{ "job_id": "1", "sertifikat": { "veredik": "belum_ada_celah_jelas", "alasan": "1309 karya relevan sudah ada. Riset ini BERISIKO duplikasi; sarankan memperluas variabel/konteks sebelum lanjut. (veredik deterministik tanpa LLM — minta analisis LLM untuk narasi detail)", "judul_riset": "Pengaruh Kualitas Layanan terhadap Kepuasan Pengguna E-Wallet di Kalangan Mahasiswa", "jumlah_literatur": 1309, "sumber": "OpenAlex (API resmi, gratis $1/hari)", "llm_narasi_tersedia": true, "veredik_oleh": "deterministik + saran LLM", "narasi_celah": "Celah ada, tapi tipis. 1309 paper = topik \"kualitas layanan → kepuasan e-wallet\" sudah jenuh di level umum; kontribusi baru hanya dari segmentasi mahasiswa + model parsial 4-13 (bukan full SERVQUAL 5 dimensi). Yang benar-benar belum banyak: multi-platform switching (mahasiswa pakai GoPay+OVO+Dana sekaligus) dan persepsi biaya transaksional sebagai moderator — hampir tidak ada di 1309 itu. Metodologis, n=150 di SEM-PLS dengan 4 konstruk masih di atas batas minimum (10× jalur terpanjang ≈ 130), tapi common-method-bias di survei kuesioner tunggal tidak terlihat diuji di mayoritas paper sejenis — celah validitas, bukan celah teori. Jujur: ini replication study di konteks sempit, bukan discovery. Layak untuk skripsi/tesis, tidak layak klaim \"gap of knowledge\" di jurnal Q1." }, "statistik": { "model": { "urutan_konstruk": [ "Kualitas", "Kepercayaan", "Kepuasan", "Loyalitas" ], "indikator": { "Kualitas": [ "K1", "K2", "K3", "K4" ], "Kepercayaan": [ "T1", "T2", "T3" ], "Kepuasan": [ "P1", "P2", "P3" ], "Loyalitas": [ "L1", "L2", "L3" ] }, "target": "Loyalitas", "targets": [ "Loyalitas" ] }, "n": 150, "path": { "Kualitas->Loyalitas": 0.05242957393356653, "Kepercayaan->Loyalitas": 0.1954521551159734, "Kepuasan->Loyalitas": 0.4459858802443328 }, "r2": { "Kualitas": 0.0, "Kepercayaan": 0.0, "Kepuasan": 0.0, "Loyalitas": 0.3043142296661757 }, "loadings": { "K1": 0.8729581129992747, "K2": 0.7318562947254632, "K3": 0.8741606109949275, "K4": 0.8017131834843974, "L1": 0.9071976136969118, "L2": 0.90542521482238, "L3": 0.8786486667125057, "P1": 0.8982061921622133, "P2": 0.8818027673855344, "P3": 0.8918528191972313, "T1": 0.8578476180311567, "T2": 0.8942884127466039, "T3": 0.8871095957842753 }, "ave": { "Kualitas": 0.6761425763920625, "Kepercayaan": 0.7742059119557032, "Kepuasan": 0.7932506451057929, "Loyalitas": 0.8049419364830627 }, "cr": { "Kualitas": 0.8983458901881255, "Kepercayaan": 0.9115007507441697, "Kepuasan": 0.9200750351673243, "Loyalitas": 0.9252926185659321 }, "htmt": { "Kualitas<->Kepercayaan": 0.053418822760194926, "Kualitas<->Kepuasan": 0.3074838382304231, "Kualitas<->Loyalitas": 0.17351598676804872, "Kepercayaan<->Kepuasan": 0.3450804376087441, "Kepercayaan<->Loyalitas": 0.3806987239172806, "Kepuasan<->Loyalitas": 0.5907620461770663 }, "vif": { "Kualitas": { "K1": 2.2720178331718177, "K2": 1.7585878345057042, "K3": 1.8022956509156791, "K4": 1.9653556406792725 }, "Kepercayaan": { "T1": 1.935689380703612, "T2": 