Garuda - Garba Rujukan Digital

Penentuan Penerima BSM Secara Objektiv Berdasarkan Metode Decision Support System VIKOR Tundo, Tundo; Akbar, Riolandi; Nugroho, Agung Yuliyanto; Saidah, Andi
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 2 (2024): September
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i2.10434

This research was conducted because of complaints from several parents regarding the BSM decision at SDN Kalanganyar ABC, however there were several students who were less well off because the choice of BSM was still subjective. SDN Kalanganyar ABC always holds activities related to BSM admissions once a year. It is hoped that this activity can also provide benefits for students who are poor but have excellent grades so they can carry out activities without being burdened by financial needs. In reality, there are still many students who do not receive BSM, even though according to the requirements, these students should be entitled to receive BSM. Therefore, there is a very irrational subjectivity in the ongoing elections. To overcome this problem, researchers tried to develop an application that applies the Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, namely a method that makes decisions based on a rational compromise of criteria. These criteria include student reports, parents' income, academic achievement, dependents, home conditions, parents' relatives, and activity. From the results of the analysis and application of the VIKOR decision support system, subjective results were obtained for students whose evaluation standards and final decisions were lower than several other students, but the school provided BSM recommendations. To prevent the recurrence of this incident, VIKOR was able to answer objective findings with results of 76.57% with subjective findings of 23.43% in the previous system.

Penentuan Penerima BSM Secara Objektiv Berdasarkan Metode Decision Support System VIKOR Tundo, Tundo; Akbar, Riolandi; Nugroho, Agung Yuliyanto; Saidah, Andi
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar

This research was conducted because of complaints from several parents regarding the BSM decision at SDN Kalanganyar ABC, however there were several students who were less well off because the choice of BSM was still subjective. SDN Kalanganyar ABC always holds activities related to BSM admissions once a year. It is hoped that this activity can also provide benefits for students who are poor but have excellent grades so they can carry out activities without being burdened by financial needs. In reality, there are still many students who do not receive BSM, even though according to the requirements, these students should be entitled to receive BSM. Therefore, there is a very irrational subjectivity in the ongoing elections. To overcome this problem, researchers tried to develop an application that applies the Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, namely a method that makes decisions based on a rational compromise of criteria. These criteria include student reports, parents' income, academic achievement, dependents, home conditions, parents' relatives, and activity. From the results of the analysis and application of the VIKOR decision support system, subjective results were obtained for students whose evaluation standards and final decisions were lower than several other students, but the school provided BSM recommendations. To prevent the recurrence of this incident, VIKOR was able to answer objective findings with results of 76.57% with subjective findings of 23.43% in the previous system.

Analisis Perbandingan Fuzzy Tsukamoto dan Sugeno dalam Menentukan Jumlah Produksi Kain Tenun Menggunakan Base Rule Decision Tree Tundo, Tundo; Akbar, Riolandi; Sela, Enny Itje
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 1: Februari 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020701751

Penelitian ini menerangkan tentang analisis perbandingan fuzzy Tsukamoto dan Sugeno dalam menentukan jumlah produksi kain tenun dengan menggunakan base rule decision tree. Dari hasil analisis penelitian ini, maka ditemukan beberapa perbedaan yang sangat signifikan: (1) Metode fuzzy Tsukamoto dari hasil yang diperoleh lebih mendekati dari data sesungguhnya, dibandingkan dengan fuzzy Sugeno, (2) Selisih yang diperoleh dengan menggunakan fuzzy Tsukamoto dengan data produksi sesungguhnya selalu konsisten yaitu hasil fuzzy Tsukamoto selalu lebih besar, sedangkan untuk fuzzy Sugeno tidak konsisten, (3) Hasil selisih untuk fuzzy Tsukamoto relatif mendekati dari data produksi sesungguhnya, sedangkan untuk fuzzy Sugeno relatif jauh selisih yang dihasilkan. Sehingga dapat disimpulkan bahwa metode yang paling mendekati nilai kebenaran adalah produksi yang mengunakan metode Tsukamoto dengan keakuratan yang diperoleh menggunakan base rule decision tree sebesar 83.3333 %.AbstractThis study describes the comparative analysis of fuzzy Tsukamoto and Sugeno determining the amount of woven fabric production using a decision tree base rule. From the results the analysis of this study, we found several very significant differences: (1) The fuzzy Tsukamoto method of the results obtained is closer to the actual, compared to fuzzy Sugeno, (2) The difference obtained by using fuzzy Tsukamoto with actual production data is always consistent is that Tsukamoto fuzzy results are always greater, while for Sugeno's fuzzy inconsistency, (3) The difference results for fuzzy Tsukamoto are relatively close to the actual production data, whereas Sugeno fuzzy is relatively far from the difference produced. So it can be concluded that the method closest to the truth value is production using the Tsukamoto method with the accuracy obtained using the base rule decision tree of 83.3333%.

