multinominal Naïve Bayes is a simplification from Bayes algoritm which is suitable for text or documents classification.This study will make additional Genetic Algorithms in the process of selecting attributes that will be used in the classification process with Naïve Bayes algorithm. Genetic Algorithms can be used as an attribute of the overall voter attributes obtained from the process of feature extraction. NB compared to NB and GA produced significant accuracy result, NB gained 89.39% accuracy rate, but GA gained 89.73% accuracy rate. So, there is an increase in 0.34 % after adding GA. NB and GA can be applied to the classification of SMS messages, because Naïve Bayes algorithm is an algorithm that does not consider the relationship between attributes to one another (independence). So, when there is a data set with hundreds of attributes, all of those attributes will be counted by Naïve Bayes, by adding a Genetic Algorithm as a feature selection, which determines the attributes that are relevant in order to optimize the classification accuracy. It is expected to apply feature selection using Particle Swarm Optimization (PSO) for the next research because there is no evolution in the operator, for example, mutation and crossover on Genetic Algorithms (GA,) and PSO is more flexible in maintaining the balance between global and local searches on its search space.
KLASIFIKASI CITRA TELUR FERTIL DAN INFERTIL DENGAN ANALISIS TEKSTUR GRAY LEVEL CO-OCCURRENCE MATRIX DAN SUPPORT VECTOR MACHINE Dewi Nurdiyah; Stefanus Santosa; Ricardus Anggi Pramunendar
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 11 No 2 (2015): Jurnal Teknologi Informasi CyberKU Vol.11 no 2
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

Fertility eggs test are steps that must be performed in an attempt to hatch eggs. Fertility testusually use egg candling. The purpose of observation is to choose eggs fertile (eggs containedembryos) and infertile eggs (eggs that are no embryos). And then fertilized egg will be entered intothe incubator for hatching eggs and infertile can be egg consumption. However, there are obstaclesin the process of sorting the eggs are less time efficient and inaccuracies of human vision todistinguish between fertile and infertile eggs. To overcome this problem, it can be used ComputerVision technology is having such a principle of human vision. It used to identify an object basedon certain characteristics, so that the object can be classified. The aim of this study to classifyimage fertile and infertile eggs with SVM (Support Vector Machine) algorithm based on inputfrom bloodspot texture analysis and blood vessels with GLCM (Gray Level Co-occurrenceMatrix). Eggs image studied are 6 day old eggs. It is expected that the proposed method is anappropriate method for classification image fertile and infertile eggs.
OPTIMASI PARAMETER ARTIFICIAL NEURAL NETWORK DENGAN MENGGUNAKAN ALGORITMA GENETIKA UNTUK MEMPREDIKSI NILAI TUKAR RUPIAH Khairul Fahmi; Stefanus Santosa; Ahmad Zainul Fanani
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 11 No 2 (2015): Jurnal Teknologi Informasi CyberKU Vol.11 no 2
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

To predict foreign exchange rate is not easy, accurate prediction is necessary for investor to reduce higrisk about exchange rate volatility. In predicting foreign exchange rate is used Artificial Neural NetworkBackpropagation as a model that applied. There are several parameters to implement Artificial NeuralNetwork that must be determined as training cyclel, learning rate, and momentum, the problem is the lackof standard guidelines in determining the parameters that will be used, therefore in this method used theexperimental method. So that we need a method that can resolve the problem, then that the parametersobtained become more optimal. Solutions that can be applied is to apply the genetic algorithm (GA) onArtificial Neural Networks, in order to optimize the value of training cycle, learning rate and momentumparameters. The results are the application of optimization techniques with Genetic Algorithm canfacilitate the search for optimal parameter values and reduce error (RMSE) or increase the value of theaccuracy of the Artificial Neural Network algorithm, thus the model obtained can be used by investor topredict foreign exchange rate.
VISUALISASI PROSES DALAM GENERATOR LISTRIK DENGAN PENDEKATAN KOGNITIF-BEHAVIORISTIK UNTUK PEMBELAJARAN SISWA SMK Agus Setyawan; Edi Noersasongko; Stefanus Santosa
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 11 No 1 (2015): Jurnal Teknologi Informasi CyberKU Vol.11 no 1
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

