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SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN GURU PRODUKTIF PESERTA PELATIHAN ASESOR KOMPETENSI LSP P1 SMK SWASTA DWIWARNA MEDAN MENGGUNAKAN METODE THE EXTENDED PROMETHEE II (EXPROM II) Assrani, Dwika; Mesran, Mesran; Sianturi, Ronda Deli; Yuhandri, Yuhandri; Iskandar, Akbar
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Vocational schools that have been licensed from BNSP to LSP P1 (first party professional certification institute) are schools that have been able to carry out their own competency certification exams for their students and later a competency assessor who will test and declare the eligibility of the students, competency assessors are productive teachers who have participated in and been given training by the government, in that training the schools choose from the number of productive teachers from each department to become competency assessor trainees in accordance with predetermined criteria so a decision support system is needed so there is no gap in the selection of productive teacher assessor training participants, a vocational school that has become a P1 LSP must have a competency assessor and is a requirement to be a P1 LSP. one of the solutions to the problem is the right one by using the Decision Support System (SPK). Decision Support System (DSS) can help the school in making the decision to choose the productive teacher of the appropriate assessor training and improve the efficiency of the decision. The Extended Promethee II (EXPROM II) is a development of the Promethee II method based on the ideal and anti-ideal solution. Promethee II itself is a method of making decisions on the function of preferences with problems through an outranking approach (ranking) or is a multicriteria analysis, comparing one alternative to another and calculating the alternative gap in pairs so as to produce an output that is alternative ranking based on the highest value.Keywords: Competitive Assessor LSP P1, SPK, The Extended Promethee II

Pembobotan Kriteria Dalam Prediksi Meningitis Tuberkulosis Menggunakan Metode SWARA dan Nearest Neighbor Dwika Assrani; Pahala Sirait; Andri Andri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3276

Weights greatly affect the value and results of decisions or predictions of a test data, a problem that often occurs in the results of the prediction process is the weighting of symptom attributes which is less certain of the value of the weight, thus affecting the prediction results and the level of accuracy of a prediction itself. This study predicts a data using the Nearest Neighbor method where in the process of predicting the attribute weight value does not yet have a definite value for testing. Then we need an attribute weighting for each test attribute to get a definite weight value result. One method that can be applied to attribute weighting is the SWARA method. Based on research conducted to compare the prediction of Meningitis Tuberculosis without SWARA weighting and with SWARA weighting, testing with a ratio of 90:10, 80:20, 70:30 results in disease prediction using the Nearest Neighbor method, there are differences in results and levels of prediction accuracy and the process in prediction helps shorten the time to find prediction results, the highest prediction result using the swara method is 100% accurate and without weighting method is 91%.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN GURU PRODUKTIF PESERTA PELATIHAN ASESOR KOMPETENSI LSP P1 SMK SWASTA DWIWARNA MEDAN MENGGUNAKAN METODE THE EXTENDED PROMETHEE II (EXPROM II) Dwika Assrani; Mesran Mesran; Ronda Deli Sianturi; Yuhandri Yuhandri; Akbar Iskandar
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v2i1.922

Vocational schools that have been licensed from BNSP to LSP P1 (first party professional certification institute) are schools that have been able to carry out their own competency certification exams for their students and later a competency assessor who will test and declare the eligibility of the students, competency assessors are productive teachers who have participated in and been given training by the government, in that training the schools choose from the number of productive teachers from each department to become competency assessor trainees in accordance with predetermined criteria so a decision support system is needed so there is no gap in the selection of productive teacher assessor training participants, a vocational school that has become a P1 LSP must have a competency assessor and is a requirement to be a P1 LSP. one of the solutions to the problem is the right one by using the Decision Support System (SPK). Decision Support System (DSS) can help the school in making the decision to choose the productive teacher of the appropriate assessor training and improve the efficiency of the decision. The Extended Promethee II (EXPROM II) is a development of the Promethee II method based on the ideal and anti-ideal solution. Promethee II itself is a method of making decisions on the function of preferences with problems through an outranking approach (ranking) or is a multicriteria analysis, comparing one alternative to another and calculating the alternative gap in pairs so as to produce an output that is alternative ranking based on the highest value.Keywords: Competitive Assessor LSP P1, SPK, The Extended Promethee II

Penentuan Penerima Bantuan Siswa Miskin Menerapkan Metode Multi Objective Optimization on The Basis of Ratio Analysis (MOORA) Dwika Assrani; Nurul Huda; Rudi Sidabutar; Imam Saputra; Oris Krianto Sulaiman
JURIKOM (Jurnal Riset Komputer) Vol 5, No 1 (2018): Februari 2018
Publisher : STMIK Budi Darma

The BSM Program is a National Program aimed at eliminating the barriers of poor students participating to school by helping poor students obtain proper access to education services, preventing dropping out, attracting poor students to return to school, helping students meet needs in learning activities, supporting compulsory education programs 9 Years (even up to middle level), as well as help smooth school programs. To obtain the Poor Student Assistance (BSM) fund, the government sets out some criteria for who are the students who can be eligible and entitled to receive Poor Student Assistance (BSM). The criteria will be later that will assist the school or educational institution in determining which students can be eligible to receive Poor Student Assistance Fund. Therefore, an educational institution must have a Decision Support Support System of Poor Student Fund (BSM) using Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method, with a decision support system of Poor Student Assistance (BSM) is expected to be successful, on target, and accepted by the rightful person. Thus the decision maker can compare the performance between the old system with the BSM funding decision support system with the method of Multi-Objective Optimization On The Basis Of Ratio Analysis (MOORA) without having to ask back the data of students who will be given Poor Student Assistance funds.

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