Article Per Year (5 Year)
p-Index From 2020 - 2025
2.589
P-Index
This Author published in this journals
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

Published : 38 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search
Journal : Jurnal Teknologi Informasi Cyberku

 1   2 
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (952.424 KB)

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (246.53 KB)

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (367.934 KB)

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (360.633 KB)

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (433.09 KB)

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.
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