Penentuan Bantuan Siswa Miskin Menggunakan Fuzzy Tsukamoto Dengan Perbandingan Rule Pakar dan Decision Tree (Studi Kasus : SDN 37 Bengkulu Selatan) Akbar, Riolandi; 'Uyun, Shofwatul
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 4: Agustus 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.0813191

Penelitian penentuan calon bantuan siswa miskin ini di Sekolah Dasar Negeri 37 Bengkulu Selatan. Masalah yang terjadi ada ketidaksesuaian dari hasil output dalam pemberian bantuan siswa miskin, belum digunakannya metode keputusan untuk setiap kriteria dan masih menggunakan penilaian prediksi atau perkiraan untuk calon penerima bantuan. Metode penelitian yang dilakukan menggunakan Fuzzy Tsukamoto dengan perbandingan dua metode yaitu rule pakar dan Decision Tree SimpleCart. Tahapan penelitian ini dimulai dengan menganalisis output dengan melakukan seleksi dari sejumlah alternatif hasil, kemudian melakukan pencarian nilai bobot setiap atribut dari Fuzzy Tsukamoto dengan metode perbandingan rule pakar dan Decision Tree SimpleCart. Selanjutnya menentukan parameter batasan fungsi keanggotaan fuzzy meliputi kartu perlindungan sosial, nilai rata-rata raport, tanggungan, penghasilan orang tua, prestasi dan kepemilikan rumah. Analisis hasil yang diperoleh dari pengujian terhadap 75 data siswa dan telah dilakukan klasifikasi menggunakan Fuzzy Tsukamoto didapatkan hasil akurasi dengan metode rule pakar sebesar 72% dan metode Decision Tree SimpleCart sebesar 76%. Hasil akurasi tersebut di simpulkan bahwa metode Decision Tree SimpleCart mempunyai tingkat akurasi yang lebih tinggi dari metode rule pakar sehingga lebih mampu dalam menyeleksi serta mencari nilai bobot penentuan bantuan siswa miskin. AbstractResearch on the determination of candidates for assistance from poor students in South Bengkulu 37 Primary School. The problem that occurs is there is a mismatch of the output results in the provision of assistance to poor students, the decision method has not been used for each criterion and is still using predictive or estimated assessments for prospective beneficiaries. The research method used was Fuzzy Tsukamoto with a comparison of two methods, namely expert rule, and SimpleCart Decision Tree. The stages of this research began by analyzing the output by selecting many alternative results, then searching for the weight value of each attribute from Fuzzy Tsukamoto with the method of expert rule comparison and the SimpleCart Decision Tree. Next determine the parameters of the fuzzy membership function limit includes social protection cards, the average value of report cards, dependents, parents' income, achievements, and homeownership. Analysis of the results obtained from testing of 75 student data and classification using Fuzzy Tsukamoto has obtained accuracy with the expert rule method by 72% and the SimpleCart Decision Tree method by 76%. The accuracy results are concluded that the SimpleCart Decision Tree method has a higher level of accuracy than the expert rule method so that it is better able to select and search for the weighting value of determining the assistance of poor students.

Title

Found 4 Documents
Search

Abstract

Abstract

Abstract

Abstract

Title Search

Found 4 Documents Search

Abstract

Abstract

Abstract

Abstract

Title

Found 4 Documents
Search