2.4176871135953397, "T3": 2.1497791432955076 }, "Kepuasan": { "P1": 2.3710102324898066, "P2": 2.176885446027149, "P3": 2.3494306411689445 }, "Loyalitas": { "L1": 2.576180634813274, "L2": 2.5281338340986643, "L3": 2.22679526194002 } }, "f2": { "Kualitas": 0.003656791604048319, "Kepercayaan": 0.049721065389077855, "Kepuasan": 0.24104150410187786 }, "interpretasi": { "path": { "Kualitas->Loyalitas": { "nilai": 0.0524, "kategori": "sangat kecil", "status": "masalah", "rumus": "\\beta_{Kualitas \\to Loyalitas} = 0.0524", "catatan": "Pengaruh positif sangat kecil dari Kualitas ke Loyalitas." }, "Kepercayaan->Loyalitas": { "nilai": 0.1955, "kategori": "kecil", "status": "baik", "rumus": "\\beta_{Kepercayaan \\to Loyalitas} = 0.1955", "catatan": "Pengaruh positif kecil dari Kepercayaan ke Loyalitas." }, "Kepuasan->Loyalitas": { "nilai": 0.446, "kategori": "sedang", "status": "baik", "rumus": "\\beta_{Kepuasan \\to Loyalitas} = 0.4460", "catatan": "Pengaruh positif sedang dari Kepuasan ke Loyalitas." } }, "r2": { "Loyalitas": { "nilai": 0.3043, "kategori": "lemah", "status": "waspada", "rumus": "R^2_{Loyalitas} = 1 - \\frac{SSE}{SST} = 0.3043", "catatan": "Variasi Loyalitas terjelaskan model sebesar 30.4%." } }, "loadings": { "K1": { "nilai": 0.873, "status": "baik", "rumus": "\\lambda_{K1} = 0.8730", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "K2": { "nilai": 0.7319, "status": "baik", "rumus": "\\lambda_{K2} = 0.7319", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "K3": { "nilai": 0.8742, "status": "baik", "rumus": "\\lambda_{K3} = 0.8742", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "K4": { "nilai": 0.8017, "status": "baik", "rumus": "\\lambda_{K4} = 0.8017", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "L1": { "nilai": 0.9072, "status": "baik", "rumus": "\\lambda_{L1} = 0.9072", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "L2": { "nilai": 0.9054, "status": "baik", "rumus": "\\lambda_{L2} = 0.9054", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "L3": { "nilai": 0.8786, "status": "baik", "rumus": "\\lambda_{L3} = 0.8786", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "P1": { "nilai": 0.8982, "status": "baik", "rumus": "\\lambda_{P1} = 0.8982", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "P2": { "nilai": 0.8818, "status": "baik", "rumus": "\\lambda_{P2} = 0.8818", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "P3": { "nilai": 0.8919, "status": "baik", "rumus": "\\lambda_{P3} = 0.8919", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "T1": { "nilai": 0.8578, "status": "baik", "rumus": "\\lambda_{T1} = 0.8578", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "T2": { "nilai": 0.8943, "status": "baik", "rumus": "\\lambda_{T2} = 0.8943", "catatan": "indikator merepresentasikan konstruknya dengan baik" }, "T3": { "nilai": 0.8871, "status": "baik", "rumus": "\\lambda_{T3} = 0.8871", "catatan": "indikator merepresentasikan konstruknya dengan baik" } }, "ave": { "Kualitas": { "nilai": 