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All Journal SOSIALITAS (Jurnal Ilmiah Pend. Sos-Ant) Martabe : Jurnal Pengabdian Kepada Masyarakat Devotion: Journal Corner of Community Service Noumerico: Journal of Technology in Mathematics Education Bustanul Ulum Journal of Islamic Education SYAIKHONA: Jurnal Magister Pendidikan Agama Islam PRIMER: Journal of Primary Education Research Dinamis: Jurnal Pengabdian Kepada Masyarakat Inovate : Jurnal Ilmiah Inovasi Teknologi Informasi
ANITA ANDRIANI, ANITA
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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KOMPARASI METODE GROUP INVESTIGATION (GI) DAN METODE JIGSAW TERHADAP HASIL BELAJAR SOSIOLOGI SISWA KELAS XI IPS SMA AL ISLAM 1 SURAKARTA TAHUN PELAJARAN 2014/2015 ANDRIANI, ANITA
ISSN.2252-8407
Publisher : SOSIALITAS; Jurnal Ilmiah Pend. Sos Ant

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (136.886 KB)

Abstract

ABSTRAKTujuan penelitian adalah untuk mengetahui: (1) perbedaan penggunaan metode Group Investigation (GI) dan metode Jigsaw terhadap hasil belajar Sosiologi siswa (2) pengaruh penggunaan metode Group Investigation (GI) dan metode Jigsaw terhadap hasil belajar Sosiologi siswa (3) seberapa besar pengaruh penggunaan metode Group Investigation (GI) dan metode Jigsaw terhadap hasil belajar Sosiologi siswa. Penelitian dilakukan pada kelas XI IPS di SMA Al Islam 1 Surakarta.Penelitian ini termasuk penelitian kausal komparatif dengan bentuk penelitian semu. Populasi penelitian adalah seluruh siswa SMA Al Islam 1 Surakarta tahun Pelajaran 2014/2015. Sampel penelitian sebanyak dua kelas dilakukan dengan teknik multistage cluster random sampling. Teknik pengumpulan data menggunakan tes, angket, dan dokumentasi. Teknik analisa data menggunakan analisis Paired Samples t-test.Kesimpulan dari penelitian adalah terdapat penggunaan metode Group Investigation (GI) dan metode Jigsaw terhadap hasil belajar Sosiologi siswa kelas XI IPS SMA Al Islam 1 Surakarta. Hasil analisis menunjukkan rata-rata penggunaan metode Group Investigation (GI) sebesar 64.33 dan rata-rata metode Jigsaw sebesar 71.67 dengan Sig= 0.000 (sangat signifikan). Nilai rata-rata kelas dengan metode Jigsaw lebih tinggi dibanding rata-rata kelas metode Group Investigation (GI). Hasil analisis menunjukkan harga t= 6.339 dengan Sig= 0.000 (sangat signifikan). Metode belajar memberikan pengaruh terhadap hasil belajar sebesar 28% dan 72% dipengaruhi faktor lain. Kata Kunci: Hasil Belajar Sosiologi, Group Investigation (GI), Jigsaw.
Sosialisasi Vaksinasi Covid-19 di Wilayah Sukarame II Sebagai Bentuk Kesadaran dan Keperdulian Terhadap Sesama dalam Menjaga Imunitas Saat Pandemi Sesuai Himbauan Pemerintah Amallia, Neysa; Perdana, M. Harviend Gilang; Putubasai, Erwin; Andriani, Anita; Saputra, Wawan Adi
Devotion: Journal Corner of Community Service Vol. 1 No. 3 (2023): February
Publisher : CV. Tripe Konsultan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54012/devotion.v1i3.158

