Repository Universitas Pakuan

Detail Karya Ilmiah Dosen

Eneng Tita Tosida, Fajar Delli Wihartiko, Agnes Chintia Dewi, Indra Permana Solihin

Judul : Prospect Prediction Model of Indonesian Telematics Medium and Large Enterprises Using Ensemble Approach

Abstrak :
Medium and Large Enterprises (MLE) play an important role in promoting development and increasing Indonesia's competitiveness in the international arena. Currently, there is not much in-depth analysis related to the prospects for medium and large telematics businesses to find out its relevance to economic conditions and what factors affect business prospects. Whereas the telematics industry sector is a supporting sector for Gross Domestic Product (GDP) with a higher growth rate compared to other sectors. The purpose of this study is to predict the prospects MLE telematics businesses using an ensemble approach with the Boost and Bagging algorithm. Data obtained from the 2016 Economic Census. The target class for business prospects consists of five classes, namely better, the same as bad, worse, and cannot be compared. Optimal results are obtained with the average precision value is 76,8, recall is 79,0 and F1-score
is 77,13. The model is able to produce important features that can be validated by experts. The advantages of the prospective MLE telematics feature are the level of sales of goods and services, profits, and the level of education of the business owner.

Keywords – Classification, Ensemble, Telematics, Medium and Large Enterprises

Tahun : 2021 Media Publikasi : Prosiding

Kategori : Prosiding No/Vol/Tahun : 3 / 4 / 2021

ISSN/ISBN : 978-1-6654-2733-3

PTN/S : Universitas Pakuan Program Studi : ILMU KOMPUTER

Bibliography :
SDPPI, T. P., “Analysis Of Indonesia's Telecommunications Industry To Support Efficiency,” Jakarta, 2018.

Nurhanisah, Y., “Startup Business Scale in Indonesia,” Retrieved from Indonesia Baik: http://indonesiabaik.id/infografis/startup indone-sia-skala-usaha-dan-masalah-yang-dihadapi, 2019.

Tosida, E. T., Maryana, S., & Thaheer, H., “The Potential of the Telematics Service Business Group,” Proceedings of the National Seminar on Quality of Life through IT & Management Application. Palembang: Universitas Bina Darm.a, 2014

Tosida, E. T., Hairlangga, O., Amirudin, F., and Ridwanah, M., “Application of decision rules for empowering of Indonesian Telematics Services SMEs,” IOP Conf. Series: Materials Science and Engineering 332, January, 1-8, 2018.

Tosida, E.T., Andria, F., Wahyudin, I., Widianto, R., Ganda, M., and Lathif, R.R, "A Hybrid Data Mining Model for Indonesian telematics SMEs Empowerment, IOP Conference Series : Materials Science and Engineering 567 (1), 012001, 2019.

Tosida, E.T., Wahyudi, I., Andria, F., Ningsih, W.K., and Lestari, D.D., “Business Intelligence of Indonesian Telematics Human Resource : Optimization of Customer and Internal Balanced
Scorecards, Journal of Southwest Jiaotong University, 55 (2), 2020, pp 1-13.

Siringoringo, R., & Jaya, I. K. “Ensemble Learning dengan Metode SMOTE Bagging pada Klasifikasi Data Tidak Seimbang,” Information System Development (Isd) Volume 3 No.2 Juli 2018, 75-81

Jayasree, V., & Balan, R. S., “A Review On Data Mining In Banking Sector,” American Journal of Applied Sciences, 2013, 1160-1165.

Tosida, E. T., Wihartiko, F. D.., Utep, Andria, F. “Prospect Prediction Model of Indonesian Telematics Medium Large Size Enterprise Using Deep Learning Approach,” International Journal of Electrical Engineering and Information Technology, Vol. 04, No. 01, March 2021, 55-65.

Witten, I.H., Frank, E., Hall, M.A., and Pal, C.J., "Data Mining: Practical Machine Learning Tools and Techniques", Fourth Ed., Morgan Kaufmann, 2017, https://doi.org/10.1016/C2015-0-02071-8

Undang-Undang Republik Indonesia No 20 Tahun 2008 tentang usaha mikro, kecil, dan menengah. 2008. Jakarta.