0.6761, "status": "baik", "rumus": "AVE_{Kualitas} = \\frac{\\sum_i \\lambda_i^2}{n} = 0.6761", "catatan": "validitas konvergen terpenuhi" }, "Kepercayaan": { "nilai": 0.7742, "status": "baik", "rumus": "AVE_{Kepercayaan} = \\frac{\\sum_i \\lambda_i^2}{n} = 0.7742", "catatan": "validitas konvergen terpenuhi" }, "Kepuasan": { "nilai": 0.7933, "status": "baik", "rumus": "AVE_{Kepuasan} = \\frac{\\sum_i \\lambda_i^2}{n} = 0.7933", "catatan": "validitas konvergen terpenuhi" }, "Loyalitas": { "nilai": 0.8049, "status": "baik", "rumus": "AVE_{Loyalitas} = \\frac{\\sum_i \\lambda_i^2}{n} = 0.8049", "catatan": "validitas konvergen terpenuhi" } }, "cr": { "Kualitas": { "nilai": 0.8983, "status": "baik", "rumus": "\\rho_c = \\frac{(\\sum_i \\lambda_i)^2}{(\\sum_i \\lambda_i)^2 + \\sum_i (1-\\lambda_i^2)} = 0.8983", "catatan": "reliabilitas konstruk memadai" }, "Kepercayaan": { "nilai": 0.9115, "status": "baik", "rumus": "\\rho_c = \\frac{(\\sum_i \\lambda_i)^2}{(\\sum_i \\lambda_i)^2 + \\sum_i (1-\\lambda_i^2)} = 0.9115", "catatan": "reliabilitas konstruk memadai" }, "Kepuasan": { "nilai": 0.9201, "status": "baik", "rumus": "\\rho_c = \\frac{(\\sum_i \\lambda_i)^2}{(\\sum_i \\lambda_i)^2 + \\sum_i (1-\\lambda_i^2)} = 0.9201", "catatan": "reliabilitas konstruk memadai" }, "Loyalitas": { "nilai": 0.9253, "status": "baik", "rumus": "\\rho_c = \\frac{(\\sum_i \\lambda_i)^2}{(\\sum_i \\lambda_i)^2 + \\sum_i (1-\\lambda_i^2)} = 0.9253", "catatan": "reliabilitas konstruk memadai" } }, "htmt": { "Kualitas<->Kepercayaan": { "nilai": 0.0534, "status": "baik", "rumus": "HTMT_{Kualitas<, >Kepercayaan} = \\frac{\\mathrm{mean}(r_{antara})}{\\sqrt{\\mathrm{mean}(r_{dalam,1})\\cdot\\mathrm{mean}(r_{dalam,2})}} = 0.0534", "catatan": "diskriminasi antar-konstruk baik" }, "Kualitas<->Kepuasan": { "nilai": 0.3075, "status": "baik", "rumus": "HTMT_{Kualitas<, >Kepuasan} = \\frac{\\mathrm{mean}(r_{antara})}{\\sqrt{\\mathrm{mean}(r_{dalam,1})\\cdot\\mathrm{mean}(r_{dalam,2})}} = 0.3075", "catatan": "diskriminasi antar-konstruk baik" }, "Kualitas<->Loyalitas": { "nilai": 0.1735, "status": "baik", "rumus": "HTMT_{Kualitas<, >Loyalitas} = \\frac{\\mathrm{mean}(r_{antara})}{\\sqrt{\\mathrm{mean}(r_{dalam,1})\\cdot\\mathrm{mean}(r_{dalam,2})}} = 0.1735", "catatan": "diskriminasi antar-konstruk baik" }, "Kepercayaan<->Kepuasan": { "nilai": 0.3451, "status": "baik", "rumus": "HTMT_{Kepercayaan<, >Kepuasan} = \\frac{\\mathrm{mean}(r_{antara})}{\\sqrt{\\mathrm{mean}(r_{dalam,1})\\cdot\\mathrm{mean}(r_{dalam,2})}} = 0.3451", "catatan": "diskriminasi antar-konstruk baik" }, "Kepercayaan<->Loyalitas": { "nilai": 0.3807, "status": "baik", "rumus": "HTMT_{Kepercayaan<, >Loyalitas} = \\frac{\\mathrm{mean}(r_{antara})}{\\sqrt{\\mathrm{mean}(r_{dalam,1})\\cdot\\mathrm{mean}(r_{dalam,2})}} = 0.3807", "catatan": "diskriminasi antar-konstruk baik" }, "Kepuasan<->Loyalitas": { "nilai": 0.5908, "status": "baik", "rumus": "HTMT_{Kepuasan<, >Loyalitas} = \\frac{\\mathrm{mean}(r_{antara})}{\\sqrt{\\mathrm{mean}(r_{dalam,1})\\cdot\\mathrm{mean}(r_{dalam,2})}} = 