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Pengelompokan Negara Berdasarkan Indikator Kesejahteraan Dengan Metode Unsupervised Learning-Clustering: Bukti Empiris dari 167 Negara Imaduddin Farih; Lukman Fadillah; N Nadira; Verry Dina Aromy; Harry Patria
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.423

One of the goals of the countries is to do continuous development in a positive direction so that the welfare of the country is guaranteed. To assess the development of a country can be seen from various factors such as socioeconomic and health factors. Some of the indicators used including GDP, health, income, export-import and others. This analysis can be used an evaluation of each country to improve its level. In addition, it is also used as a basis for determining which countries are entitled to receive assistance from funding institutions, so that the people of these countries can have a better life. Based on these problems, the authors analyze data of countries in the world using the Machine Learning Unsupervised which is Clustering method with KNIME. This analysis aims to determine the effect of indicators on the level of a country. The data to be studied are 167 countries in the world with socioeconomic and health factors. Based on research to avoid multicolenarity the authors use the PCA method. From this study, the authors used 4 PCA which represented 90% of the data and obtained 3 optimal clusters with an average silhouette value of 0.443.

Analisis Konsumsi Energi Listrik Pelanggan Dan Biaya Pokok Produksi Penyediaan Energi Listrik dengan Machine Learning Raditya Hari Nugraha; Eko Yuwono; Latif Prasetyohadi; Yanuardhi Arief B; Harry Patria
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.424

PT PLN (Persero) during the Covid-19 pandemic was one of the companies whose sales growth was affected by the decline in electricity consumption in several sectors. Another condition is that several power plant and substation construction projects have fulfilled the realization commitment to the RUPTL from PT PLN (Persero). This has resulted in PT PLN (Persero) being faced with an over supply condition between power capacity and customer usage load. Realization of sales growth until July 2021 was 4.44% (144,788 TWh). Energy consumption in July 2021 was 20.55 TWh where the growth of kWh sales in July 2021 comparing with July 2020 began to show a recovery of +1.82%. The factor that most affected business and industrial growth was the manufacturing sector in Indonesia experiencing a slowdown/contraction as reflected in the PMI (Purchasing Managers Index) which decreased from 53.5 to 40.1. Growth is strongly influenced by consumer behavior in responding to government regulations, especially related to controlling the spread of Covid-19 in Indonesia in the form of restrictions on social activities (PSBB, PPKM, or Lockdown) which have been effectively implemented since April 2020 until now. Based on the analysis of the customer's electrical energy consumption data per industrial sector, as well as using technical data on the availability of power per electrical sub-system and the cost of producing electrical energy in an area, an evaluation model will be obtained that can be used in selecting the criteria for prospective customers who will be given program offers "SEMAKIN PRODUKTIF". By using "SEMAKIN PRODUKTIF" program data modeling, it is hoped that prospective customers will be given program offers so that they can be an opportunity to increase sales growth of electrical energy which is targeted to grow 6% in December 2021

Pengelompokan Negara Berdasarkan Indikator Kesejahteraan Dengan Metode Unsupervised Learning-Clustering: Bukti Empiris dari 167 Negara Imaduddin Farih; Lukman Fadillah; N Nadira; Verry Dina Aromy; Harry Patria
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.423

One of the goals of the countries is to do continuous development in a positive direction so that the welfare of the country is guaranteed. To assess the development of a country can be seen from various factors such as socioeconomic and health factors. Some of the indicators used including GDP, health, income, export-import and others. This analysis can be used an evaluation of each country to improve its level. In addition, it is also used as a basis for determining which countries are entitled to receive assistance from funding institutions, so that the people of these countries can have a better life. Based on these problems, the authors analyze data of countries in the world using the Machine Learning Unsupervised which is Clustering method with KNIME. This analysis aims to determine the effect of indicators on the level of a country. The data to be studied are 167 countries in the world with socioeconomic and health factors. Based on research to avoid multicolenarity the authors use the PCA method. From this study, the authors used 4 PCA which represented 90% of the data and obtained 3 optimal clusters with an average silhouette value of 0.443.

Analisis Konsumsi Energi Listrik Pelanggan Dan Biaya Pokok Produksi Penyediaan Energi Listrik dengan Machine Learning Raditya Hari Nugraha; Eko Yuwono; Latif Prasetyohadi; Yanuardhi Arief B; Harry Patria
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.424

PT PLN (Persero) during the Covid-19 pandemic was one of the companies whose sales growth was affected by the decline in electricity consumption in several sectors. Another condition is that several power plant and substation construction projects have fulfilled the realization commitment to the RUPTL from PT PLN (Persero). This has resulted in PT PLN (Persero) being faced with an over supply condition between power capacity and customer usage load. Realization of sales growth until July 2021 was 4.44% (144,788 TWh). Energy consumption in July 2021 was 20.55 TWh where the growth of kWh sales in July 2021 comparing with July 2020 began to show a recovery of +1.82%. The factor that most affected business and industrial growth was the manufacturing sector in Indonesia experiencing a slowdown/contraction as reflected in the PMI (Purchasing Managers Index) which decreased from 53.5 to 40.1. Growth is strongly influenced by consumer behavior in responding to government regulations, especially related to controlling the spread of Covid-19 in Indonesia in the form of restrictions on social activities (PSBB, PPKM, or Lockdown) which have been effectively implemented since April 2020 until now. Based on the analysis of the customer's electrical energy consumption data per industrial sector, as well as using technical data on the availability of power per electrical sub-system and the cost of producing electrical energy in an area, an evaluation model will be obtained that can be used in selecting the criteria for prospective customers who will be given program offers "SEMAKIN PRODUKTIF". By using "SEMAKIN PRODUKTIF" program data modeling, it is hoped that prospective customers will be given program offers so that they can be an opportunity to increase sales growth of electrical energy which is targeted to grow 6% in December 2021

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