S. Liu, J. Xiao, J. Liu, X. Wang, J. Wu and J. Zhu, "Visual Diagnosis of Tree Boosting Methods," in IEEE Transactions on Visualization and Computer Graphics, vol. 24, no. 1, pp. 163-173, Jan. 2018, doi: 10.1109/TVCG.2017.2744378.

Mayr, A., and Hofner, B., “Boosting for Statistical Modelling-A Non-technical Introduction”, Sage Journars, January 24, 2018, https://doi.org/10.1177 /1471082X17748086

Menak, D. P. “Telecommunication Business is Getting Sexier, More Promising,” Retrieved from BisnisTempo: https://bisnis.tempo.co/read/10306 00/bisnis-telekomunikasimakin-seksi-makin-menjanjikan/full&view=ok, November 4, 2017.

Srirejeki, K. “Analysis of the Benefits of the Social Media in Empowering Micro, Small and Medium Enterprises (MLMEs),” Jurnal Masyarakat Telematika dan Informasi Vol. 7 No.1, 2016, 57-68.

Nasution, R. D. “The Effect of the Digital Gap on Rural Development,” Jurnal Penelitian Komunikasi dan Opini Publik Vol.20 No.1, 2016, 31-44.

Kominfo. “The Number of Internet Users in 2017 Increases, Kominfo Continues to Accelerate Broadband Development,” Retrieved from Siaran Pers: https://kominfo.go.id/content/detail/12640/ siaran-pers-no- 53hmkominfo022018-tentang-jum lah-pengguna-internet-2017- ,February 19, 2018.

Song, Y., & Cai, W. “Handling of Feature Space Complexity for Texture Analysis in Medical Images,” Biomedical Texture Analysis, 2017, 163-191.

Sagi, O., and Rokach, L., “Ensemble Learning : A Survey”, WIREs Data Mining and Knowledge Discovery, 8 (4), 2018, https://doi.org/10.1002 /widm.1249

Ubing, A.A., Jasmi, S.K., Abdullah, A., Jhanjhi, N.Z., and Supramaniam, M., “ Phishing Website Detection: An Improved Accuracy through Feature Selection and Ensemble Learning”, IJACSA, International Journal of Advanced Computer Science and Applications, 10 (1), 2019.

Padhi S., Millstein T., Nori A., Sharma R., “Overfitting in Synthesis: Theory and Practice”, In : Dillig I., Tasiran S. (eds) Computer Aided Verification. CAV 2019. https://doi.org/10.1007/ 978-3-030-25540-4_17

Marzuki, A., Bustaman, U., & Yuniarti. “Economic Cencus Evaluation of the Small and Medium Enterprises – Medium and Large Entreprises,” Jakarta: Badan Pusat Statistik, 2019.

Suci, Y. R. “Development of MSMEs (Micro, Small, and Medium Enterprises) in Indonesia,” Jurnal Ilmiah Cano Ekonomos Vol. 6 No. 1 Januari 2017, 51-58.

Pertiwi, D. “The Influence of the Number of Labor, Capital, Technology, and Enterpreneurship on the Profits of Micro, Small and Medium Enterprises,” Jurnal Ilmiah Mahasiswa Fakultas
Ekonomi dan Bisnis Universitas Brawijaya, 2017, 1-10.

Muharam, H., Andria, F., and Tosida, E.T., “Effect of Process Innovation and Market Innovation on Financial Performance with Moderating Role of Disruptive Technology, Systematic Reviews in
Pharm. 11(1), 2020, 223-232.

Kemenkop. “KEMENKOP and SMEs Will Intensify the Transformation of SMEs From Offline To Onlilne,” Retrieved from Kementrian Koperasi dan Usaha Kecil dan Menengah Republik
Indonesia:http://www.depkop.go.id/read/kemen-kop-dan-ukmakan-gencarkan-transformasi-umkm -dari-offline-ke-online, May, 2020.