Abstract

Pengabdian kepada masyarakat dilakukan dengan tujuan untuk memberikan sosialisasi kepada masyarakat tentang pentingnya vaksinasi untuk mengurangi penyebaran virus Covid-19. Sasaran utama dari Pengabdian Kepada Masyarakat ini adalah masyarakat di Kelurahan Sukarame II, Kecamatan Teluk Betung Barat, Kota Bandar Lampung, karena masih banyak masyarakat yang belum dan takut mengikuti vaksinasi Covid-19. Kegiatan ini dilaksanakan dengan memberikan informasi mengenai pemahaman tentang gejala yang ditimbulkan setelah melakukan vaksinasi Covid-19, protokol kesehatan, dan penatalaksanaan yang bisa dilakukan di rumah setelah melakukan vaksinasi Covid-19. Metode pelaksanaan kegiatan ini berupa sosialisasi. Hasil dari kegiatan sosialiasi ini adalah meningkatnya kesadaran masyarakat untuk melakukan vaksinasi Covid-19.
Measuring Faith with Numbers: Can Islamic Religious Education Exams Assess Spiritual Understanding? Andriani, Anita; Al Ayyubi, Ibnu Imam; Apriyanti, Niken Siti Nur; Nurhikmah; Rahmawati, Siti
Bustanul Ulum Journal of Islamic Education Vol. 3 No. 1 (2025): Bustanul Ulum Journal of Islamic Education
Publisher : Sekolah Tinggi Ilmu Tarbiyah Bustanul `'Ulum Lampung Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62448/bujie.v3i1.170

Abstract

This study aims to evaluate whether numerical results from IRE exams can accurately reflect students' overall spiritual comprehension. Through both quantitative and qualitative analysis, the study finds that relying solely on test scores is insufficient to assess students’ faith and spiritual insight. Significant differences in learning outcomes between schools suggest that variations in teaching methods and assessment systems contribute to these disparities. Interviews with students and teachers reveal that IRE exams, which tend to emphasize memorization, fall short in uncovering deeper understanding of religious values. In contrast, assessment approaches that are more relevant to everyday life, encourage reflection, utilize narrative methods, and observe student behavior are perceived as more effective. Therefore, an ideal model for assessing Islamic Religious Education should integrate both cognitive evaluation and spiritual reflection through a comprehensive, holistic approach. By combining written assessments with contextual inquiry, personal reflection, and behavioral observation, educators can gain a more accurate and authentic picture of students’ religious understanding. Such a multifaceted evaluation system not only enhances the relevance of PAI but also supports the formation of students who genuinely embody Islamic values in their daily lives.
Pembelajaran Matematika pada Faktor Persekutuan Terbesar dan Kelipatan Persekutuan Terkecil di Sekolah Dasar Andriani, Anita; Al Ayyubi, Ibnu Imam; Nurhikmah; Prayetno, Eko; Khan, Anis
Journal of Primary Education Research Vol. 3 No. 1 (2025): Journal of Primary Education Research
Publisher : Program Studi Pendidikan Guru Sekolah Dasar

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Abstract

This study aims to analyze the impact of mathematics learning on the concepts of the Greatest Common Divisor (GCD) and the Least Common Multiple (LCM) on students' abilities at SDN Pasir Banteng, West Bandung Regency. The population consisted of all students at SDN Pasir Banteng, with a sample of 40 fifth-grade students. The research employed a quantitative method with an explanatory research approach and a causal-correlational study design. The sampling technique used was probability sampling with simple random sampling, and the instruments included questionnaires and tests that had been validated and tested for reliability. Validity and reliability tests were conducted by comparing Cronbach’s Alpha with Cronbach’s Alpha if Item Deleted, using SPSS version 26. The normality test using the Kolmogorov-Smirnov method indicated that the data were not normally distributed, with significance values of 0.000 and 0.003 (p < 0.05). This was also supported by the analysis of the Normal Q-Q Plot, where the data points were not clustered around the diagonal line. Consequently, a non-parametric statistical analysis using Spearman’s correlation was conducted. The results showed a significance value of 0.002 (p < 0.05), indicating a significant impact of GCD learning on students' abilities to understand LCM. The Correlation Coefficient value of 0.470 demonstrated a moderate relationship between the two variables. Therefore, it can be concluded that GCD learning has a significant correlation with students' understanding of LCM, emphasizing the need for teachers to integrate these two concepts effectively in the learning process.
PENERAPAN SISTEM PENDUKUNG KEPUTUSAN METODE TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) REKOMENDASI SISWA BERPRESTASI UNTUK DIAJUKAN KE KELAS UNGGULAN Wahyu Saputro, Angga; Rahman Prehanto, Dedy; Andriani, Anita
Inovate Vol 3 No 2 (2019): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v3i2.734