Power generation is one of the learning materials in Competence Expertise Electricity, methods of tutorials, lectures and question and answer and practices originating in the textbook or modules used in learning. Obstacle field practice that is in addition to equipment is limited, some generators have been damaged either due to aging or installation errors of the students on practice time. It is also to know more clearly about the working principle of electric generators in this case is the magnetic field and rotor rotation that can generate electricity learners understand the difficulty because the occurrence is in the generator with a closed circuit. In reality the practice field to meet the ideal lesson about electrical generators required is expensive and the more generators are turned on at the same time will generate noise that can interfere with other learners. Appropriate learning method is to use the visualization method in this case is by displaying the symbols or tools that illustrate the process of installation of electricity generators and the actual electricity generation process, including the parts of the generator, such as: rotor, stator, the anchor and the commutator. Research done by making the model visualization in the form of interactive multimedia animations and equipped with control equipment that can be operated by users, so users can choose what you want to proceed. From the data showed that the media system in the form of generator power this gives a positive contribution to the understanding of student learning.
PREDIKSI LOYALITAS PELANGGAN TELEKOMUNIKASI MENGGUNAKAN LOGISTIC REGRESSION DENGAN SELEKSI FITUR PARTICLE SWARM OPTIMIZATION Stefanus Santosa; Fenilinas Adi Artanto
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 11 No 1 (2015): Jurnal Teknologi Informasi CyberKU Vol.11 no 1
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

For many companies, finding a reason to lose customers, measurement of customer loyalty and regain customers have become essential, including for telecommunication companies. The telecommunications company is one of the industry, where the customer really needs special attention because it is very influential in maintaining the stability of the company's revenue. The telecommunications industry has always faced the threat of financial loss resulting from customer loyalty. The customer who leaves the service is usually called churners. Find churners can help telecommunications companies in retaining customers and keep the company financially. This study used Logistic Regression algorithm with feature selection Particle Swarm Optimization to predict customer loyalty telecommunications. The test results obtained using ANN algorithm accuracy value amounted to 94.80%, and Logistic Regression Algorithm with Particle Swarm Optimization feature selection shows the value of accuracy of 97.65%, and the AUC value of 0.99, then the Logistic Regression algorithm with feature selection Particle Swarm Optimization can improve the accuracy of prediction telecommunications customer loyalty
PREDIKSI HARGA KEDELAI LOKAL DAN KEDELAI IMPOR DENGAN METODE SUPPORT VECTOR MACHINE BERBASIS FORWARD SELECTION Fatkhuroji Fatkhuroji; Stefanus Santosa; Ricardus Anggi Pramunendar
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 15 No 1 (2019): Jurnal Teknologi Informasi CyberKU Vol. 15, no 1
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

Besarnya permintaan harga kedelai yang tinggi untuk kebutuhan makanan baik untuk olahan atau bahan jadi menjadikan harga kedelai sangat fluktuatif seiring impor kedelai yang terus meningkat. Pola harga kedelai yang sangat fluktuatif memicu gejolak ekomoni yang memicu terjadinya inflasi di salah satu daerah. Untuk mengatasi hal tersebut perlu adanya suatu prediksi harga kedelai agar pemerintah dapat mengantisipasinya. belum ada model prediksi terhadap harga komoditas kedelai baik lokal maupun impor, model prediksi yang ada saat ini tentang komoditi sembako. Penelitian ini mengusulkan model prediksi harga kedelai dengan menerapkan algoritma Support Vector Machine (SVM) dengan optimasi menggunakan Forward Selection. Untuk prediksi kedelai lokal dengan menggunakan parameter inputan data 4 (empat ) hari sebelumnya, K-fold=10, nilai C= 0,1 diperoleh nilai RMSE terkecil sebesar 154.025 +/- 114.993. Setelah dilakukan seleksi atribut menggunakan Forward Selection diperoleh nilai RMSE sebesar 79.749 +/- 16.051, terdapat peningkatan RMSE sebesar= 74.276. Untuk prediksi kedelai lokal dengan menggunakan parameter inputan data 5 (lima) hari sebelumnya, K-fold=15, nilai C= 0,1 diperoleh nilai RMSE terkecil sebesar 126.008 +/- 78.371, setelah dilakukan optimasi menggunakan Forward Selection diperoleh nilai RMSE sebesar 122.270 +/- 56.049, terdapat peningkatan RMSE sebesar= 3.738.
DESAIN PROTOTIPE ALAT BANTU KLASTERISASI GAYA BELAJAR DAN KECERDASAN MAJEMUK BERBASIS JST KOHONEN Stefanus Santosa; Wiji Lestari Panjidang
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 14 No 2 (2018): Jurnal Teknologi Informasi CyberKU Vol.14 no 2
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