URL : https://ieeexplore.ieee.org/abstract/document/9699309

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Detail Karya Ilmiah Dosen

Eneng Tita Tosida, Fajar Delli Wihartiko, Agnes Chintia Dewi, Indra Permana Solihin

Judul	:	Prospect Prediction Model of Indonesian Telematics Medium and Large Enterprises Using Ensemble Approach
Abstrak	:	Medium and Large Enterprises (MLE) play an important role in promoting development and increasing Indonesia's competitiveness in the international arena. Currently, there is not much in-depth analysis related to the prospects for medium and large telematics businesses to find out its relevance to economic conditions and what factors affect business prospects. Whereas the telematics industry sector is a supporting sector for Gross Domestic Product (GDP) with a higher growth rate compared to other sectors. The purpose of this study is to predict the prospects MLE telematics businesses using an ensemble approach with the Boost and Bagging algorithm. Data obtained from the 2016 Economic Census. The target class for business prospects consists of five classes, namely better, the same as bad, worse, and cannot be compared. Optimal results are obtained with the average precision value is 76,8, recall is 79,0 and F1-score is 77,13. The model is able to produce important features that can be validated by experts. The advantages of the prospective MLE telematics feature are the level of sales of goods and services, profits, and the level of education of the business owner. Keywords – Classification, Ensemble, Telematics, Medium and Large Enterprises
Tahun	:	2021	Media Publikasi	:	Prosiding
Kategori	:	Prosiding	No/Vol/Tahun	:	3 / 4 / 2021
ISSN/ISBN	:	978-1-6654-2733-3
PTN/S	:	Universitas Pakuan	Program Studi	:	ILMU KOMPUTER
Bibliography	:	SDPPI, T. P., “Analysis Of Indonesia's Telecommunications Industry To Support Efficiency,” Jakarta, 2018. Nurhanisah, Y., “Startup Business Scale in Indonesia,” Retrieved from Indonesia Baik: http://indonesiabaik.id/infografis/startup indone-sia-skala-usaha-dan-masalah-yang-dihadapi, 2019. Tosida, E. T., Maryana, S., & Thaheer, H., “The Potential of the Telematics Service Business Group,” Proceedings of the National Seminar on Quality of Life through IT & Management Application. Palembang: Universitas Bina Darm.a, 2014 Tosida, E. T., Hairlangga, O., Amirudin, F., and Ridwanah, M., “Application of decision rules for empowering of Indonesian Telematics Services SMEs,” IOP Conf. Series: Materials Science and Engineering 332, January, 1-8, 2018. Tosida, E.T., Andria, F., Wahyudin, I., Widianto, R., Ganda, M., and Lathif, R.R, "A Hybrid Data Mining Model for Indonesian telematics SMEs Empowerment, IOP Conference Series : Materials Science and Engineering 567 (1), 012001, 2019. Tosida, E.T., Wahyudi, I., Andria, F., Ningsih, W.K., and Lestari, D.D., “Business Intelligence of Indonesian Telematics Human Resource : Optimization of Customer and Internal Balanced Scorecards, Journal of Southwest Jiaotong University, 55 (2), 2020, pp 1-13. Siringoringo, R., & Jaya, I. K. “Ensemble Learning dengan Metode SMOTE Bagging pada Klasifikasi Data Tidak Seimbang,” Information System Development (Isd) Volume 3 No.2 Juli 2018, 75-81 Jayasree, V., & Balan, R. S., “A Review On Data Mining In Banking Sector,” American Journal of Applied Sciences, 2013, 1160-1165. Tosida, E. T., Wihartiko, F. D.., Utep, Andria, F. “Prospect Prediction Model of Indonesian Telematics Medium Large Size Enterprise Using Deep Learning Approach,” International Journal of Electrical Engineering and Information Technology, Vol. 04, No. 01, March 2021, 55-65. Witten, I.H., Frank, E., Hall, M.A., and Pal, C.J., "Data Mining: Practical Machine Learning Tools and Techniques", Fourth Ed., Morgan Kaufmann, 2017, https://doi.org/10.1016/C2015-0-02071-8 Undang-Undang Republik Indonesia No 20 Tahun 2008 tentang usaha mikro, kecil, dan menengah. 