Abstract

Madrasah tsanawiyah negeri is an islamic school which have the same level as junior high school.Sometimes it requires outstanding students to be recommended to a special class, which not only considersacademic score, but also non-academic of each student. To avoid subjective decision, it need DecisionSupport System (DSS) in providing student recommendations.One of DSS methods to solving a problem is TOPSIS. TOPSIS is based on the concept that the chosenalternative should have the shortest distance from the positive ideal solution as well as the longest distancefrom the negative ideal solutionThis study focuses on providing recommendation of outstanding students at MTsN TambakberasJombang. Observations data are collected from students grade 7 and processed using TOPSIS method. Thecriteria variables are academic score, nonacademic score, extra score, attitude score, attendance score,communication skill, and expertness. The result of preference score is generated by system then comparedwith result of manual. The comparison obtained an accuracy of 99.75%. Then, based on blackbox testingit can be concluded that the system is feasible to be used in this study case.Keywords: DSS, TOPSIS, Recommended Student, Outstanding Class.
SISTEM PEMILIHAN RUMAH KOS TERBAIK DI SEKITAR UNHASY DENGAN METODE MULTI ATTRIBUTE UTILITY THEORY (MAUT) BERBASIS WEB Hidayatullah, Arif; Kadek Dwi Nuryana, I; Andriani, Anita
Inovate Vol 3 No 2 (2019): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v3i2.741

Abstract

Boarding house is temporary house rent by a settled foreigner or someone who stays a way from home. Someof unhasy students from outside the city find some difficulties to get information about the boarding house, they haveto come and compare it. It makes them confused to select the best boarding house. Therefore, it is necesssary to presenta system on selecting a boarding house in order to help the students. The system implements MAUT method with several criteria related to finding the best boarding house. Thesuperiority of the MAUT method is able to process data from multiple criteria which have different attributes. Asanother DSS method, MAUT is only able to solve the problem of semi-structured and non-structured.The system work by searching the result of total evaluation on every boarding house based on the determinedcriteria and alternative clasification. As the result, the system shows the best boarding house to be recomended. the comparison between system and manual calculation gets 100 % accuration. This proves that the MAUT method hasbeen successfully applied to the system, and able to give recomendation the best boarding house based on the specificcriteria above.Keyword : boarding house, decision supporting system, MAUT, Information System
Memprediksi Jumlah Produksi Roti Dengan Menerapkan Metode Monte Carlo Nur Rohmah, Fitri; Arwin Dermawan, Dodik; Andriani, Anita
Inovate Vol 5 No 2 (2021): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v5i2.3120

Abstract

The process of predicting the amount of production is useful for reducing the level of producer losses due to inaccuracy in determining the amount of production, so that the stock of goods which usually experience accumulation or even out of stock is expected no longer. The purpose of this research itself is to design a system using Monte Carlo as a method to predict the amount of bread production. In the Monte Carlo method there is one step in the process using random numbers. The method used to generate random numbers this time is using the Linear Congruent Method (LCM). Hasil method. The results of this research is an application to facilitate the admin of the production sector to predict the amount of bread production for the next day. The prediction of the amount of production for this type of comb bread yields 1461 seeds of bread. The results of testing the accuracy of the Monte Carlo method in predicting the amount of bread production using MAPE, resulting in a fairly small error value of 9.43%. So this research is quite appropriate to be used as a method of predicting the amount of bread production. Keywords: Prediction, Production, Monte Carlo, LCM
Implementasi Algoritma FP Growth Untuk Menganalisa Pola Pembelian Barang (studi kasus : Koperasi) Sabila K.S., Nella; Sujatmiko, Bambang; Andriani, Anita
Inovate Vol 6 No 2 (2022): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v6i2.3173