Sistem pembelajaran yang mampu mendukung peningkatan pengalaman belajar siswa dan menciptakan kemudahan bagi guru untuk merancang strategi pembelajaran yang mampu beradaptasi dengan karakteristik siswa masih menjadi tantangan besar dunia pendidikan. Pembelajaran adaptif perlu mempertimbangkan gaya belajar dan kecerdasan majemuk siswa yang berbeda-beda dan unik. Data mining dan machine learning mampu memberikan solusi atas masalah tersebut. Penelitian ini mengusulkan suatu Desain prototipe Alat Bantu Klasterisasi Gaya Belajar dan Kecerdasan Majemuk Berbasis Jaringan Syaraf Tiruan (JST) Kohonen yang diharapkan dapat menjadi acuan pengembangan LMS yang mampu memetakan pembelajar sehingga memungkinkan siswa untuk memperoleh pelayanan pembelajaran secara khusus dan unik sesuai dengan karakteristiknya dan memudahkan guru dalam penyusunan strategi pembelajaran.
Klasterisasi Kecerdasan Majemuk Siswa Berbasis Jaringan Syaraf Kohonen Guna Mendukung Adaptive Elearning Stefanus Santosa; Wiji Lestari Panjidang; Yonathan Purbo Santosa
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 15 No 2 (2019): Jurnal Teknologi Informasi - Jurnal CyberKU Vol. 15, no 2
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

Learning strategies are often applied without considering the unique and different characteristics of the learner's intelligence. This causes students to have difficulty understanding the material, not focused, bored, decreased motivation, frustration, and various other learning difficulties. The efforts to create student-oriented learning strategies can be done with adaptive elearning. Adaptive elearning system requires recognition function to cluster the intelligence of the learner when learning takes place. This study shows that Kohonen's Artificial Neural Network can be used for mapping students based on multiple intelligences. The results showed that there were 8 clusters with different intelligence compositions. There is no cluster that has a single intelligence. Intrapersonal intelligence is almost owned by 90% of students, while the lowest is visual-spatial intelligence, which is only 23.33%. In order to create a learner-oriented learning process, this clustering method should be embedded in an adaptive elearning system.
DESAIN DAN VALIDASI MODEL BASIS DATA PEMELIHARAAN KOMPONEN ARSITEKTUR GEDUNG SEBAGAI PENDUKUNG FACILITY MAINTENANCE MANAGEMENT (FMM) Santosa, Stefanus; Suroso, Suroso; Suwarto, Suwarto; Setiyono, Karnawan Joko; Suwarno, Anung
Wahana Teknik Sipil: Jurnal Pengembangan Teknik Sipil Vol. 29 No. 1 (2024): Wahana Teknik Sipil
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/wahanats.v29i1.5647

Abstract

The problems that arise in Facility Maintenance Management (FMM) in Indonesia, which involve aspects of management, learning, and mutual understanding in the Common Data Environment (CDE), can be overcome one way by developing a database. To compile a good database, a database design method is required that is based on existing theories and standards. This research was conducted to design a database model with the scope of the object of architectural component maintenance of buildings starting from the stages of identifying needs, designing, and testing to users. The results of the study show that the database model obtained has the category of "very feasible" overall or partially in terms of service quality and material aspects. This also proves that proven methods and design techniques in providing accurate, non-overlapping, and efficient information needed in the management of material data, equipment, contractors, types of work, schedules, and costs during the maintenance and maintenance of architectural component buildings can be met properly through a relational database approach and verification and validation testing. For the development of science, especially Computational of Building Modeling Learning Technology, the results of this research provide a contribution in the form of a Database Model for Architectural Component Maintenance that can be applied in industry and education. It is recommended that this database design model be further developed into a Building Architectural Component Maintenance Information System.
VISUALISASI DAN UJI COBA METODE PERAWATAN LANTAI KERAMIK GUNA PEMBELAJARAN VIRTUAL Santosa, Stefanus; Suwarto, Suwarto; Suroso, Suroso; Setiyono, Karnawan Joko; Setyaningsih, Desi; Ilala, Oze Dora
Wahana Teknik Sipil: Jurnal Pengembangan Teknik Sipil Vol. 28 No. 1 (2023): Wahana Teknik Sipil
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/wahanats.v28i1.4557