0.5908", "catatan": "diskriminasi antar-konstruk baik" } }, "vif": { "Kualitas.K1": { "nilai": 2.272, "status": "baik", "rumus": "VIF_{K1} = \\frac{1}{1 - R_i^2} = 2.2720", "catatan": "tidak ada multikolinearitas" }, "Kualitas.K2": { "nilai": 1.7586, "status": "baik", "rumus": "VIF_{K2} = \\frac{1}{1 - R_i^2} = 1.7586", "catatan": "tidak ada multikolinearitas" }, "Kualitas.K3": { "nilai": 1.8023, "status": "baik", "rumus": "VIF_{K3} = \\frac{1}{1 - R_i^2} = 1.8023", "catatan": "tidak ada multikolinearitas" }, "Kualitas.K4": { "nilai": 1.9654, "status": "baik", "rumus": "VIF_{K4} = \\frac{1}{1 - R_i^2} = 1.9654", "catatan": "tidak ada multikolinearitas" }, "Kepercayaan.T1": { "nilai": 1.9357, "status": "baik", "rumus": "VIF_{T1} = \\frac{1}{1 - R_i^2} = 1.9357", "catatan": "tidak ada multikolinearitas" }, "Kepercayaan.T2": { "nilai": 2.4177, "status": "baik", "rumus": "VIF_{T2} = \\frac{1}{1 - R_i^2} = 2.4177", "catatan": "tidak ada multikolinearitas" }, "Kepercayaan.T3": { "nilai": 2.1498, "status": "baik", "rumus": "VIF_{T3} = \\frac{1}{1 - R_i^2} = 2.1498", "catatan": "tidak ada multikolinearitas" }, "Kepuasan.P1": { "nilai": 2.371, "status": "baik", "rumus": "VIF_{P1} = \\frac{1}{1 - R_i^2} = 2.3710", "catatan": "tidak ada multikolinearitas" }, "Kepuasan.P2": { "nilai": 2.1769, "status": "baik", "rumus": "VIF_{P2} = \\frac{1}{1 - R_i^2} = 2.1769", "catatan": "tidak ada multikolinearitas" }, "Kepuasan.P3": { "nilai": 2.3494, "status": "baik", "rumus": "VIF_{P3} = \\frac{1}{1 - R_i^2} = 2.3494", "catatan": "tidak ada multikolinearitas" }, "Loyalitas.L1": { "nilai": 2.5762, "status": "baik", "rumus": "VIF_{L1} = \\frac{1}{1 - R_i^2} = 2.5762", "catatan": "tidak ada multikolinearitas" }, "Loyalitas.L2": { "nilai": 2.5281, "status": "baik", "rumus": "VIF_{L2} = \\frac{1}{1 - R_i^2} = 2.5281", "catatan": "tidak ada multikolinearitas" }, "Loyalitas.L3": { "nilai": 2.2268, "status": "baik", "rumus": "VIF_{L3} = \\frac{1}{1 - R_i^2} = 2.2268", "catatan": "tidak ada multikolinearitas" } }, "f2": { "Kualitas": { "nilai": 0.0037, "kategori": "diabaikan", "status": "masalah", "rumus": "f^2_{Kualitas} = \\frac{R^2_{inklusi} - R^2_{eksklusi}}{1 - R^2_{inklusi}} = 0.0037", "catatan": "Ukuran efek Kualitas: diabaikan (Cohen)." }, "Kepercayaan": { "nilai": 0.0497, "kategori": "kecil", "status": "baik", "rumus": "f^2_{Kepercayaan} = \\frac{R^2_{inklusi} - R^2_{eksklusi}}{1 - R^2_{inklusi}} = 0.0497", "catatan": "Ukuran efek Kepercayaan: kecil (Cohen)." }, "Kepuasan": { "nilai": 0.241, "kategori": "sedang", "status": "baik", "rumus": "f^2_{Kepuasan} = \\frac{R^2_{inklusi} - R^2_{eksklusi}}{1 - R^2_{inklusi}} = 0.2410", "catatan": "Ukuran efek Kepuasan: sedang (Cohen)." } } }, "bootstrap": { "n_iterations": 200, "metode": "percentile 2.5 / 97.5", "path_ci": { "Kualitas->Loyalitas": { "estimat": 0.05243, "mean": 0.064827, "std_error": 0.088918, "ci_lower": -0.1775, "ci_upper": 0.209413, "t_stat": 0.589643 }, "Kepercayaan->Loyalitas": { "estimat": 0.195452, "mean": 0.20809, "std_error": 0.073729, "ci_lower": 0.064291, "ci_upper": 0.354221, "t_stat": 2.650968 }, "Kepuasan->Loyalitas": { "estimat": 0.445986, "mean": 0.437739, "std_error": 0.073302, "ci_lower": 0.298319, "ci_upper": 0.563842, "t_stat": 6.084204 } }, "r2_ci": { "Loyalitas": { "estimat": 0.304314, "mean": 0.326753, "std_error": 0.059562, "ci_lower": 0.227361, "ci_upper": 0.435374, "t_stat": 5.109174 } } }, "ipma": { "target": "Loyalitas", "indicators": {}, "constructs": { "K3": { "importance": 0.0, "performance": 50.0 }, "K4": { "importance": 0.0, "performance": 50.0 }, "P1": { "importance": 0.0, "performance": 50.0 }, "T3": { "importance": 0.0, "performance": 50.0 }, "K2": { "importance": 0.0, "performance": 50.0 }, "P3": { "importance": 0.0, "performance": 50.0 }, "L1": { "importance": 0.0, "performance": 50.0 }, "L2": { "importance": 0.0, "performance": 50.0 }, "L3": { "importance": 0.0, "performance": 50.0 }, "T2": { "importance": 0.0, "performance": 50.0 }, "T1": { "importance": 0.0, "performance": 50.0 }, "P2": { "importance": 0.0, "performance": 50.0 }, "K1": { "importance": 0.0, "performance": 50.0 } }, "quadrants": { "keep_up": [ "K3", "K4", "P1", "T3", "K2", "P3", "L1", "L2", "L3", "T2", "T1", "P2", "K1" ], "concentrate": [], "low_priority": [], "possible_overkill": [] } }, "cross_validation": { "status": "DIVERIFIKASI_SILANG", "n_koefisien": 3, "selisih_maks": 0.079434, "searah_semua": true, "detail": "03_matrix/cross_validation.json" }, "cfa": { "status": "LULUS", "alasan": "Semua loading, AVE, dan CR memenuhi ambang.", "n": 150, "loadings": { "Kualitas": { "K1": 0.840972, "K2": 0.716592, "K3": 0.732111, "K4": 0.769461 }, "Kepercayaan": { "T1": 0.763923, "T2": 0.8644, "T3": 0.81531 }, "Kepuasan": { "P1": 0.846656, "P2": 0.808259, "P3": 0.837275 }, "Loyalitas": { "L1": 0.863404, "L2": 0.857577, "L3": 0.80252 } }, "reliabilitas": { "Kualitas": { "CR": 0.85002, "AVE": 0.587199 }, "Kepercayaan": { "CR": 0.856003, "AVE": 0.665165 }, "Kepuasan": { "CR": 0.869905, "AVE": 0.690379 }, "Loyalitas": { "CR": 0.879188, "AVE": 0.708314 } }, "fit": { "CFI": 1.007137, "TLI": 1.009436, "RMSEA": 0.0, "chi2": 52.117037, "DoF": 59.0 }, "loading_terstandar": true }, "efa": { "muatan_faktor": { "K1": [ -0.45294427579114777, -0.8458804941232183, -0.3709449246675437 ], "K2": [ -0.2895592785407379, -0.6866283288218011, -0.2953471578955113 ], "K3": [ -0.3742224745074006, -0.7631299512965847, -0.14844727342321393 ], "K4": [ -0.2936900091714276, -0.7573476593433331, -0.24129282498763086 ], "T1": [ -0.6314952151693984, 0.45943769157508546, -0.47853723007494464 ], "T2": [ -0.6628542131270336, 0.49390250650641454, -0.5767554842741683 ], "T3": [ -0.6630266882818444, 0.46262024559724063, -0.48487190258625806 ], "P1": [ -0.7944892905577652, -0.14286733060703638, 0.17057143543454073 ], "P2": [ -0.7480785988831669, -0.11488225870487768, 0.16530887201772507 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