Abstract

Analyzing piles of sales transaction data turns out to be able to produce information, one of which can take a recommendation and layout decisions of goods such as arranging goods according to association patterns, doing discount or cheap redemption prices on products that are less desirable based on the results of the association pattern, and information on goods that are not in demand. less desirable according to association rules. The association pattern has several solutions, one of which is using the fp growth algorithm. The purpose of using the fp growth algorithm is to find out frequent itemset data sets, in this study the authors apply the fp growth algorithm and association rules to cooperative data for the 1 day period of 2019. The results of this study are to produce applications that can make it easier for cooperatives to take A decision uses 20 sample data to look for association rules and FP growth, which can analyze consumer habits in making purchases, with an average percentage of support values of 9.09% and a confidence value of 100% Keywords: Data Mining, Fp Growth, Association rules, recommendations
Implementasi Algoritma Apriori Untuk Menentukan Strategi Pemasaran Bilqis Ismail Putri, Tiara; Sujatmiko, Bambang; Andriani, Anita
Inovate Vol 7 No 1 (2022): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v7i1.3680

Abstract

Store X is retail that provide a variety of toys for girls and boys. Every day the sales transaction data Store X will definitely increase and accumulate. So that data does not accumulate it is good can be used to know the habits of the buyer or of buyer behavior of goods purchased. How to search the goods sold simultaneously can use the data mining methods, which is a technique to analyze large-sized data by finding relationships among the data or the search combination and rule. The search for a combination is done with the process of merging (join) and pruning (prune) items called apriori algorithm. This research resulted in a website-based system by testing data sales transactions as many as 30 data a memorandum of the transaction with a minimum support of 35% and minimum confidence of 75%. So as to form one rule, namely, if buy a Meja Belajar K then will buy a Kreatif Block Tas with the value of the support 36.67% and the value of the confidence 78.57%. Keywords : Association, Apriori Algorithm, The Transaction Data, Sales
Klasifikasi Komentar Publik Dalam Pemilihan Umum Presiden 2024 Dengan Menggunakan Metode Naive Bayes: Studi Kasus Indentifikasi Haters Dan Non-Haters Imania, Dina; Andriani, Anita; Ali, Mahrus
Inovate Vol 8 No 1 (2023): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v8i1.5096

Abstract

Indonesia is one of the countries that adheres to a democratic system. The democratic system of governmentprioritizes the people. So that when the election of the people's representatives is carried out, the people havethe highest right to go through elections that take place freely. In 2024, the Indonesian presidential electionwill be held. Every moment of the presidential election or presidential general election, there are manyopinions from the public about the rumored presidential candidate. However, in practice, there are manynegative comments that are "hate speech," which can trigger social conflict and damage the politicalenvironment. This research aims to build a classification model of public comments into "haters" and "non-haters" categories in Indonesian using the Naïve Bayes algorithm. This research uses data totaling 1000, withdetails of training data of 800 and test data of 200. With the stages of data collection, data pre-processing,classification with Naïve Bayes, Evaluation, and Deployment. The results obtained an accuracy value of83.5%, a precision value of 82%, and a recall value of 90%.Keywords: Presidential Election; Classification; Naive Bayes.
Co-Authors Abda Abda Adinda Yuli Setiani Agung Rizky Wijaya Alhamdani, Deden Abdul Hamid Apriyanti, Niken Siti Nur Arif Hidayatullah, Arif Arwin Dermawan, Dodik BAMBANG SUJATMIKO Bilqis Ismail Putri, Tiara Dedy Rahman Prehanto Erwin Putubasai F, Reza Augusta Jannatul Farenda, Cika Fatkhur Rizal, Muhammad Firdaus, Reza Augusta Jannatul Ginanjar Setyo Permadi Heru Mujianto , Ahmad I Kadek Dwi Nuryana, I Ibnu Imam Al Ayyubi Iftitaahul Mufarrihah Imania, Dina Indana Lazulfa, Indana Islamiyah, Nadiatul Khan, Anis Kistofer, Terdy Listanto, Firgiawan Mahrus Ali Martini, Sofia Mashuri, Chamdan Muhaemin, Abdul Muhammad Fatkhur Rizal Mujianto, Ahmad Heru Neysa Amallia Noerzanah, Firda Nur Rohmah, Fitri Nurhikmah Perdana, M. Harviend Gilang Prayetno, Eko Qois Al’Ariq Ricky Darmawan Rizky Permadi Syah Sabila K.S., Nella Saputra, Wawan Adi Sari, Desi Wulan Siti Rahmawati Sri Widoyoningrum Sucipto , Hadi Suryana, Irfan Wahyu Saputro, Angga Widiani, Erina Widoyoningrum, Sri Yasmin, Sabrina