2008. Jakarta. S. Liu, J. Xiao, J. Liu, X. Wang, J. Wu and J. Zhu, "Visual Diagnosis of Tree Boosting Methods," in IEEE Transactions on Visualization and Computer Graphics, vol. 24, no. 1, pp. 163-173, Jan. 2018, doi: 10.1109/TVCG.2017.2744378. Mayr, A., and Hofner, B., “Boosting for Statistical Modelling-A Non-technical Introduction”, Sage Journars, January 24, 2018, https://doi.org/10.1177 /1471082X17748086 Menak, D. P. “Telecommunication Business is Getting Sexier, More Promising,” Retrieved from BisnisTempo: https://bisnis.tempo.co/read/10306 00/bisnis-telekomunikasimakin-seksi-makin-menjanjikan/full&view=ok, November 4, 2017. Srirejeki, K. “Analysis of the Benefits of the Social Media in Empowering Micro, Small and Medium Enterprises (MLMEs),” Jurnal Masyarakat Telematika dan Informasi Vol. 7 No.1, 2016, 57-68. Nasution, R. D. “The Effect of the Digital Gap on Rural Development,” Jurnal Penelitian Komunikasi dan Opini Publik Vol.20 No.1, 2016, 31-44. Kominfo. “The Number of Internet Users in 2017 Increases, Kominfo Continues to Accelerate Broadband Development,” Retrieved from Siaran Pers: https://kominfo.go.id/content/detail/12640/ siaran-pers-no- 53hmkominfo022018-tentang-jum lah-pengguna-internet-2017- ,February 19, 2018. Song, Y., & Cai, W. “Handling of Feature Space Complexity for Texture Analysis in Medical Images,” Biomedical Texture Analysis, 2017, 163-191. Sagi, O., and Rokach, L., “Ensemble Learning : A Survey”, WIREs Data Mining and Knowledge Discovery, 8 (4), 2018, https://doi.org/10.1002 /widm.1249 Ubing, A.A., Jasmi, S.K., Abdullah, A., Jhanjhi, N.Z., and Supramaniam, M., “ Phishing Website Detection: An Improved Accuracy through Feature Selection and Ensemble Learning”, IJACSA, International Journal of Advanced Computer Science and Applications, 10 (1), 2019. Padhi S., Millstein T., Nori A., Sharma R., “Overfitting in Synthesis: Theory and Practice”, In : Dillig I., Tasiran S. (eds) Computer Aided Verification. CAV 2019. https://doi.org/10.1007/ 978-3-030-25540-4_17 Marzuki, A., Bustaman, U., & Yuniarti. “Economic Cencus Evaluation of the Small and Medium Enterprises – Medium and Large Entreprises,” Jakarta: Badan Pusat Statistik, 2019. Suci, Y. R. “Development of MSMEs (Micro, Small, and Medium Enterprises) in Indonesia,” Jurnal Ilmiah Cano Ekonomos Vol. 6 No. 1 Januari 2017, 51-58. Pertiwi, D. “The Influence of the Number of Labor, Capital, Technology, and Enterpreneurship on the Profits of Micro, Small and Medium Enterprises,” Jurnal Ilmiah Mahasiswa Fakultas Ekonomi dan Bisnis Universitas Brawijaya, 2017, 1-10. Muharam, H., Andria, F., and Tosida, E.T., “Effect of Process Innovation and Market Innovation on Financial Performance with Moderating Role of Disruptive Technology, Systematic Reviews in Pharm. 11(1), 2020, 223-232. Kemenkop. “KEMENKOP and SMEs Will Intensify the Transformation of SMEs From Offline To Onlilne,” Retrieved from Kementrian Koperasi dan Usaha Kecil dan Menengah Republik Indonesia:http://www.depkop.go.id/read/kemen-kop-dan-ukmakan-gencarkan-transformasi-umkm -dari-offline-ke-online, May, 2020.
URL	:	https://ieeexplore.ieee.org/abstract/document/9699309