Abstract

The Architecture, Engineering, Construction, and Operations (AECO) industry has shown high interest in the use of Building Information Modeling (BIM) for Facility Maintenance Management (FMM). The opportunity to use BIM for the operational activities of building facilities is very large, but the use of BIM in FM is still far behind compared to the implementation of BIM at the design and construction stages. This research is intended to test the tile floor maintenance method and create visualizations in animative form and apply them in virtual learning with evaluation based on the Technology Acceptance Model (TAM). The results of the student t-test statistical test showed that there was a very significant effect of the Ceramic Floor Care Method Learning Media on increasing user knowledge in 5 aspects (learning objectives, knowledge, materials, service quality, and appearance). The test results by media experts on the aspects of language, display, and service quality obtained the "very feasible" category, while the test results by material experts on the aspects of learning objectives, material delivery, and material selection also obtained the "very feasible" category to be applied in learning/ training. It is hoped that the results of this research can trigger the formation of an open access BIM object library.
Co-Authors Abd. Rasyid Syamsuri Adityawan, Harish Trio Agus Setyawan Agus Widjanarko Ahmad Zainul Fanani Ajib Susanto Ali Sofyan Anung Suwarno, Anung April Firman Daru Basuki Setiyo Budi BASUKI SETIYO BUDI S.T., M.T. Catur Supriyanto Catur Supriyanto Catur Supriyanto Supriyanto De Rosal Ignatius Moses Setiadi Dewi Nurdiyah Dianita Ratna Kusumastuti Edi Noersasongko Erni Rahmawatie Fahdiyat, Lukman Fahdiyat, Lukman Farroq, Omar Fatkhuroji Fatkhuroji Fenilinas Adi Artanto Gan, Hong-Seng Goro, Garup Lambang Hadi Wibowo Hadi, Tjokro Hario Guritno Heri Triluqman Budisantoso Ilala, Oze Dora Indah Munitasri Islam, Hussain Md Mehedul Isnubroto, Danang Jadi . Joko, Karnawan JUNAIDI S.T., M.Eng. Karnawan Joko Setiyono Khairul Fahmi Leily Fatmawati, Leily M. Arief Soeleman Marchus Budi Utomo Marchus Budi Utomo, Marchus Budi MARSUDI Marsudi Marsudi Martono Martono Martono Martono Martono Martono Mawardi Mawardi Mochammad Tri Rochadi Nur Aeni Widiastuti Ojugo, Arnold Adimabua Pertiwi, Zulaikha Putri Pertiwi, Zulaikha Putri Praharseno, Fikri Pratama, M Hafidh Aditya Putra, Erwin Dwika Rabinah, Aiun Hayatu Ricardus Anggi Pramunendar Rifqi Aulia Abdillah, Rifqi Aulia Roselina Rahmawati Roy Yuliantara S, Sri Wahyuningsih Sarker, Md Kamruzzaman Setiyono, Karnawan Joko Setyaningsih, Desi SUDARMONO SUDARMONO Suhartono, Edy Sukoyo Sukoyo Sulaiman, Sri Wahyuningsih Sulaiman, Sriwahyuningsih Supriyadi Supriyadi Supriyo Supriyo Supriyo Suroso Suroso Suroso Suroso Suwarto Suwarto Suwarto Suwarto Tjokro Hadi TJOKRO HADI SST., M.T. Triatmo Sugih Hardono W, Herry Ludiro Wahyono, Herry Ludiro Wicaksono, M Rafi Wiji Lestari Yonathan Purbo Santosa Yudha Tirto Pramonoaji Yusetyowati Yusetyowati, Yusetyowati Zenal Arifin Zuama, Leygian Reyhan